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erasromani/isaac-sim-python/grasp/grasping_scenarios/franka.py | # Credits: The majority of this code is taken from build code associated with nvidia/isaac-sim:2020.2.2_ea with minor modifications.
import time
import os
import numpy as np
import carb.tokens
import omni.kit.settings
from pxr import Usd, UsdGeom, Gf
from collections import deque
from omni.isaac.dynamic_control import _dynamic_control
from omni.isaac.motion_planning import _motion_planning
from omni.isaac.samples.scripts.utils import math_utils
# default joint configuration
default_config = (0.00, -1.3, 0.00, -2.87, 0.00, 2.00, 0.75)
# Alternative default config for motion planning
alternate_config = [
(1.5356, -1.3813, -1.5151, -2.0015, -1.3937, 1.5887, 1.4597),
(-1.5356, -1.3813, 1.5151, -2.0015, 1.3937, 1.5887, 0.4314),
]
class Gripper:
"""
Gripper for franka.
"""
def __init__(self, dc, ar):
"""
Initialize gripper.
Args:
dc (omni.isaac.motion_planning._motion_planning.MotionPlanning): motion planning interface from RMP extension
ar (int): articulation identifier
"""
self.dc = dc
self.ar = ar
self.finger_j1 = self.dc.find_articulation_dof(self.ar, "panda_finger_joint1")
self.finger_j2 = self.dc.find_articulation_dof(self.ar, "panda_finger_joint2")
self.width = 0
self.width_history = deque(maxlen=50)
def open(self, wait=False):
"""
Open gripper.
"""
if self.width < 0.045:
self.move(0.045, wait=True)
self.move(0.09, wait=wait)
def close(self, wait=False, force=0):
"""
Close gripper.
"""
self.move(0, wait=wait)
def move(self, width=0.03, speed=0.2, wait=False):
"""
Modify width.
"""
self.width = width
# if wait:
# time.sleep(0.5)
def update(self):
"""
Actuate gripper.
"""
self.dc.set_dof_position_target(self.finger_j1, self.width * 0.5 * 100)
self.dc.set_dof_position_target(self.finger_j2, self.width * 0.5 * 100)
self.width_history.append(self.get_width())
def get_width(self):
"""
Get current width.
"""
return sum(self.get_position())
def get_position(self):
"""
Get left and right finger local position.
"""
return self.dc.get_dof_position(self.finger_j1), self.dc.get_dof_position(self.finger_j2)
def get_velocity(self, from_articulation=True):
"""
Get left and right finger local velocity.
"""
if from_articulation:
return (self.dc.get_dof_velocity(self.finger_j1), self.dc.get_dof_velocity(self.finger_j2))
else:
leftfinger_handle = self.dc.get_rigid_body(self.dc.get_articulation_path(self.ar) + '/panda_leftfinger')
rightfinger_handle = self.dc.get_rigid_body(self.dc.get_articulation_path(self.ar) + '/panda_rightfinger')
leftfinger_velocity = np.linalg.norm(np.array(self.dc.get_rigid_body_local_linear_velocity(leftfinger_handle)))
rightfinger_velocity = np.linalg.norm(np.array(self.dc.get_rigid_body_local_linear_velocity(rightfinger_handle)))
return (leftfinger_velocity, rightfinger_velocity)
def is_moving(self, tol=1e-2):
"""
Determine if gripper fingers are moving
"""
if len(self.width_history) < self.width_history.maxlen or np.array(self.width_history).std() > tol:
return True
else:
return False
def get_state(self):
"""
Get gripper state.
"""
dof_states = self.dc.get_articulation_dof_states(self.ar, _dynamic_control.STATE_ALL)
return dof_states[-2], dof_states[-1]
def is_closed(self, tol=1e-2):
"""
Determine if gripper is closed.
"""
if self.get_width() < tol:
return True
else:
return False
class Status:
"""
Class that contains status for end effector
"""
def __init__(self, mp, rmp_handle):
"""
Initialize status object.
Args:
mp (omni.isaac.dynamic_control._dynamic_control.DynamicControl): dynamic control interface
rmp_handle (int): RMP handle identifier
"""
self.mp = mp
self.rmp_handle = rmp_handle
self.orig = np.array([0, 0, 0])
self.axis_x = np.array([1, 0, 0])
self.axis_y = np.array([0, 1, 0])
self.axis_z = np.array([0, 0, 1])
self.current_frame = {"orig": self.orig, "axis_x": self.axis_x, "axis_y": self.axis_y, "axis_z": self.axis_z}
self.target_frame = {"orig": self.orig, "axis_x": self.axis_x, "axis_y": self.axis_y, "axis_z": self.axis_z}
self.frame = self.current_frame
def update(self):
"""
Update end effector state.
"""
state = self.mp.getRMPState(self.rmp_handle)
target = self.mp.getRMPTarget(self.rmp_handle)
self.orig = np.array([state[0].x, state[0].y, state[0].z])
self.axis_x = np.array([state[1].x, state[1].y, state[1].z])
self.axis_y = np.array([state[2].x, state[2].y, state[2].z])
self.axis_z = np.array([state[3].x, state[3].y, state[3].z])
self.current_frame = {"orig": self.orig, "axis_x": self.axis_x, "axis_y": self.axis_y, "axis_z": self.axis_z}
self.frame = self.current_frame
self.current_target = {
"orig": np.array([target[0].x, target[0].y, target[0].z]),
"axis_x": np.array([target[1].x, target[1].y, target[1].z]),
"axis_y": np.array([target[2].x, target[2].y, target[2].z]),
"axis_z": np.array([target[3].x, target[3].y, target[3].z]),
}
class EndEffector:
"""
End effector object that controls movement.
"""
def __init__(self, dc, mp, ar, rmp_handle):
"""
Initialize end effector.
Args:
dc (omni.isaac.motion_planning._motion_planning.MotionPlanning): motion planning interface from RMP extension
mp (omni.isaac.dynamic_control._dynamic_control.DynamicControl): dynamic control interface
ar (int): articulation identifier
rmp_handle (int): RMP handle identifier
"""
self.dc = dc
self.ar = ar
self.mp = mp
self.rmp_handle = rmp_handle
self.gripper = Gripper(dc, ar)
self.status = Status(mp, rmp_handle)
self.UpRot = Gf.Rotation(Gf.Vec3d(0, 0, 1), 90)
def freeze(self):
self.go_local(
orig=self.status.orig, axis_x=self.status.axis_x, axis_z=self.status.axis_z, wait_for_target=False
)
def go_local(
self,
target=None,
orig=[],
axis_x=[],
axis_y=[],
axis_z=[],
required_orig_err=0.01,
required_axis_x_err=0.01,
required_axis_y_err=0.01,
required_axis_z_err=0.01,
orig_thresh=None,
axis_x_thresh=None,
axis_y_thresh=None,
axis_z_thresh=None,
approach_direction=[],
approach_standoff=0.1,
approach_standoff_std_dev=0.001,
use_level_surface_orientation=False,
use_target_weight_override=True,
use_default_config=False,
wait_for_target=True,
wait_time=None,
):
self.target_weight_override_value = 10000.0
self.target_weight_override_std_dev = 0.03
if orig_thresh:
required_orig_err = orig_thresh
if axis_x_thresh:
required_axis_x_err = axis_x_thresh
if axis_y_thresh:
required_axis_y_err = axis_y_thresh
if axis_z_thresh:
required_axis_z_err = axis_z_thresh
if target:
orig = target["orig"]
if "axis_x" in target and target["axis_x"] is not None:
axis_x = target["axis_x"]
if "axis_y" in target and target["axis_y"] is not None:
axis_y = target["axis_y"]
if "axis_z" in target and target["axis_z"] is not None:
axis_z = target["axis_z"]
orig = np.array(orig)
axis_x = np.array(axis_x)
axis_y = np.array(axis_y)
axis_z = np.array(axis_z)
approach = _motion_planning.Approach((0, 0, 1), 0, 0)
if len(approach_direction) != 0:
approach = _motion_planning.Approach(approach_direction, approach_standoff, approach_standoff_std_dev)
pose_command = _motion_planning.PartialPoseCommand()
if len(orig) > 0:
pose_command.set(_motion_planning.Command(orig, approach), int(_motion_planning.FrameElement.ORIG))
if len(axis_x) > 0:
pose_command.set(_motion_planning.Command(axis_x), int(_motion_planning.FrameElement.AXIS_X))
if len(axis_y) > 0:
pose_command.set(_motion_planning.Command(axis_y), int(_motion_planning.FrameElement.AXIS_Y))
if len(axis_z) > 0:
pose_command.set(_motion_planning.Command(axis_z), int(_motion_planning.FrameElement.AXIS_Z))
self.mp.goLocal(self.rmp_handle, pose_command)
if wait_for_target and wait_time:
error = 1
future_time = time.time() + wait_time
while error > required_orig_err and time.time() < future_time:
# time.sleep(0.1)
error = self.mp.getError(self.rmp_handle)
def look_at(self, gripper_pos, target):
# Y up works for look at but sometimes flips, go_local might be a safer bet with a locked y_axis
orientation = math_utils.lookAt(gripper_pos, target, (0, 1, 0))
mat = Gf.Matrix3d(orientation).GetTranspose()
self.go_local(
orig=[gripper_pos[0], gripper_pos[1], gripper_pos[2]],
axis_x=[mat.GetColumn(0)[0], mat.GetColumn(0)[1], mat.GetColumn(0)[2]],
axis_z=[mat.GetColumn(2)[0], mat.GetColumn(2)[1], mat.GetColumn(2)[2]],
)
class Franka:
"""
Franka objects that contains implementation details for robot control.
"""
def __init__(self, stage, prim, dc, mp, world=None, group_path="", default_config=None, is_ghost=False):
"""
Initialize Franka controller.
Args:
stage (pxr.Usd.Stage): usd stage
prim (pxr.Usd.Prim): robot prim
dc (omni.isaac.motion_planning._motion_planning.MotionPlanning): motion planning interface from RMP extension
mp (omni.isaac.dynamic_control._dynamic_control.DynamicControl): dynamic control interface
world (omni.isaac.samples.scripts.utils.world.World): simulation world handler
default_config (tuple or list): default configuration for robot revolute joint drivers
is_ghost (bool): flag for turning off collision and modifying visuals for robot arm
"""
self.dc = dc
self.mp = mp
self.prim = prim
self.stage = stage
# get handle to the articulation for this franka
self.ar = self.dc.get_articulation(prim.GetPath().pathString)
self.is_ghost = is_ghost
self.base = self.dc.get_articulation_root_body(self.ar)
body_count = self.dc.get_articulation_body_count(self.ar)
for bodyIdx in range(body_count):
body = self.dc.get_articulation_body(self.ar, bodyIdx)
self.dc.set_rigid_body_disable_gravity(body, True)
exec_folder = os.path.abspath(
carb.tokens.get_tokens_interface().resolve(
f"{os.environ['ISAAC_PATH']}/exts/omni.isaac.motion_planning/resources/lula/lula_franka"
)
)
self.rmp_handle = self.mp.registerRmp(
exec_folder + "/urdf/lula_franka_gen.urdf",
exec_folder + "/config/robot_descriptor.yaml",
exec_folder + "/config/franka_rmpflow_common.yaml",
prim.GetPath().pathString,
"right_gripper",
True,
)
print("franka rmp handle", self.rmp_handle)
if world is not None:
self.world = world
self.world.rmp_handle = self.rmp_handle
self.world.register_parent(self.base, self.prim, "panda_link0")
settings = omni.kit.settings.get_settings_interface()
self.mp.setFrequency(self.rmp_handle, settings.get("/physics/timeStepsPerSecond"), True)
self.end_effector = EndEffector(self.dc, self.mp, self.ar, self.rmp_handle)
if default_config:
self.mp.setDefaultConfig(self.rmp_handle, default_config)
self.target_visibility = True
if self.is_ghost:
self.target_visibility = False
self.imageable = UsdGeom.Imageable(self.prim)
def __del__(self):
"""
Unregister RMP.
"""
self.mp.unregisterRmp(self.rmp_handle)
print(" Delete Franka")
def set_pose(self, pos, rot):
"""
Set robot pose.
"""
self._mp.setTargetLocal(self.rmp_handle, pos, rot)
def set_speed(self, speed_level):
"""
Set robot speed.
"""
pass
def update(self):
"""
Update robot state.
"""
self.end_effector.gripper.update()
self.end_effector.status.update()
if self.imageable:
if self.target_visibility is not self.imageable.ComputeVisibility(Usd.TimeCode.Default()):
if self.target_visibility:
self.imageable.MakeVisible()
else:
self.imageable.MakeInvisible()
def send_config(self, config):
"""
Set robot default configuration.
"""
if self.is_ghost is False:
self.mp.setDefaultConfig(self.rmp_handle, config)
|
erasromani/isaac-sim-python/grasp/utils/isaac_utils.py | # Credits: All code except class RigidBody and Camera is taken from build code associated with nvidia/isaac-sim:2020.2.2_ea.
import numpy as np
import omni.kit
from pxr import Usd, UsdGeom, Gf, PhysicsSchema, PhysxSchema
def create_prim_from_usd(stage, prim_env_path, prim_usd_path, location):
"""
Create prim from usd.
"""
envPrim = stage.DefinePrim(prim_env_path, "Xform") # create an empty Xform at the given path
envPrim.GetReferences().AddReference(prim_usd_path) # attach the USD to the given path
set_translate(envPrim, location) # set pose
return stage.GetPrimAtPath(envPrim.GetPath().pathString)
def set_up_z_axis(stage):
"""
Utility function to specify the stage with the z axis as "up".
"""
rootLayer = stage.GetRootLayer()
rootLayer.SetPermissionToEdit(True)
with Usd.EditContext(stage, rootLayer):
UsdGeom.SetStageUpAxis(stage, UsdGeom.Tokens.z)
def set_translate(prim, new_loc):
"""
Specify position of a given prim, reuse any existing transform ops when possible.
"""
properties = prim.GetPropertyNames()
if "xformOp:translate" in properties:
translate_attr = prim.GetAttribute("xformOp:translate")
translate_attr.Set(new_loc)
elif "xformOp:translation" in properties:
translation_attr = prim.GetAttribute("xformOp:translate")
translation_attr.Set(new_loc)
elif "xformOp:transform" in properties:
transform_attr = prim.GetAttribute("xformOp:transform")
matrix = prim.GetAttribute("xformOp:transform").Get()
matrix.SetTranslateOnly(new_loc)
transform_attr.Set(matrix)
else:
xform = UsdGeom.Xformable(prim)
xform_op = xform.AddXformOp(UsdGeom.XformOp.TypeTransform, UsdGeom.XformOp.PrecisionDouble, "")
xform_op.Set(Gf.Matrix4d().SetTranslate(new_loc))
def set_rotate(prim, rot_mat):
"""
Specify orientation of a given prim, reuse any existing transform ops when possible.
"""
properties = prim.GetPropertyNames()
if "xformOp:rotate" in properties:
rotate_attr = prim.GetAttribute("xformOp:rotate")
rotate_attr.Set(rot_mat)
elif "xformOp:transform" in properties:
transform_attr = prim.GetAttribute("xformOp:transform")
matrix = prim.GetAttribute("xformOp:transform").Get()
matrix.SetRotateOnly(rot_mat.ExtractRotation())
transform_attr.Set(matrix)
else:
xform = UsdGeom.Xformable(prim)
xform_op = xform.AddXformOp(UsdGeom.XformOp.TypeTransform, UsdGeom.XformOp.PrecisionDouble, "")
xform_op.Set(Gf.Matrix4d().SetRotate(rot_mat))
def create_background(stage, background_stage):
"""
Create background stage.
"""
background_path = "/background"
if not stage.GetPrimAtPath(background_path):
backPrim = stage.DefinePrim(background_path, "Xform")
backPrim.GetReferences().AddReference(background_stage)
# Move the stage down -104cm so that the floor is below the table wheels, move in y axis to get light closer
set_translate(backPrim, Gf.Vec3d(0, -400, -104))
def setup_physics(stage):
"""
Set default physics parameters.
"""
# Specify gravity
metersPerUnit = UsdGeom.GetStageMetersPerUnit(stage)
gravityScale = 9.81 / metersPerUnit
gravity = Gf.Vec3f(0.0, 0.0, -gravityScale)
scene = PhysicsSchema.PhysicsScene.Define(stage, "/physics/scene")
scene.CreateGravityAttr().Set(gravity)
PhysxSchema.PhysxSceneAPI.Apply(stage.GetPrimAtPath("/physics/scene"))
physxSceneAPI = PhysxSchema.PhysxSceneAPI.Get(stage, "/physics/scene")
physxSceneAPI.CreatePhysxSceneEnableCCDAttr(True)
physxSceneAPI.CreatePhysxSceneEnableStabilizationAttr(True)
physxSceneAPI.CreatePhysxSceneEnableGPUDynamicsAttr(False)
physxSceneAPI.CreatePhysxSceneBroadphaseTypeAttr("MBP")
physxSceneAPI.CreatePhysxSceneSolverTypeAttr("TGS")
class Camera:
"""
Camera object that contain state information for a camera in the scene.
"""
def __init__(self, camera_path, translation, rotation):
"""
Initializes the Camera object.
Args:
camera_path (str): path of camera in stage hierarchy
translation (list or tuple): camera position
rotation (list or tuple): camera orientation described by euler angles in degrees
"""
self.prim = self._kit.create_prim(
camera_path,
"Camera",
translation=translation,
rotation=rotatation,
)
self.name = self.prim.GetPrimPath().name
self.vpi = omni.kit.viewport.get_viewport_interface
def set_translate(self, position):
"""
Set camera position.
Args:
position (tuple): camera position specified by (X, Y, Z)
"""
if not isinstance(position, tuple): position = tuple(position)
translate_attr = self.prim.GetAttribute("xformOp:translate")
translate_attr.Set(position)
def set_rotate(self, rotation):
"""
Set camera position.
Args:
rotation (tuple): camera orientation specified by three euler angles in degrees
"""
if not isinstance(rotation, tuple): rotation = tuple(rotation)
rotate_attr = self.prim.GetAttribute("xformOp:rotateZYX")
rotate_attr.Set(rotation)
def activate(self):
"""
Activate camera to viewport.
"""
self.vpi.get_viewport_window().set_active_camera(str(self.prim.GetPath()))
def __repr__(self):
return self.name
class Camera:
"""
Camera object that contain state information for a camera in the scene.
"""
def __init__(self, camera_path, translation, rotation):
"""
Initializes the Camera object.
Args:
camera_path (str): path of camera in stage hierarchy
translation (list or tuple): camera position
rotation (list or tuple): camera orientation described by euler angles in degrees
"""
self.prim = self._kit.create_prim(
camera_path,
"Camera",
translation=translation,
rotation=rotation,
)
self.name = self.prim.GetPrimPath().name
self.vpi = omni.kit.viewport.get_viewport_interface
def set_translate(self, position):
"""
Set camera position.
Args:
position (tuple): camera position specified by (X, Y, Z)
"""
if not isinstance(position, tuple): position = tuple(position)
translate_attr = self.prim.GetAttribute("xformOp:translate")
translate_attr.Set(position)
def set_rotate(self, rotation):
"""
Set camera position.
Args:
rotation (tuple): camera orientation specified by three euler angles in degrees
"""
if not isinstance(rotation, tuple): rotation = tuple(rotation)
rotate_attr = self.prim.GetAttribute("xformOp:rotateZYX")
rotate_attr.Set(rotation)
def activate(self):
"""
Activate camera to viewport.
"""
self.vpi.get_viewport_window().set_active_camera(str(self.prim.GetPath()))
def __repr__(self):
return self.name
class RigidBody:
"""
RigidBody objects that contains state information of the rigid body.
"""
def __init__(self, prim, dc):
"""
Initializes for RigidBody object
Args:
prim (pxr.Usd.Prim): rigid body prim
dc (omni.isaac.motion_planning._motion_planning.MotionPlanning): motion planning interface from RMP extension
"""
self.prim = prim
self._dc = dc
self.name = prim.GetPrimPath().name
self.handle = self.get_rigid_body_handle()
def get_rigid_body_handle(self):
"""
Get rigid body handle.
"""
object_children = self.prim.GetChildren()
for child in object_children:
child_path = child.GetPath().pathString
body_handle = self._dc.get_rigid_body(child_path)
if body_handle != 0:
bin_path = child_path
object_handle = self._dc.get_rigid_body(bin_path)
if object_handle != 0: return object_handle
def get_linear_velocity(self):
"""
Get linear velocity of rigid body.
"""
return np.array(self._dc.get_rigid_body_linear_velocity(self.handle))
def get_angular_velocity(self):
"""
Get angular velocity of rigid body.
"""
return np.array(self._dc.get_rigid_body_angular_velocity(self.handle))
def get_speed(self):
"""
Get speed of rigid body given by the l2 norm of the velocity.
"""
velocity = self.get_linear_velocity()
speed = np.linalg.norm(velocity)
return speed
def get_pose(self):
"""
Get pose of the rigid body containing the position and orientation information.
"""
return self._dc.get_rigid_body_pose(self.handle)
def get_position(self):
"""
Get the position of the rigid body object.
"""
pose = self.get_pose()
position = np.array(pose.p)
return position
def get_orientation(self):
"""
Get orientation of the rigid body object.
"""
pose = self.get_pose()
orientation = np.array(pose.r)
return orientation
def get_bound(self):
"""
Get bounds of the rigid body object in global coordinates.
"""
bound = UsdGeom.Mesh(self.prim).ComputeWorldBound(0.0, "default").GetBox()
return [np.array(bound.GetMin()), np.array(bound.GetMax())]
def __repr__(self):
return self.name
|
erasromani/isaac-sim-python/grasp/utils/visualize.py | import os
import ffmpeg
import matplotlib.pyplot as plt
def screenshot(sd_helper, suffix="", prefix="image", directory="images/"):
"""
Take a screenshot of the current time step of a running NVIDIA Omniverse Isaac-Sim simulation.
Args:
sd_helper (omni.isaac.synthetic_utils.SyntheticDataHelper): helper class for visualizing OmniKit simulation
suffix (str or int): suffix for output filename of image screenshot of current time step of simulation
prefix (str): prefix for output filename of image screenshot of current time step of simulation
directory (str): output directory of image screenshot of current time step of simulation
"""
gt = sd_helper.get_groundtruth(
[
"rgb",
]
)
image = gt["rgb"][..., :3]
plt.imshow(image)
if suffix == "":
suffix = 0
if isinstance(suffix, int):
filename = os.path.join(directory, f'{prefix}_{suffix:05}.png')
else:
filename = os.path.join(directory, f'{prefix}_{suffix}.png')
plt.axis('off')
plt.savefig(filename)
def img2vid(input_pattern, output_fn, pattern_type='glob', framerate=25):
"""
Create video from a collection of images.
Args:
input_pattern (str): input pattern for a path of collection of images
output_fn (str): video output filename
pattern_type (str): pattern type for input pattern
framerate (int): video framerate
"""
(
ffmpeg
.input(input_pattern, pattern_type=pattern_type, framerate=framerate)
.output(output_fn)
.run(overwrite_output=True, quiet=True)
)
|
erasromani/isaac-sim-python/grasp/utils/__init__.py | |
pantelis-classes/omniverse-ai/README.md | # Learning in Simulated Worlds in Omniverse.
Please go to the wiki tab.
![image](https://user-images.githubusercontent.com/589439/143660504-bbcdb786-ea5f-4f74-9496-489032fa2e03.png)
https://github.com/pantelis-classes/omniverse-ai/wiki
<hr />
# Wiki Navigation
* [Home][home]
* [Isaac-Sim-SDK-Omniverse-Installation][Omniverse]
* [Synthetic-Data-Generation][SDG]
* [NVIDIA Transfer Learning Toolkit (TLT) Installation][TLT]
* [NVIDIA TAO][TAO]
* [detectnet_v2 Installation][detectnet_v2]
* [Jupyter Notebook][Jupyter-Notebook]
[home]: https://github.com/pantelis-classes/omniverse-ai/wiki
[Omniverse]: https://github.com/pantelis-classes/omniverse-ai/wiki/Isaac-Sim-SDK-Omniverse-Installation
[SDG]: https://github.com/pantelis-classes/omniverse-ai/wiki/Synthetic-Data-Generation-(Python-API)
[TLT]: https://github.com/pantelis-classes/omniverse-ai/wiki/NVIDIA-Transfer-Learning-Toolkit-(TLT)-Installation
[NTLTSD]: https://github.com/pantelis-classes/omniverse-ai/wiki/Using-NVIDIA-TLT-with-Synthetic-Data
[TAO]: https://github.com/pantelis-classes/omniverse-ai/wiki/TAO-(NVIDIA-Train,-Adapt,-and-Optimize)
[detectnet_v2]: https://github.com/pantelis-classes/omniverse-ai/wiki/detectnet_v2-Installation
[Jupyter-Notebook]: https://github.com/pantelis-classes/omniverse-ai/wiki/Jupyter-Notebook
<hr />
<a href="https://docs.google.com/document/d/1WAzdqlWE0RUns41-0P951mnsqMR7I2XV/edit?usp=sharing&ouid=112712585131518554614&rtpof=true&sd=true"> ![image](https://user-images.githubusercontent.com/589439/161171527-4e748031-ff4d-46ed-b1ac-b521cd8ffd3c.png)</a>
## Reports
<a href="https://docs.google.com/document/d/1jVXxrNgtOosZw_vAORzomSnmy45G3qK_mmk2B4oJtPg/edit?usp=sharing">Domain Randomization Paper</a><br>
This report provides an indepth understanding on how Domain Randomization helps perception machine learning tasks such as object detection and/or segmentation.
<a href="https://docs.google.com/document/d/1WAzdqlWE0RUns41-0P951mnsqMR7I2XV/edit?usp=sharing&ouid=112712585131518554614&rtpof=true&sd=true">Final Report</a><br>
This final report contains an indepth explanation on the hardware/software used, the methods used to collect the data, an explanation on the data collected, trained and pruned, and the overall conclusions made from the trained and pruned datasets.
<a href="https://docs.google.com/document/d/1WAzdqlWE0RUns41-0P951mnsqMR7I2XV/edit?usp=sharing&ouid=112712585131518554614&rtpof=true&sd=true">![image](https://user-images.githubusercontent.com/589439/161171433-d2359618-b3dc-4839-b509-c938ce401f73.png)</a>
## Authors
<a href="https://github.com/dfsanchez999">Diego Sanchez</a> | <a href="https://harp.njit.edu/~jga26/">Jibran Absarulislam</a> | <a href="https://github.com/markkcruz">Mark Cruz</a> | <a href="https://github.com/sppatel2112">Sapan Patel</a>
## Supervisor
<a href="https://pantelis.github.io/">Dr. Pantelis Monogioudis</a>
## Credits
<a href="https://developer.nvidia.com/nvidia-omniverse-platform">NVIDIA Omniverse</a><br>
A platform that enables universal interoperability across different applications and 3D ecosystem vendors providing real-time scene updates.
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pantelis-classes/omniverse-ai/Images/images.md | # A markdown file containing all the images in the wiki. (Saved in github's cloud)
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|
pantelis-classes/omniverse-ai/training_output/dataset1/train_1_summary.txt | Mean average_precision (in %): 4.2231
Mean average_precision (in %): 6.1684
Mean average_precision (in %): 8.5120
Mean average_precision (in %): 10.1440
Mean average_precision (in %): 12.0589
Mean average_precision (in %): 13.8389
Mean average_precision (in %): 13.8909
Mean average_precision (in %): 14.6698
Mean average_precision (in %): 15.8793
Mean average_precision (in %): 16.7417
Validation cost: 0.001164
Validation cost: 0.001069
Validation cost: 0.000885
Validation cost: 0.000975
Validation cost: 0.000967
Validation cost: 0.000840
Validation cost: 0.000776
Validation cost: 0.000779
Validation cost: 0.000783
Validation cost: 0.000682 |
pantelis-classes/omniverse-ai/training_output/dataset1/train_1.txt | 2021-11-27 16:31:00,082 [INFO] root: Registry: ['nvcr.io']
2021-11-27 16:31:00,127 [INFO] tlt.components.instance_handler.local_instance: Running command in container: nvcr.io/nvidia/tao/tao-toolkit-tf:v3.21.11-tf1.15.4-py3
Matplotlib created a temporary config/cache directory at /tmp/matplotlib-72jja2oo because the default path (/.config/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.
Using TensorFlow backend.
WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
Using TensorFlow backend.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:43: The name tf.train.SessionRunHook is deprecated. Please use tf.estimator.SessionRunHook instead.
2021-11-27 21:31:04,350 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:43: The name tf.train.SessionRunHook is deprecated. Please use tf.estimator.SessionRunHook instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/checkpoint_saver_hook.py:25: The name tf.train.CheckpointSaverHook is deprecated. Please use tf.estimator.CheckpointSaverHook instead.
2021-11-27 21:31:04,451 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/checkpoint_saver_hook.py:25: The name tf.train.CheckpointSaverHook is deprecated. Please use tf.estimator.CheckpointSaverHook instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:69: The name tf.logging.set_verbosity is deprecated. Please use tf.compat.v1.logging.set_verbosity instead.
2021-11-27 21:31:04,453 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:69: The name tf.logging.set_verbosity is deprecated. Please use tf.compat.v1.logging.set_verbosity instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:69: The name tf.logging.INFO is deprecated. Please use tf.compat.v1.logging.INFO instead.
2021-11-27 21:31:04,453 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:69: The name tf.logging.INFO is deprecated. Please use tf.compat.v1.logging.INFO instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:117: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.
2021-11-27 21:31:04,458 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:117: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:143: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.
2021-11-27 21:31:04,458 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:143: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.
2021-11-27 21:31:04,700 [INFO] __main__: Loading experiment spec at /workspace/tao-experiments/detectnet_v2/specs/detectnet_v2_train_resnet18_kitti.txt.
2021-11-27 21:31:04,701 [INFO] iva.detectnet_v2.spec_handler.spec_loader: Merging specification from /workspace/tao-experiments/detectnet_v2/specs/detectnet_v2_train_resnet18_kitti.txt
2021-11-27 21:31:04,793 [INFO] __main__: Cannot iterate over exactly 86 samples with a batch size of 4; each epoch will therefore take one extra step.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:107: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
2021-11-27 21:31:04,796 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:107: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:110: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.
2021-11-27 21:31:04,796 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:110: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:113: The name tf.assign is deprecated. Please use tf.compat.v1.assign instead.
2021-11-27 21:31:04,797 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:113: The name tf.assign is deprecated. Please use tf.compat.v1.assign instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
2021-11-27 21:31:04,932 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
2021-11-27 21:31:04,932 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1834: The name tf.nn.fused_batch_norm is deprecated. Please use tf.compat.v1.nn.fused_batch_norm instead.
2021-11-27 21:31:04,945 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1834: The name tf.nn.fused_batch_norm is deprecated. Please use tf.compat.v1.nn.fused_batch_norm instead.
WARNING:tensorflow:From /opt/nvidia/third_party/keras/tensorflow_backend.py:187: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.
2021-11-27 21:31:05,658 [WARNING] tensorflow: From /opt/nvidia/third_party/keras/tensorflow_backend.py:187: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:174: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.
2021-11-27 21:31:05,788 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:174: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:199: The name tf.is_variable_initialized is deprecated. Please use tf.compat.v1.is_variable_initialized instead.
2021-11-27 21:31:05,789 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:199: The name tf.is_variable_initialized is deprecated. Please use tf.compat.v1.is_variable_initialized instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:206: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.
2021-11-27 21:31:05,989 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:206: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.
2021-11-27 21:31:09,663 [INFO] iva.detectnet_v2.objectives.bbox_objective: Default L1 loss function will be used.
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) (None, 3, 384, 1248) 0
__________________________________________________________________________________________________
conv1 (Conv2D) (None, 64, 192, 624) 9472 input_1[0][0]
__________________________________________________________________________________________________
bn_conv1 (BatchNormalization) (None, 64, 192, 624) 256 conv1[0][0]
__________________________________________________________________________________________________
activation_1 (Activation) (None, 64, 192, 624) 0 bn_conv1[0][0]
__________________________________________________________________________________________________
block_1a_conv_1 (Conv2D) (None, 64, 96, 312) 36928 activation_1[0][0]
__________________________________________________________________________________________________
block_1a_bn_1 (BatchNormalizati (None, 64, 96, 312) 256 block_1a_conv_1[0][0]
__________________________________________________________________________________________________
block_1a_relu_1 (Activation) (None, 64, 96, 312) 0 block_1a_bn_1[0][0]
__________________________________________________________________________________________________
block_1a_conv_2 (Conv2D) (None, 64, 96, 312) 36928 block_1a_relu_1[0][0]
__________________________________________________________________________________________________
block_1a_conv_shortcut (Conv2D) (None, 64, 96, 312) 4160 activation_1[0][0]
__________________________________________________________________________________________________
block_1a_bn_2 (BatchNormalizati (None, 64, 96, 312) 256 block_1a_conv_2[0][0]
__________________________________________________________________________________________________
block_1a_bn_shortcut (BatchNorm (None, 64, 96, 312) 256 block_1a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, 64, 96, 312) 0 block_1a_bn_2[0][0]
block_1a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_1a_relu (Activation) (None, 64, 96, 312) 0 add_1[0][0]
__________________________________________________________________________________________________
block_1b_conv_1 (Conv2D) (None, 64, 96, 312) 36928 block_1a_relu[0][0]
__________________________________________________________________________________________________
block_1b_bn_1 (BatchNormalizati (None, 64, 96, 312) 256 block_1b_conv_1[0][0]
__________________________________________________________________________________________________
block_1b_relu_1 (Activation) (None, 64, 96, 312) 0 block_1b_bn_1[0][0]
__________________________________________________________________________________________________
block_1b_conv_2 (Conv2D) (None, 64, 96, 312) 36928 block_1b_relu_1[0][0]
__________________________________________________________________________________________________
block_1b_bn_2 (BatchNormalizati (None, 64, 96, 312) 256 block_1b_conv_2[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, 64, 96, 312) 0 block_1b_bn_2[0][0]
block_1a_relu[0][0]
__________________________________________________________________________________________________
block_1b_relu (Activation) (None, 64, 96, 312) 0 add_2[0][0]
__________________________________________________________________________________________________
block_2a_conv_1 (Conv2D) (None, 128, 48, 156) 73856 block_1b_relu[0][0]
__________________________________________________________________________________________________
block_2a_bn_1 (BatchNormalizati (None, 128, 48, 156) 512 block_2a_conv_1[0][0]
__________________________________________________________________________________________________
block_2a_relu_1 (Activation) (None, 128, 48, 156) 0 block_2a_bn_1[0][0]
__________________________________________________________________________________________________
block_2a_conv_2 (Conv2D) (None, 128, 48, 156) 147584 block_2a_relu_1[0][0]
__________________________________________________________________________________________________
block_2a_conv_shortcut (Conv2D) (None, 128, 48, 156) 8320 block_1b_relu[0][0]
__________________________________________________________________________________________________
block_2a_bn_2 (BatchNormalizati (None, 128, 48, 156) 512 block_2a_conv_2[0][0]
__________________________________________________________________________________________________
block_2a_bn_shortcut (BatchNorm (None, 128, 48, 156) 512 block_2a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_3 (Add) (None, 128, 48, 156) 0 block_2a_bn_2[0][0]
block_2a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_2a_relu (Activation) (None, 128, 48, 156) 0 add_3[0][0]
__________________________________________________________________________________________________
block_2b_conv_1 (Conv2D) (None, 128, 48, 156) 147584 block_2a_relu[0][0]
__________________________________________________________________________________________________
block_2b_bn_1 (BatchNormalizati (None, 128, 48, 156) 512 block_2b_conv_1[0][0]
__________________________________________________________________________________________________
block_2b_relu_1 (Activation) (None, 128, 48, 156) 0 block_2b_bn_1[0][0]
__________________________________________________________________________________________________
block_2b_conv_2 (Conv2D) (None, 128, 48, 156) 147584 block_2b_relu_1[0][0]
__________________________________________________________________________________________________
block_2b_bn_2 (BatchNormalizati (None, 128, 48, 156) 512 block_2b_conv_2[0][0]
__________________________________________________________________________________________________
add_4 (Add) (None, 128, 48, 156) 0 block_2b_bn_2[0][0]
block_2a_relu[0][0]
__________________________________________________________________________________________________
block_2b_relu (Activation) (None, 128, 48, 156) 0 add_4[0][0]
__________________________________________________________________________________________________
block_3a_conv_1 (Conv2D) (None, 256, 24, 78) 295168 block_2b_relu[0][0]
__________________________________________________________________________________________________
block_3a_bn_1 (BatchNormalizati (None, 256, 24, 78) 1024 block_3a_conv_1[0][0]
__________________________________________________________________________________________________
block_3a_relu_1 (Activation) (None, 256, 24, 78) 0 block_3a_bn_1[0][0]
__________________________________________________________________________________________________
block_3a_conv_2 (Conv2D) (None, 256, 24, 78) 590080 block_3a_relu_1[0][0]
__________________________________________________________________________________________________
block_3a_conv_shortcut (Conv2D) (None, 256, 24, 78) 33024 block_2b_relu[0][0]
__________________________________________________________________________________________________
block_3a_bn_2 (BatchNormalizati (None, 256, 24, 78) 1024 block_3a_conv_2[0][0]
__________________________________________________________________________________________________
block_3a_bn_shortcut (BatchNorm (None, 256, 24, 78) 1024 block_3a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_5 (Add) (None, 256, 24, 78) 0 block_3a_bn_2[0][0]
block_3a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_3a_relu (Activation) (None, 256, 24, 78) 0 add_5[0][0]
__________________________________________________________________________________________________
block_3b_conv_1 (Conv2D) (None, 256, 24, 78) 590080 block_3a_relu[0][0]
__________________________________________________________________________________________________
block_3b_bn_1 (BatchNormalizati (None, 256, 24, 78) 1024 block_3b_conv_1[0][0]
__________________________________________________________________________________________________
block_3b_relu_1 (Activation) (None, 256, 24, 78) 0 block_3b_bn_1[0][0]
__________________________________________________________________________________________________
block_3b_conv_2 (Conv2D) (None, 256, 24, 78) 590080 block_3b_relu_1[0][0]
__________________________________________________________________________________________________
block_3b_bn_2 (BatchNormalizati (None, 256, 24, 78) 1024 block_3b_conv_2[0][0]
__________________________________________________________________________________________________
add_6 (Add) (None, 256, 24, 78) 0 block_3b_bn_2[0][0]
block_3a_relu[0][0]
__________________________________________________________________________________________________
block_3b_relu (Activation) (None, 256, 24, 78) 0 add_6[0][0]
__________________________________________________________________________________________________
block_4a_conv_1 (Conv2D) (None, 512, 24, 78) 1180160 block_3b_relu[0][0]
__________________________________________________________________________________________________
block_4a_bn_1 (BatchNormalizati (None, 512, 24, 78) 2048 block_4a_conv_1[0][0]
__________________________________________________________________________________________________
block_4a_relu_1 (Activation) (None, 512, 24, 78) 0 block_4a_bn_1[0][0]
__________________________________________________________________________________________________
block_4a_conv_2 (Conv2D) (None, 512, 24, 78) 2359808 block_4a_relu_1[0][0]
__________________________________________________________________________________________________
block_4a_conv_shortcut (Conv2D) (None, 512, 24, 78) 131584 block_3b_relu[0][0]
__________________________________________________________________________________________________
block_4a_bn_2 (BatchNormalizati (None, 512, 24, 78) 2048 block_4a_conv_2[0][0]
__________________________________________________________________________________________________
block_4a_bn_shortcut (BatchNorm (None, 512, 24, 78) 2048 block_4a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_7 (Add) (None, 512, 24, 78) 0 block_4a_bn_2[0][0]
block_4a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_4a_relu (Activation) (None, 512, 24, 78) 0 add_7[0][0]
__________________________________________________________________________________________________
block_4b_conv_1 (Conv2D) (None, 512, 24, 78) 2359808 block_4a_relu[0][0]
__________________________________________________________________________________________________
block_4b_bn_1 (BatchNormalizati (None, 512, 24, 78) 2048 block_4b_conv_1[0][0]
__________________________________________________________________________________________________
block_4b_relu_1 (Activation) (None, 512, 24, 78) 0 block_4b_bn_1[0][0]
__________________________________________________________________________________________________
block_4b_conv_2 (Conv2D) (None, 512, 24, 78) 2359808 block_4b_relu_1[0][0]
__________________________________________________________________________________________________
block_4b_bn_2 (BatchNormalizati (None, 512, 24, 78) 2048 block_4b_conv_2[0][0]
__________________________________________________________________________________________________
add_8 (Add) (None, 512, 24, 78) 0 block_4b_bn_2[0][0]
block_4a_relu[0][0]
__________________________________________________________________________________________________
block_4b_relu (Activation) (None, 512, 24, 78) 0 add_8[0][0]
__________________________________________________________________________________________________
output_bbox (Conv2D) (None, 36, 24, 78) 18468 block_4b_relu[0][0]
__________________________________________________________________________________________________
output_cov (Conv2D) (None, 9, 24, 78) 4617 block_4b_relu[0][0]
==================================================================================================
Total params: 11,218,413
Trainable params: 11,208,685
Non-trainable params: 9,728
__________________________________________________________________________________________________
2021-11-27 21:31:09,687 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Serial augmentation enabled = False
2021-11-27 21:31:09,687 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Pseudo sharding enabled = False
2021-11-27 21:31:09,687 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Max Image Dimensions (all sources): (0, 0)
2021-11-27 21:31:09,687 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: number of cpus: 16, io threads: 32, compute threads: 16, buffered batches: 4
2021-11-27 21:31:09,687 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: total dataset size 86, number of sources: 1, batch size per gpu: 4, steps: 22
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/autograph/converters/directives.py:119: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
2021-11-27 21:31:09,715 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/autograph/converters/directives.py:119: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
WARNING:tensorflow:Entity <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7fb0548cc7b8>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7fb0548cc7b8>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 21:31:09,747 [WARNING] tensorflow: Entity <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7fb0548cc7b8>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7fb0548cc7b8>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 21:31:09,759 [INFO] iva.detectnet_v2.dataloader.default_dataloader: Bounding box coordinates were detected in the input specification! Bboxes will be automatically converted to polygon coordinates.
2021-11-27 21:31:09,925 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: shuffle: True - shard 0 of 1
2021-11-27 21:31:09,928 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: sampling 1 datasets with weights:
2021-11-27 21:31:09,928 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: source: 0 weight: 1.000000
WARNING:tensorflow:Entity <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7fb08e894a58>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7fb08e894a58>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 21:31:09,938 [WARNING] tensorflow: Entity <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7fb08e894a58>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7fb08e894a58>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 21:31:10,177 [INFO] __main__: Found 86 samples in training set
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/rasterizers/bbox_rasterizer.py:347: The name tf.bincount is deprecated. Please use tf.math.bincount instead.
2021-11-27 21:31:10,244 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/rasterizers/bbox_rasterizer.py:347: The name tf.bincount is deprecated. Please use tf.math.bincount instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/training_proto_utilities.py:89: The name tf.train.get_or_create_global_step is deprecated. Please use tf.compat.v1.train.get_or_create_global_step instead.
2021-11-27 21:31:10,357 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/training_proto_utilities.py:89: The name tf.train.get_or_create_global_step is deprecated. Please use tf.compat.v1.train.get_or_create_global_step instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/training_proto_utilities.py:36: The name tf.train.AdamOptimizer is deprecated. Please use tf.compat.v1.train.AdamOptimizer instead.
2021-11-27 21:31:10,367 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/training_proto_utilities.py:36: The name tf.train.AdamOptimizer is deprecated. Please use tf.compat.v1.train.AdamOptimizer instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_functions.py:17: The name tf.log is deprecated. Please use tf.math.log instead.
2021-11-27 21:31:10,482 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_functions.py:17: The name tf.log is deprecated. Please use tf.math.log instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:235: The name tf.assign_add is deprecated. Please use tf.compat.v1.assign_add instead.
2021-11-27 21:31:10,574 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:235: The name tf.assign_add is deprecated. Please use tf.compat.v1.assign_add instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/model/detectnet_model.py:591: The name tf.summary.scalar is deprecated. Please use tf.compat.v1.summary.scalar instead.
2021-11-27 21:31:10,591 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/model/detectnet_model.py:591: The name tf.summary.scalar is deprecated. Please use tf.compat.v1.summary.scalar instead.
2021-11-27 21:31:11,937 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Serial augmentation enabled = False
2021-11-27 21:31:11,937 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Pseudo sharding enabled = False
2021-11-27 21:31:11,937 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Max Image Dimensions (all sources): (0, 0)
2021-11-27 21:31:11,938 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: number of cpus: 16, io threads: 32, compute threads: 16, buffered batches: 4
2021-11-27 21:31:11,938 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: total dataset size 14, number of sources: 1, batch size per gpu: 4, steps: 4
WARNING:tensorflow:Entity <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7fb0548cc780>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7fb0548cc780>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 21:31:11,944 [WARNING] tensorflow: Entity <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7fb0548cc780>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7fb0548cc780>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 21:31:11,956 [INFO] iva.detectnet_v2.dataloader.default_dataloader: Bounding box coordinates were detected in the input specification! Bboxes will be automatically converted to polygon coordinates.
2021-11-27 21:31:12,109 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: shuffle: False - shard 0 of 1
2021-11-27 21:31:12,112 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: sampling 1 datasets with weights:
2021-11-27 21:31:12,112 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: source: 0 weight: 1.000000
WARNING:tensorflow:Entity <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7fb0101b1ac8>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7fb0101b1ac8>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 21:31:12,121 [WARNING] tensorflow: Entity <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7fb0101b1ac8>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7fb0101b1ac8>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 21:31:12,271 [INFO] __main__: Found 14 samples in validation set
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/validation_hook.py:40: The name tf.summary.FileWriterCache is deprecated. Please use tf.compat.v1.summary.FileWriterCache instead.
2021-11-27 21:31:12,762 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/validation_hook.py:40: The name tf.summary.FileWriterCache is deprecated. Please use tf.compat.v1.summary.FileWriterCache instead.
2021-11-27 21:31:13,616 [INFO] __main__: Checkpoint interval: 10
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:109: The name tf.train.Scaffold is deprecated. Please use tf.compat.v1.train.Scaffold instead.
2021-11-27 21:31:13,616 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:109: The name tf.train.Scaffold is deprecated. Please use tf.compat.v1.train.Scaffold instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:14: The name tf.local_variables_initializer is deprecated. Please use tf.compat.v1.local_variables_initializer instead.
2021-11-27 21:31:13,616 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:14: The name tf.local_variables_initializer is deprecated. Please use tf.compat.v1.local_variables_initializer instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:15: The name tf.tables_initializer is deprecated. Please use tf.compat.v1.tables_initializer instead.
2021-11-27 21:31:13,616 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:15: The name tf.tables_initializer is deprecated. Please use tf.compat.v1.tables_initializer instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:16: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
2021-11-27 21:31:13,617 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:16: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:59: The name tf.train.LoggingTensorHook is deprecated. Please use tf.estimator.LoggingTensorHook instead.
2021-11-27 21:31:13,618 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:59: The name tf.train.LoggingTensorHook is deprecated. Please use tf.estimator.LoggingTensorHook instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:60: The name tf.train.StopAtStepHook is deprecated. Please use tf.estimator.StopAtStepHook instead.
2021-11-27 21:31:13,618 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:60: The name tf.train.StopAtStepHook is deprecated. Please use tf.estimator.StopAtStepHook instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:73: The name tf.train.StepCounterHook is deprecated. Please use tf.estimator.StepCounterHook instead.
2021-11-27 21:31:13,618 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:73: The name tf.train.StepCounterHook is deprecated. Please use tf.estimator.StepCounterHook instead.
INFO:tensorflow:Create CheckpointSaverHook.
2021-11-27 21:31:13,618 [INFO] tensorflow: Create CheckpointSaverHook.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:99: The name tf.train.SummarySaverHook is deprecated. Please use tf.estimator.SummarySaverHook instead.
2021-11-27 21:31:13,618 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:99: The name tf.train.SummarySaverHook is deprecated. Please use tf.estimator.SummarySaverHook instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/utilities.py:140: The name tf.train.SingularMonitoredSession is deprecated. Please use tf.compat.v1.train.SingularMonitoredSession instead.
2021-11-27 21:31:13,619 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/utilities.py:140: The name tf.train.SingularMonitoredSession is deprecated. Please use tf.compat.v1.train.SingularMonitoredSession instead.
INFO:tensorflow:Graph was finalized.
2021-11-27 21:31:14,169 [INFO] tensorflow: Graph was finalized.
INFO:tensorflow:Running local_init_op.
2021-11-27 21:31:15,298 [INFO] tensorflow: Running local_init_op.
INFO:tensorflow:Done running local_init_op.
2021-11-27 21:31:15,678 [INFO] tensorflow: Done running local_init_op.
INFO:tensorflow:Saving checkpoints for step-0.
2021-11-27 21:31:20,052 [INFO] tensorflow: Saving checkpoints for step-0.
INFO:tensorflow:epoch = 0.0, learning_rate = 4.9999994e-06, loss = 0.083847225, step = 0
2021-11-27 21:31:33,730 [INFO] tensorflow: epoch = 0.0, learning_rate = 4.9999994e-06, loss = 0.083847225, step = 0
2021-11-27 21:31:33,731 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 0/120: loss: 0.08385 learning rate: 0.00000 Time taken: 0:00:00 ETA: 0:00:00
2021-11-27 21:31:33,731 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 0.964
INFO:tensorflow:global_step/sec: 1.4339
2021-11-27 21:31:35,125 [INFO] tensorflow: global_step/sec: 1.4339
INFO:tensorflow:global_step/sec: 15.1283
2021-11-27 21:31:35,258 [INFO] tensorflow: global_step/sec: 15.1283
INFO:tensorflow:global_step/sec: 14.7831
2021-11-27 21:31:35,393 [INFO] tensorflow: global_step/sec: 14.7831
INFO:tensorflow:global_step/sec: 14.4561
2021-11-27 21:31:35,531 [INFO] tensorflow: global_step/sec: 14.4561
INFO:tensorflow:global_step/sec: 14.9825
2021-11-27 21:31:35,665 [INFO] tensorflow: global_step/sec: 14.9825
INFO:tensorflow:global_step/sec: 14.6884
2021-11-27 21:31:35,801 [INFO] tensorflow: global_step/sec: 14.6884
INFO:tensorflow:global_step/sec: 14.3131
2021-11-27 21:31:35,941 [INFO] tensorflow: global_step/sec: 14.3131
INFO:tensorflow:global_step/sec: 14.5834
2021-11-27 21:31:36,078 [INFO] tensorflow: global_step/sec: 14.5834
INFO:tensorflow:global_step/sec: 14.6913
2021-11-27 21:31:36,214 [INFO] tensorflow: global_step/sec: 14.6913
INFO:tensorflow:global_step/sec: 14.085
2021-11-27 21:31:36,356 [INFO] tensorflow: global_step/sec: 14.085
5df7bf374f13:58:92 [0] NCCL INFO Bootstrap : Using lo:127.0.0.1<0>
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INFO:tensorflow:global_step/sec: 5.08956
2021-11-27 21:31:36,749 [INFO] tensorflow: global_step/sec: 5.08956
2021-11-27 21:31:36,750 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 1/120: loss: 0.27070 learning rate: 0.00001 Time taken: 0:00:07.095566 ETA: 0:14:04.372386
INFO:tensorflow:global_step/sec: 15.2007
2021-11-27 21:31:36,880 [INFO] tensorflow: global_step/sec: 15.2007
2021-11-27 21:31:36,881 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 13.697
INFO:tensorflow:global_step/sec: 15.2471
2021-11-27 21:31:37,012 [INFO] tensorflow: global_step/sec: 15.2471
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INFO:tensorflow:global_step/sec: 13.7074
2021-11-27 21:31:38,254 [INFO] tensorflow: global_step/sec: 13.7074
2021-11-27 21:31:38,255 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 2/120: loss: 0.16879 learning rate: 0.00001 Time taken: 0:00:01.506391 ETA: 0:02:57.754172
INFO:tensorflow:global_step/sec: 14.5663
2021-11-27 21:31:38,391 [INFO] tensorflow: global_step/sec: 14.5663
INFO:tensorflow:global_step/sec: 14.6227
2021-11-27 21:31:38,528 [INFO] tensorflow: global_step/sec: 14.6227
2021-11-27 21:31:38,597 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.277
INFO:tensorflow:global_step/sec: 14.7751
2021-11-27 21:31:38,663 [INFO] tensorflow: global_step/sec: 14.7751
INFO:tensorflow:epoch = 2.3636363636363638, learning_rate = 1.2385377e-05, loss = 0.12353368, step = 52 (5.073 sec)
2021-11-27 21:31:38,803 [INFO] tensorflow: epoch = 2.3636363636363638, learning_rate = 1.2385377e-05, loss = 0.12353368, step = 52 (5.073 sec)
INFO:tensorflow:global_step/sec: 14.259
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2021-11-27 21:31:39,756 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 3/120: loss: 0.07809 learning rate: 0.00002 Time taken: 0:00:01.501290 ETA: 0:02:55.650968
INFO:tensorflow:global_step/sec: 14.9706
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2021-11-27 21:31:40,295 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.905
INFO:tensorflow:global_step/sec: 14.8274
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INFO:tensorflow:global_step/sec: 13.7134
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2021-11-27 21:31:41,248 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 4/120: loss: 0.03462 learning rate: 0.00002 Time taken: 0:00:01.490692 ETA: 0:02:52.920288
INFO:tensorflow:global_step/sec: 14.6668
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2021-11-27 21:31:41,997 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.762
INFO:tensorflow:global_step/sec: 14.439
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2021-11-27 21:31:42,782 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 5/120: loss: 0.02198 learning rate: 0.00003 Time taken: 0:00:01.527407 ETA: 0:02:55.651770
INFO:tensorflow:global_step/sec: 14.2794
2021-11-27 21:31:42,922 [INFO] tensorflow: global_step/sec: 14.2794
INFO:tensorflow:global_step/sec: 15.0424
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2021-11-27 21:31:43,714 [INFO] tensorflow: global_step/sec: 14.9112
2021-11-27 21:31:43,715 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.224
INFO:tensorflow:global_step/sec: 15.0502
2021-11-27 21:31:43,847 [INFO] tensorflow: global_step/sec: 15.0502
INFO:tensorflow:epoch = 5.7727272727272725, learning_rate = 4.582378e-05, loss = 0.013955122, step = 127 (5.110 sec)
2021-11-27 21:31:43,913 [INFO] tensorflow: epoch = 5.7727272727272725, learning_rate = 4.582378e-05, loss = 0.013955122, step = 127 (5.110 sec)
INFO:tensorflow:global_step/sec: 15.4896
2021-11-27 21:31:43,976 [INFO] tensorflow: global_step/sec: 15.4896
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2021-11-27 21:31:44,242 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 6/120: loss: 0.01475 learning rate: 0.00005 Time taken: 0:00:01.465466 ETA: 0:02:47.063181
INFO:tensorflow:global_step/sec: 15.3628
2021-11-27 21:31:44,372 [INFO] tensorflow: global_step/sec: 15.3628
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INFO:tensorflow:global_step/sec: 12.65
2021-11-27 21:31:45,327 [INFO] tensorflow: global_step/sec: 12.65
2021-11-27 21:31:45,394 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.584
INFO:tensorflow:global_step/sec: 14.7737
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2021-11-27 21:31:45,737 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 7/120: loss: 0.00729 learning rate: 0.00007 Time taken: 0:00:01.495057 ETA: 0:02:48.941399
INFO:tensorflow:global_step/sec: 15.3858
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2021-11-27 21:31:47,054 [INFO] tensorflow: global_step/sec: 15.4033
2021-11-27 21:31:47,055 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.215
INFO:tensorflow:global_step/sec: 13.9334
2021-11-27 21:31:47,197 [INFO] tensorflow: global_step/sec: 13.9334
2021-11-27 21:31:47,198 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 8/120: loss: 0.00513 learning rate: 0.00011 Time taken: 0:00:01.454498 ETA: 0:02:42.903755
INFO:tensorflow:global_step/sec: 14.699
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2021-11-27 21:31:48,726 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 9/120: loss: 0.00476 learning rate: 0.00016 Time taken: 0:00:01.529690 ETA: 0:02:49.795540
2021-11-27 21:31:48,793 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.549
INFO:tensorflow:global_step/sec: 14.7406
2021-11-27 21:31:48,861 [INFO] tensorflow: global_step/sec: 14.7406
INFO:tensorflow:epoch = 9.181818181818182, learning_rate = 0.00016954016, loss = 0.0040661036, step = 202 (5.087 sec)
2021-11-27 21:31:49,000 [INFO] tensorflow: epoch = 9.181818181818182, learning_rate = 0.00016954016, loss = 0.0040661036, step = 202 (5.087 sec)
INFO:tensorflow:global_step/sec: 14.3046
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INFO:tensorflow:global_step/sec: 13.9338
2021-11-27 21:31:50,128 [INFO] tensorflow: global_step/sec: 13.9338
INFO:tensorflow:Saving checkpoints for step-220.
2021-11-27 21:31:50,199 [INFO] tensorflow: Saving checkpoints for step-220.
INFO:tensorflow:global_step/sec: 0.796942
2021-11-27 21:31:52,637 [INFO] tensorflow: global_step/sec: 0.796942
2021-11-27 21:31:52,638 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 10/120: loss: 0.00352 learning rate: 0.00023 Time taken: 0:00:03.906896 ETA: 0:07:09.758573
INFO:tensorflow:global_step/sec: 14.776
2021-11-27 21:31:52,773 [INFO] tensorflow: global_step/sec: 14.776
INFO:tensorflow:global_step/sec: 15.0587
2021-11-27 21:31:52,905 [INFO] tensorflow: global_step/sec: 15.0587
2021-11-27 21:31:52,906 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 24.312
INFO:tensorflow:global_step/sec: 15.0996
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INFO:tensorflow:epoch = 11.0, learning_rate = 0.000340646, loss = 0.0036697325, step = 242 (5.108 sec)
2021-11-27 21:31:54,107 [INFO] tensorflow: epoch = 11.0, learning_rate = 0.000340646, loss = 0.0036697325, step = 242 (5.108 sec)
INFO:tensorflow:global_step/sec: 13.4528
2021-11-27 21:31:54,108 [INFO] tensorflow: global_step/sec: 13.4528
2021-11-27 21:31:54,109 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 11/120: loss: 0.00367 learning rate: 0.00034 Time taken: 0:00:01.469206 ETA: 0:02:40.143464
INFO:tensorflow:global_step/sec: 15.0168
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2021-11-27 21:31:54,572 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.049
INFO:tensorflow:global_step/sec: 14.6749
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2021-11-27 21:31:55,570 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 12/120: loss: 0.00225 learning rate: 0.00050 Time taken: 0:00:01.463416 ETA: 0:02:38.048887
INFO:tensorflow:global_step/sec: 14.946
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2021-11-27 21:31:56,238 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.032
INFO:tensorflow:global_step/sec: 14.5762
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2021-11-27 21:31:57,076 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 13/120: loss: 0.00187 learning rate: 0.00050 Time taken: 0:00:01.501979 ETA: 0:02:40.711714
INFO:tensorflow:global_step/sec: 15.014
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2021-11-27 21:31:57,966 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.864
INFO:tensorflow:global_step/sec: 14.0557
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INFO:tensorflow:global_step/sec: 15.359
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2021-11-27 21:31:58,590 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 14/120: loss: 0.00258 learning rate: 0.00050 Time taken: 0:00:01.511611 ETA: 0:02:40.230815
INFO:tensorflow:global_step/sec: 15.0277
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2021-11-27 21:31:59,134 [INFO] tensorflow: global_step/sec: 14.8048
INFO:tensorflow:epoch = 14.40909090909091, learning_rate = 0.00049999997, loss = 0.0022279387, step = 317 (5.099 sec)
2021-11-27 21:31:59,206 [INFO] tensorflow: epoch = 14.40909090909091, learning_rate = 0.00049999997, loss = 0.0022279387, step = 317 (5.099 sec)
INFO:tensorflow:global_step/sec: 13.9091
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2021-11-27 21:31:59,702 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.626
INFO:tensorflow:global_step/sec: 14.6233
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2021-11-27 21:32:00,125 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 15/120: loss: 0.00160 learning rate: 0.00050 Time taken: 0:00:01.529787 ETA: 0:02:40.627667
INFO:tensorflow:global_step/sec: 14.8995
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2021-11-27 21:32:01,444 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.423
INFO:tensorflow:global_step/sec: 14.4972
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2021-11-27 21:32:01,657 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 16/120: loss: 0.00166 learning rate: 0.00050 Time taken: 0:00:01.534032 ETA: 0:02:39.539289
INFO:tensorflow:global_step/sec: 14.623
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2021-11-27 21:32:03,172 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 17/120: loss: 0.00210 learning rate: 0.00050 Time taken: 0:00:01.513803 ETA: 0:02:35.921710
2021-11-27 21:32:03,172 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.879
INFO:tensorflow:global_step/sec: 15.2497
2021-11-27 21:32:03,302 [INFO] tensorflow: global_step/sec: 15.2497
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2021-11-27 21:32:04,266 [INFO] tensorflow: global_step/sec: 14.4214
INFO:tensorflow:epoch = 17.772727272727273, learning_rate = 0.00049999997, loss = 0.00184356, step = 391 (5.129 sec)
2021-11-27 21:32:04,336 [INFO] tensorflow: epoch = 17.772727272727273, learning_rate = 0.00049999997, loss = 0.00184356, step = 391 (5.129 sec)
INFO:tensorflow:global_step/sec: 14.5394
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2021-11-27 21:32:04,675 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 18/120: loss: 0.00177 learning rate: 0.00050 Time taken: 0:00:01.499717 ETA: 0:02:32.971085
INFO:tensorflow:global_step/sec: 14.3802
2021-11-27 21:32:04,813 [INFO] tensorflow: global_step/sec: 14.3802
2021-11-27 21:32:04,879 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.591
INFO:tensorflow:global_step/sec: 14.8187
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INFO:tensorflow:global_step/sec: 13.5439
2021-11-27 21:32:06,204 [INFO] tensorflow: global_step/sec: 13.5439
2021-11-27 21:32:06,205 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 19/120: loss: 0.00155 learning rate: 0.00050 Time taken: 0:00:01.529584 ETA: 0:02:34.488001
INFO:tensorflow:global_step/sec: 14.3055
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2021-11-27 21:32:06,611 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.729
INFO:tensorflow:global_step/sec: 14.9099
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2021-11-27 21:32:07,576 [INFO] tensorflow: global_step/sec: 14.1223
INFO:tensorflow:Saving checkpoints for step-440.
2021-11-27 21:32:07,645 [INFO] tensorflow: Saving checkpoints for step-440.
INFO:tensorflow:epoch = 20.0, learning_rate = 0.00049999997, loss = 0.0016232943, step = 440 (5.737 sec)
2021-11-27 21:32:10,073 [INFO] tensorflow: epoch = 20.0, learning_rate = 0.00049999997, loss = 0.0016232943, step = 440 (5.737 sec)
INFO:tensorflow:global_step/sec: 0.800898
2021-11-27 21:32:10,073 [INFO] tensorflow: global_step/sec: 0.800898
2021-11-27 21:32:10,074 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 20/120: loss: 0.00162 learning rate: 0.00050 Time taken: 0:00:03.864767 ETA: 0:06:26.476707
INFO:tensorflow:global_step/sec: 13.666
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2021-11-27 21:32:10,694 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 24.493
INFO:tensorflow:global_step/sec: 14.5623
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INFO:tensorflow:global_step/sec: 13.7548
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2021-11-27 21:32:11,597 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 21/120: loss: 0.00229 learning rate: 0.00050 Time taken: 0:00:01.522311 ETA: 0:02:30.708833
INFO:tensorflow:global_step/sec: 14.492
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2021-11-27 21:32:12,433 [INFO] tensorflow: global_step/sec: 14.4087
2021-11-27 21:32:12,434 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.502
INFO:tensorflow:global_step/sec: 14.5344
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2021-11-27 21:32:13,122 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 22/120: loss: 0.00173 learning rate: 0.00050 Time taken: 0:00:01.525494 ETA: 0:02:29.498375
INFO:tensorflow:global_step/sec: 14.3331
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2021-11-27 21:32:14,170 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.592
INFO:tensorflow:global_step/sec: 14.3793
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2021-11-27 21:32:14,667 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 23/120: loss: 0.00144 learning rate: 0.00050 Time taken: 0:00:01.541562 ETA: 0:02:29.531499
INFO:tensorflow:global_step/sec: 13.9933
2021-11-27 21:32:14,809 [INFO] tensorflow: global_step/sec: 13.9933
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INFO:tensorflow:epoch = 23.31818181818182, learning_rate = 0.00049999997, loss = 0.0017488953, step = 513 (5.090 sec)
2021-11-27 21:32:15,163 [INFO] tensorflow: epoch = 23.31818181818182, learning_rate = 0.00049999997, loss = 0.0017488953, step = 513 (5.090 sec)
INFO:tensorflow:global_step/sec: 14.6985
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2021-11-27 21:32:15,913 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.385
INFO:tensorflow:global_step/sec: 14.202
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INFO:tensorflow:global_step/sec: 12.8793
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2021-11-27 21:32:16,209 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 24/120: loss: 0.00166 learning rate: 0.00050 Time taken: 0:00:01.541709 ETA: 0:02:28.004082
INFO:tensorflow:global_step/sec: 14.3241
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2021-11-27 21:32:17,663 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.162
INFO:tensorflow:global_step/sec: 13.1499
2021-11-27 21:32:17,733 [INFO] tensorflow: global_step/sec: 13.1499
2021-11-27 21:32:17,734 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 25/120: loss: 0.00148 learning rate: 0.00050 Time taken: 0:00:01.523090 ETA: 0:02:24.693562
INFO:tensorflow:global_step/sec: 14.4335
2021-11-27 21:32:17,871 [INFO] tensorflow: global_step/sec: 14.4335
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2021-11-27 21:32:18,140 [INFO] tensorflow: global_step/sec: 14.7769
INFO:tensorflow:global_step/sec: 14.1323
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INFO:tensorflow:global_step/sec: 14.9708
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INFO:tensorflow:global_step/sec: 14.3743
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INFO:tensorflow:global_step/sec: 14.4519
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INFO:tensorflow:global_step/sec: 14.5481
2021-11-27 21:32:19,106 [INFO] tensorflow: global_step/sec: 14.5481
INFO:tensorflow:global_step/sec: 13.6372
2021-11-27 21:32:19,253 [INFO] tensorflow: global_step/sec: 13.6372
2021-11-27 21:32:19,253 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 26/120: loss: 0.00157 learning rate: 0.00050 Time taken: 0:00:01.516972 ETA: 0:02:22.595352
INFO:tensorflow:global_step/sec: 14.6464
2021-11-27 21:32:19,389 [INFO] tensorflow: global_step/sec: 14.6464
2021-11-27 21:32:19,390 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.953
INFO:tensorflow:global_step/sec: 14.2493
2021-11-27 21:32:19,530 [INFO] tensorflow: global_step/sec: 14.2493
INFO:tensorflow:global_step/sec: 14.8253
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INFO:tensorflow:global_step/sec: 14.0242
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INFO:tensorflow:global_step/sec: 14.6664
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INFO:tensorflow:global_step/sec: 14.3821
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INFO:tensorflow:global_step/sec: 14.4664
2021-11-27 21:32:20,221 [INFO] tensorflow: global_step/sec: 14.4664
INFO:tensorflow:epoch = 26.681818181818183, learning_rate = 0.00049999997, loss = 0.0014593615, step = 587 (5.125 sec)
2021-11-27 21:32:20,288 [INFO] tensorflow: epoch = 26.681818181818183, learning_rate = 0.00049999997, loss = 0.0014593615, step = 587 (5.125 sec)
INFO:tensorflow:global_step/sec: 14.8458
2021-11-27 21:32:20,356 [INFO] tensorflow: global_step/sec: 14.8458
INFO:tensorflow:global_step/sec: 14.5087
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INFO:tensorflow:global_step/sec: 13.9724
2021-11-27 21:32:20,775 [INFO] tensorflow: global_step/sec: 13.9724
2021-11-27 21:32:20,776 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 27/120: loss: 0.00143 learning rate: 0.00050 Time taken: 0:00:01.524051 ETA: 0:02:21.736716
INFO:tensorflow:global_step/sec: 14.4074
2021-11-27 21:32:20,914 [INFO] tensorflow: global_step/sec: 14.4074
INFO:tensorflow:global_step/sec: 14.6238
2021-11-27 21:32:21,050 [INFO] tensorflow: global_step/sec: 14.6238
2021-11-27 21:32:21,116 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.933
INFO:tensorflow:global_step/sec: 14.7618
2021-11-27 21:32:21,186 [INFO] tensorflow: global_step/sec: 14.7618
INFO:tensorflow:global_step/sec: 14.0194
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INFO:tensorflow:global_step/sec: 14.3016
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INFO:tensorflow:global_step/sec: 14.8373
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INFO:tensorflow:global_step/sec: 14.8671
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INFO:tensorflow:global_step/sec: 13.9839
2021-11-27 21:32:21,881 [INFO] tensorflow: global_step/sec: 13.9839
INFO:tensorflow:global_step/sec: 14.1962
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INFO:tensorflow:global_step/sec: 14.8889
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INFO:tensorflow:global_step/sec: 13.3134
2021-11-27 21:32:22,306 [INFO] tensorflow: global_step/sec: 13.3134
2021-11-27 21:32:22,307 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 28/120: loss: 0.00134 learning rate: 0.00050 Time taken: 0:00:01.526674 ETA: 0:02:20.454011
INFO:tensorflow:global_step/sec: 14.4676
2021-11-27 21:32:22,444 [INFO] tensorflow: global_step/sec: 14.4676
INFO:tensorflow:global_step/sec: 14.7996
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INFO:tensorflow:global_step/sec: 15.207
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INFO:tensorflow:global_step/sec: 14.943
2021-11-27 21:32:22,845 [INFO] tensorflow: global_step/sec: 14.943
2021-11-27 21:32:22,845 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.845
INFO:tensorflow:global_step/sec: 14.829
2021-11-27 21:32:22,980 [INFO] tensorflow: global_step/sec: 14.829
INFO:tensorflow:global_step/sec: 15.0299
2021-11-27 21:32:23,113 [INFO] tensorflow: global_step/sec: 15.0299
INFO:tensorflow:global_step/sec: 14.1244
2021-11-27 21:32:23,254 [INFO] tensorflow: global_step/sec: 14.1244
INFO:tensorflow:global_step/sec: 14.6959
2021-11-27 21:32:23,390 [INFO] tensorflow: global_step/sec: 14.6959
INFO:tensorflow:global_step/sec: 14.0629
2021-11-27 21:32:23,533 [INFO] tensorflow: global_step/sec: 14.0629
INFO:tensorflow:global_step/sec: 13.7648
2021-11-27 21:32:23,678 [INFO] tensorflow: global_step/sec: 13.7648
INFO:tensorflow:global_step/sec: 13.2653
2021-11-27 21:32:23,829 [INFO] tensorflow: global_step/sec: 13.2653
2021-11-27 21:32:23,829 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 29/120: loss: 0.00164 learning rate: 0.00050 Time taken: 0:00:01.520847 ETA: 0:02:18.397041
INFO:tensorflow:global_step/sec: 15.3221
2021-11-27 21:32:23,959 [INFO] tensorflow: global_step/sec: 15.3221
INFO:tensorflow:global_step/sec: 14.2741
2021-11-27 21:32:24,099 [INFO] tensorflow: global_step/sec: 14.2741
INFO:tensorflow:global_step/sec: 14.2907
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INFO:tensorflow:global_step/sec: 14.322
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INFO:tensorflow:global_step/sec: 14.2586
2021-11-27 21:32:24,519 [INFO] tensorflow: global_step/sec: 14.2586
2021-11-27 21:32:24,586 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.456
INFO:tensorflow:global_step/sec: 14.6974
2021-11-27 21:32:24,655 [INFO] tensorflow: global_step/sec: 14.6974
INFO:tensorflow:global_step/sec: 14.0924
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INFO:tensorflow:global_step/sec: 13.8409
2021-11-27 21:32:24,942 [INFO] tensorflow: global_step/sec: 13.8409
INFO:tensorflow:global_step/sec: 13.9689
2021-11-27 21:32:25,085 [INFO] tensorflow: global_step/sec: 13.9689
INFO:tensorflow:global_step/sec: 14.7609
2021-11-27 21:32:25,220 [INFO] tensorflow: global_step/sec: 14.7609
INFO:tensorflow:Saving checkpoints for step-660.
2021-11-27 21:32:25,291 [INFO] tensorflow: Saving checkpoints for step-660.
2021-11-27 21:32:27,694 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 9464/9464 [00:00<00:00, 25950.90it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 8228/8228 [00:00<00:00, 28442.31it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 2382/2382 [00:00<00:00, 26669.74it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 11667/11667 [00:00<00:00, 28879.89it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 11897/11897 [00:00<00:00, 30530.80it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 4009/4009 [00:00<00:00, 24358.89it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 9895/9895 [00:00<00:00, 38853.75it/s]
Epoch 30/120
=========================
Validation cost: 0.001164
Mean average_precision (in %): 4.2231
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 0.657461
floor 0
palette 0.00523879
pillar 1.31196
pushcart 0
rackframe 6.2239
rackshelf 9.30193
wall 20.5074
Median Inference Time: 0.007165
INFO:tensorflow:epoch = 30.0, learning_rate = 0.00049999997, loss = 0.0014004486, step = 660 (18.097 sec)
2021-11-27 21:32:38,384 [INFO] tensorflow: epoch = 30.0, learning_rate = 0.00049999997, loss = 0.0014004486, step = 660 (18.097 sec)
INFO:tensorflow:global_step/sec: 0.151918
2021-11-27 21:32:38,385 [INFO] tensorflow: global_step/sec: 0.151918
2021-11-27 21:32:38,386 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 30/120: loss: 0.00140 learning rate: 0.00050 Time taken: 0:00:14.554359 ETA: 0:21:49.892349
INFO:tensorflow:global_step/sec: 14.4657
2021-11-27 21:32:38,524 [INFO] tensorflow: global_step/sec: 14.4657
INFO:tensorflow:global_step/sec: 14.4099
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INFO:tensorflow:global_step/sec: 14.5693
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INFO:tensorflow:global_step/sec: 14.0068
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INFO:tensorflow:global_step/sec: 14.1569
2021-11-27 21:32:39,084 [INFO] tensorflow: global_step/sec: 14.1569
INFO:tensorflow:global_step/sec: 14.267
2021-11-27 21:32:39,224 [INFO] tensorflow: global_step/sec: 14.267
INFO:tensorflow:global_step/sec: 14.4686
2021-11-27 21:32:39,362 [INFO] tensorflow: global_step/sec: 14.4686
2021-11-27 21:32:39,363 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 6.767
INFO:tensorflow:global_step/sec: 14.7445
2021-11-27 21:32:39,498 [INFO] tensorflow: global_step/sec: 14.7445
INFO:tensorflow:global_step/sec: 14.5212
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INFO:tensorflow:global_step/sec: 14.4805
2021-11-27 21:32:39,774 [INFO] tensorflow: global_step/sec: 14.4805
INFO:tensorflow:global_step/sec: 14.3056
2021-11-27 21:32:39,914 [INFO] tensorflow: global_step/sec: 14.3056
2021-11-27 21:32:39,915 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 31/120: loss: 0.00156 learning rate: 0.00050 Time taken: 0:00:01.531411 ETA: 0:02:16.295594
INFO:tensorflow:global_step/sec: 14.1456
2021-11-27 21:32:40,055 [INFO] tensorflow: global_step/sec: 14.1456
INFO:tensorflow:global_step/sec: 15.1835
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INFO:tensorflow:global_step/sec: 14.5779
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INFO:tensorflow:global_step/sec: 15.3496
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INFO:tensorflow:global_step/sec: 15.2895
2021-11-27 21:32:40,585 [INFO] tensorflow: global_step/sec: 15.2895
INFO:tensorflow:global_step/sec: 14.6721
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INFO:tensorflow:global_step/sec: 14.1121
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INFO:tensorflow:global_step/sec: 14.6013
2021-11-27 21:32:41,000 [INFO] tensorflow: global_step/sec: 14.6013
2021-11-27 21:32:41,068 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.664
INFO:tensorflow:global_step/sec: 14.5962
2021-11-27 21:32:41,137 [INFO] tensorflow: global_step/sec: 14.5962
INFO:tensorflow:global_step/sec: 14.263
2021-11-27 21:32:41,277 [INFO] tensorflow: global_step/sec: 14.263
INFO:tensorflow:global_step/sec: 14.2234
2021-11-27 21:32:41,418 [INFO] tensorflow: global_step/sec: 14.2234
2021-11-27 21:32:41,419 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 32/120: loss: 0.00154 learning rate: 0.00050 Time taken: 0:00:01.503738 ETA: 0:02:12.328959
INFO:tensorflow:global_step/sec: 15.118
2021-11-27 21:32:41,550 [INFO] tensorflow: global_step/sec: 15.118
INFO:tensorflow:global_step/sec: 14.6076
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INFO:tensorflow:global_step/sec: 14.7102
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INFO:tensorflow:global_step/sec: 14.309
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INFO:tensorflow:global_step/sec: 14.4039
2021-11-27 21:32:42,102 [INFO] tensorflow: global_step/sec: 14.4039
INFO:tensorflow:global_step/sec: 14.7045
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INFO:tensorflow:global_step/sec: 14.5524
2021-11-27 21:32:42,375 [INFO] tensorflow: global_step/sec: 14.5524
INFO:tensorflow:global_step/sec: 14.9722
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INFO:tensorflow:global_step/sec: 14.4851
2021-11-27 21:32:42,647 [INFO] tensorflow: global_step/sec: 14.4851
INFO:tensorflow:global_step/sec: 15.1488
2021-11-27 21:32:42,779 [INFO] tensorflow: global_step/sec: 15.1488
2021-11-27 21:32:42,780 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.443
INFO:tensorflow:global_step/sec: 13.2843
2021-11-27 21:32:42,929 [INFO] tensorflow: global_step/sec: 13.2843
2021-11-27 21:32:42,930 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 33/120: loss: 0.00141 learning rate: 0.00050 Time taken: 0:00:01.502839 ETA: 0:02:10.746980
INFO:tensorflow:global_step/sec: 14.3123
2021-11-27 21:32:43,069 [INFO] tensorflow: global_step/sec: 14.3123
INFO:tensorflow:global_step/sec: 14.4227
2021-11-27 21:32:43,208 [INFO] tensorflow: global_step/sec: 14.4227
INFO:tensorflow:global_step/sec: 14.7635
2021-11-27 21:32:43,343 [INFO] tensorflow: global_step/sec: 14.7635
INFO:tensorflow:epoch = 33.36363636363637, learning_rate = 0.00049999997, loss = 0.0013472163, step = 734 (5.094 sec)
2021-11-27 21:32:43,478 [INFO] tensorflow: epoch = 33.36363636363637, learning_rate = 0.00049999997, loss = 0.0013472163, step = 734 (5.094 sec)
INFO:tensorflow:global_step/sec: 14.6789
2021-11-27 21:32:43,479 [INFO] tensorflow: global_step/sec: 14.6789
INFO:tensorflow:global_step/sec: 14.5483
2021-11-27 21:32:43,617 [INFO] tensorflow: global_step/sec: 14.5483
INFO:tensorflow:global_step/sec: 13.9031
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INFO:tensorflow:global_step/sec: 14.922
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INFO:tensorflow:global_step/sec: 14.8578
2021-11-27 21:32:44,029 [INFO] tensorflow: global_step/sec: 14.8578
INFO:tensorflow:global_step/sec: 14.8988
2021-11-27 21:32:44,164 [INFO] tensorflow: global_step/sec: 14.8988
INFO:tensorflow:global_step/sec: 14.5407
2021-11-27 21:32:44,301 [INFO] tensorflow: global_step/sec: 14.5407
INFO:tensorflow:global_step/sec: 14.3613
2021-11-27 21:32:44,440 [INFO] tensorflow: global_step/sec: 14.3613
2021-11-27 21:32:44,441 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 34/120: loss: 0.00140 learning rate: 0.00050 Time taken: 0:00:01.515900 ETA: 0:02:10.367371
2021-11-27 21:32:44,504 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.017
INFO:tensorflow:global_step/sec: 15.458
2021-11-27 21:32:44,570 [INFO] tensorflow: global_step/sec: 15.458
INFO:tensorflow:global_step/sec: 14.9633
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INFO:tensorflow:global_step/sec: 14.3656
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INFO:tensorflow:global_step/sec: 14.613
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INFO:tensorflow:global_step/sec: 13.8544
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INFO:tensorflow:global_step/sec: 14.6963
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INFO:tensorflow:global_step/sec: 14.3702
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INFO:tensorflow:global_step/sec: 14.3116
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INFO:tensorflow:global_step/sec: 13.2295
2021-11-27 21:32:45,971 [INFO] tensorflow: global_step/sec: 13.2295
2021-11-27 21:32:45,972 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 35/120: loss: 0.00158 learning rate: 0.00050 Time taken: 0:00:01.526463 ETA: 0:02:09.749378
INFO:tensorflow:global_step/sec: 14.85
2021-11-27 21:32:46,106 [INFO] tensorflow: global_step/sec: 14.85
INFO:tensorflow:global_step/sec: 15.0526
2021-11-27 21:32:46,238 [INFO] tensorflow: global_step/sec: 15.0526
2021-11-27 21:32:46,239 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.636
INFO:tensorflow:global_step/sec: 14.4186
2021-11-27 21:32:46,377 [INFO] tensorflow: global_step/sec: 14.4186
INFO:tensorflow:global_step/sec: 14.1258
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INFO:tensorflow:global_step/sec: 14.3816
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INFO:tensorflow:global_step/sec: 14.8252
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INFO:tensorflow:global_step/sec: 15.1449
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INFO:tensorflow:global_step/sec: 14.7781
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INFO:tensorflow:global_step/sec: 14.1028
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INFO:tensorflow:global_step/sec: 14.7033
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INFO:tensorflow:global_step/sec: 14.0873
2021-11-27 21:32:47,480 [INFO] tensorflow: global_step/sec: 14.0873
2021-11-27 21:32:47,481 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 36/120: loss: 0.00146 learning rate: 0.00050 Time taken: 0:00:01.506683 ETA: 0:02:06.561341
INFO:tensorflow:global_step/sec: 14.5565
2021-11-27 21:32:47,617 [INFO] tensorflow: global_step/sec: 14.5565
INFO:tensorflow:global_step/sec: 14.7497
2021-11-27 21:32:47,753 [INFO] tensorflow: global_step/sec: 14.7497
INFO:tensorflow:global_step/sec: 14.8356
2021-11-27 21:32:47,888 [INFO] tensorflow: global_step/sec: 14.8356
2021-11-27 21:32:47,953 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.350
INFO:tensorflow:global_step/sec: 14.6259
2021-11-27 21:32:48,024 [INFO] tensorflow: global_step/sec: 14.6259
INFO:tensorflow:global_step/sec: 14.6353
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INFO:tensorflow:global_step/sec: 14.5341
2021-11-27 21:32:48,299 [INFO] tensorflow: global_step/sec: 14.5341
INFO:tensorflow:global_step/sec: 14.7215
2021-11-27 21:32:48,434 [INFO] tensorflow: global_step/sec: 14.7215
INFO:tensorflow:epoch = 36.72727272727273, learning_rate = 0.00049999997, loss = 0.0014747924, step = 808 (5.095 sec)
2021-11-27 21:32:48,573 [INFO] tensorflow: epoch = 36.72727272727273, learning_rate = 0.00049999997, loss = 0.0014747924, step = 808 (5.095 sec)
INFO:tensorflow:global_step/sec: 14.3285
2021-11-27 21:32:48,574 [INFO] tensorflow: global_step/sec: 14.3285
INFO:tensorflow:global_step/sec: 14.5799
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INFO:tensorflow:global_step/sec: 14.1664
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INFO:tensorflow:global_step/sec: 13.7631
2021-11-27 21:32:48,998 [INFO] tensorflow: global_step/sec: 13.7631
2021-11-27 21:32:48,999 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 37/120: loss: 0.00185 learning rate: 0.00050 Time taken: 0:00:01.516000 ETA: 0:02:05.827963
INFO:tensorflow:global_step/sec: 14.835
2021-11-27 21:32:49,133 [INFO] tensorflow: global_step/sec: 14.835
INFO:tensorflow:global_step/sec: 14.273
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INFO:tensorflow:global_step/sec: 14.5869
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INFO:tensorflow:global_step/sec: 14.4334
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INFO:tensorflow:global_step/sec: 14.936
2021-11-27 21:32:49,682 [INFO] tensorflow: global_step/sec: 14.936
2021-11-27 21:32:49,683 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.834
INFO:tensorflow:global_step/sec: 14.3397
2021-11-27 21:32:49,822 [INFO] tensorflow: global_step/sec: 14.3397
INFO:tensorflow:global_step/sec: 14.25
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INFO:tensorflow:global_step/sec: 13.8079
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INFO:tensorflow:global_step/sec: 14.0843
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INFO:tensorflow:global_step/sec: 14.2765
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INFO:tensorflow:global_step/sec: 13.5643
2021-11-27 21:32:50,536 [INFO] tensorflow: global_step/sec: 13.5643
2021-11-27 21:32:50,538 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 38/120: loss: 0.00147 learning rate: 0.00050 Time taken: 0:00:01.539168 ETA: 0:02:06.211747
INFO:tensorflow:global_step/sec: 14.3483
2021-11-27 21:32:50,676 [INFO] tensorflow: global_step/sec: 14.3483
INFO:tensorflow:global_step/sec: 14.4771
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INFO:tensorflow:global_step/sec: 14.7469
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INFO:tensorflow:global_step/sec: 14.0668
2021-11-27 21:32:51,092 [INFO] tensorflow: global_step/sec: 14.0668
INFO:tensorflow:global_step/sec: 14.661
2021-11-27 21:32:51,228 [INFO] tensorflow: global_step/sec: 14.661
INFO:tensorflow:global_step/sec: 14.2397
2021-11-27 21:32:51,369 [INFO] tensorflow: global_step/sec: 14.2397
2021-11-27 21:32:51,438 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 56.994
INFO:tensorflow:global_step/sec: 14.2795
2021-11-27 21:32:51,509 [INFO] tensorflow: global_step/sec: 14.2795
INFO:tensorflow:global_step/sec: 13.9655
2021-11-27 21:32:51,652 [INFO] tensorflow: global_step/sec: 13.9655
INFO:tensorflow:global_step/sec: 13.8627
2021-11-27 21:32:51,796 [INFO] tensorflow: global_step/sec: 13.8627
INFO:tensorflow:global_step/sec: 14.2911
2021-11-27 21:32:51,936 [INFO] tensorflow: global_step/sec: 14.2911
INFO:tensorflow:global_step/sec: 13.1637
2021-11-27 21:32:52,088 [INFO] tensorflow: global_step/sec: 13.1637
2021-11-27 21:32:52,090 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 39/120: loss: 0.00161 learning rate: 0.00050 Time taken: 0:00:01.547016 ETA: 0:02:05.308288
INFO:tensorflow:global_step/sec: 14.8911
2021-11-27 21:32:52,222 [INFO] tensorflow: global_step/sec: 14.8911
INFO:tensorflow:global_step/sec: 14.5099
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INFO:tensorflow:global_step/sec: 13.5787
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INFO:tensorflow:global_step/sec: 14.1389
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INFO:tensorflow:global_step/sec: 13.9978
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INFO:tensorflow:global_step/sec: 14.7987
2021-11-27 21:32:52,927 [INFO] tensorflow: global_step/sec: 14.7987
INFO:tensorflow:global_step/sec: 15.0165
2021-11-27 21:32:53,060 [INFO] tensorflow: global_step/sec: 15.0165
INFO:tensorflow:global_step/sec: 14.6274
2021-11-27 21:32:53,197 [INFO] tensorflow: global_step/sec: 14.6274
2021-11-27 21:32:53,198 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 56.824
INFO:tensorflow:global_step/sec: 14.5524
2021-11-27 21:32:53,334 [INFO] tensorflow: global_step/sec: 14.5524
INFO:tensorflow:global_step/sec: 14.8787
2021-11-27 21:32:53,469 [INFO] tensorflow: global_step/sec: 14.8787
INFO:tensorflow:Saving checkpoints for step-880.
2021-11-27 21:32:53,538 [INFO] tensorflow: Saving checkpoints for step-880.
2021-11-27 21:32:56,039 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 4330/4330 [00:00<00:00, 27824.98it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 9054/9054 [00:00<00:00, 29263.29it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 1661/1661 [00:00<00:00, 25930.76it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 13296/13296 [00:00<00:00, 30918.94it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 8373/8373 [00:00<00:00, 29561.52it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 3676/3676 [00:00<00:00, 24088.14it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 7359/7359 [00:00<00:00, 38038.78it/s]
Epoch 40/120
=========================
Validation cost: 0.001069
Mean average_precision (in %): 6.1684
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 2.42723
floor 0
palette 0.0348023
pillar 4.67769
pushcart 0
rackframe 13.4735
rackshelf 15.5739
wall 19.3285
Median Inference Time: 0.007937
INFO:tensorflow:epoch = 40.0, learning_rate = 0.00049999997, loss = 0.0016446046, step = 880 (16.673 sec)
2021-11-27 21:33:05,246 [INFO] tensorflow: epoch = 40.0, learning_rate = 0.00049999997, loss = 0.0016446046, step = 880 (16.673 sec)
INFO:tensorflow:global_step/sec: 0.169804
2021-11-27 21:33:05,247 [INFO] tensorflow: global_step/sec: 0.169804
2021-11-27 21:33:05,248 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 40/120: loss: 0.00164 learning rate: 0.00050 Time taken: 0:00:13.158530 ETA: 0:17:32.682362
INFO:tensorflow:global_step/sec: 14.6689
2021-11-27 21:33:05,383 [INFO] tensorflow: global_step/sec: 14.6689
INFO:tensorflow:global_step/sec: 14.1188
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INFO:tensorflow:global_step/sec: 14.3951
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INFO:tensorflow:global_step/sec: 14.7127
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INFO:tensorflow:global_step/sec: 14.3691
2021-11-27 21:33:05,939 [INFO] tensorflow: global_step/sec: 14.3691
INFO:tensorflow:global_step/sec: 14.4377
2021-11-27 21:33:06,078 [INFO] tensorflow: global_step/sec: 14.4377
INFO:tensorflow:global_step/sec: 14.6455
2021-11-27 21:33:06,214 [INFO] tensorflow: global_step/sec: 14.6455
INFO:tensorflow:global_step/sec: 14.9074
2021-11-27 21:33:06,348 [INFO] tensorflow: global_step/sec: 14.9074
INFO:tensorflow:global_step/sec: 15.0927
2021-11-27 21:33:06,481 [INFO] tensorflow: global_step/sec: 15.0927
2021-11-27 21:33:06,551 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 7.489
INFO:tensorflow:global_step/sec: 14.2229
2021-11-27 21:33:06,622 [INFO] tensorflow: global_step/sec: 14.2229
INFO:tensorflow:global_step/sec: 14.0467
2021-11-27 21:33:06,764 [INFO] tensorflow: global_step/sec: 14.0467
2021-11-27 21:33:06,765 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 41/120: loss: 0.00151 learning rate: 0.00050 Time taken: 0:00:01.516923 ETA: 0:01:59.836951
INFO:tensorflow:global_step/sec: 15.0784
2021-11-27 21:33:06,897 [INFO] tensorflow: global_step/sec: 15.0784
INFO:tensorflow:global_step/sec: 13.5394
2021-11-27 21:33:07,044 [INFO] tensorflow: global_step/sec: 13.5394
INFO:tensorflow:global_step/sec: 14.6299
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INFO:tensorflow:global_step/sec: 14.3833
2021-11-27 21:33:07,320 [INFO] tensorflow: global_step/sec: 14.3833
INFO:tensorflow:global_step/sec: 15.0823
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INFO:tensorflow:global_step/sec: 14.3516
2021-11-27 21:33:07,592 [INFO] tensorflow: global_step/sec: 14.3516
INFO:tensorflow:global_step/sec: 15.2871
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INFO:tensorflow:global_step/sec: 14.7135
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INFO:tensorflow:global_step/sec: 14.7307
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INFO:tensorflow:global_step/sec: 14.8146
2021-11-27 21:33:08,130 [INFO] tensorflow: global_step/sec: 14.8146
INFO:tensorflow:global_step/sec: 14.0035
2021-11-27 21:33:08,272 [INFO] tensorflow: global_step/sec: 14.0035
2021-11-27 21:33:08,274 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 42/120: loss: 0.00125 learning rate: 0.00050 Time taken: 0:00:01.509022 ETA: 0:01:57.703697
2021-11-27 21:33:08,274 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.063
INFO:tensorflow:global_step/sec: 14.2453
2021-11-27 21:33:08,413 [INFO] tensorflow: global_step/sec: 14.2453
INFO:tensorflow:global_step/sec: 14.7175
2021-11-27 21:33:08,549 [INFO] tensorflow: global_step/sec: 14.7175
INFO:tensorflow:global_step/sec: 14.4183
2021-11-27 21:33:08,687 [INFO] tensorflow: global_step/sec: 14.4183
INFO:tensorflow:global_step/sec: 14.4027
2021-11-27 21:33:08,826 [INFO] tensorflow: global_step/sec: 14.4027
INFO:tensorflow:global_step/sec: 14.6654
2021-11-27 21:33:08,963 [INFO] tensorflow: global_step/sec: 14.6654
INFO:tensorflow:global_step/sec: 15.2233
2021-11-27 21:33:09,094 [INFO] tensorflow: global_step/sec: 15.2233
INFO:tensorflow:global_step/sec: 14.8415
2021-11-27 21:33:09,229 [INFO] tensorflow: global_step/sec: 14.8415
INFO:tensorflow:global_step/sec: 15.3095
2021-11-27 21:33:09,359 [INFO] tensorflow: global_step/sec: 15.3095
INFO:tensorflow:global_step/sec: 15.1184
2021-11-27 21:33:09,492 [INFO] tensorflow: global_step/sec: 15.1184
INFO:tensorflow:global_step/sec: 14.5763
2021-11-27 21:33:09,629 [INFO] tensorflow: global_step/sec: 14.5763
INFO:tensorflow:global_step/sec: 13.8235
2021-11-27 21:33:09,774 [INFO] tensorflow: global_step/sec: 13.8235
2021-11-27 21:33:09,775 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 43/120: loss: 0.00168 learning rate: 0.00050 Time taken: 0:00:01.495542 ETA: 0:01:55.156756
INFO:tensorflow:global_step/sec: 14.6323
2021-11-27 21:33:09,910 [INFO] tensorflow: global_step/sec: 14.6323
2021-11-27 21:33:09,979 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.642
INFO:tensorflow:global_step/sec: 14.4616
2021-11-27 21:33:10,048 [INFO] tensorflow: global_step/sec: 14.4616
INFO:tensorflow:global_step/sec: 14.4352
2021-11-27 21:33:10,187 [INFO] tensorflow: global_step/sec: 14.4352
INFO:tensorflow:epoch = 43.36363636363637, learning_rate = 0.00049999997, loss = 0.0011689283, step = 954 (5.074 sec)
2021-11-27 21:33:10,320 [INFO] tensorflow: epoch = 43.36363636363637, learning_rate = 0.00049999997, loss = 0.0011689283, step = 954 (5.074 sec)
INFO:tensorflow:global_step/sec: 14.9045
2021-11-27 21:33:10,321 [INFO] tensorflow: global_step/sec: 14.9045
INFO:tensorflow:global_step/sec: 14.8267
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INFO:tensorflow:global_step/sec: 14.887
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INFO:tensorflow:global_step/sec: 14.6449
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INFO:tensorflow:global_step/sec: 14.5802
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INFO:tensorflow:global_step/sec: 14.649
2021-11-27 21:33:11,001 [INFO] tensorflow: global_step/sec: 14.649
INFO:tensorflow:global_step/sec: 15.0163
2021-11-27 21:33:11,134 [INFO] tensorflow: global_step/sec: 15.0163
INFO:tensorflow:global_step/sec: 13.89
2021-11-27 21:33:11,278 [INFO] tensorflow: global_step/sec: 13.89
2021-11-27 21:33:11,279 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 44/120: loss: 0.00138 learning rate: 0.00050 Time taken: 0:00:01.502695 ETA: 0:01:54.204808
INFO:tensorflow:global_step/sec: 14.5376
2021-11-27 21:33:11,416 [INFO] tensorflow: global_step/sec: 14.5376
INFO:tensorflow:global_step/sec: 14.9906
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INFO:tensorflow:global_step/sec: 14.9057
2021-11-27 21:33:11,683 [INFO] tensorflow: global_step/sec: 14.9057
2021-11-27 21:33:11,684 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.680
INFO:tensorflow:global_step/sec: 15.1208
2021-11-27 21:33:11,815 [INFO] tensorflow: global_step/sec: 15.1208
INFO:tensorflow:global_step/sec: 14.828
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INFO:tensorflow:global_step/sec: 14.5413
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INFO:tensorflow:global_step/sec: 14.3019
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INFO:tensorflow:global_step/sec: 14.0469
2021-11-27 21:33:12,779 [INFO] tensorflow: global_step/sec: 14.0469
2021-11-27 21:33:12,779 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 45/120: loss: 0.00129 learning rate: 0.00050 Time taken: 0:00:01.500749 ETA: 0:01:52.556165
INFO:tensorflow:global_step/sec: 14.6207
2021-11-27 21:33:12,915 [INFO] tensorflow: global_step/sec: 14.6207
INFO:tensorflow:global_step/sec: 14.2684
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INFO:tensorflow:global_step/sec: 14.1099
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INFO:tensorflow:global_step/sec: 14.601
2021-11-27 21:33:13,334 [INFO] tensorflow: global_step/sec: 14.601
2021-11-27 21:33:13,402 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.228
INFO:tensorflow:global_step/sec: 14.7052
2021-11-27 21:33:13,470 [INFO] tensorflow: global_step/sec: 14.7052
INFO:tensorflow:global_step/sec: 14.3695
2021-11-27 21:33:13,609 [INFO] tensorflow: global_step/sec: 14.3695
INFO:tensorflow:global_step/sec: 14.5011
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INFO:tensorflow:global_step/sec: 14.2794
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INFO:tensorflow:global_step/sec: 14.4875
2021-11-27 21:33:14,026 [INFO] tensorflow: global_step/sec: 14.4875
INFO:tensorflow:global_step/sec: 14.6722
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INFO:tensorflow:global_step/sec: 14.064
2021-11-27 21:33:14,304 [INFO] tensorflow: global_step/sec: 14.064
2021-11-27 21:33:14,305 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 46/120: loss: 0.00145 learning rate: 0.00050 Time taken: 0:00:01.526521 ETA: 0:01:52.962587
INFO:tensorflow:global_step/sec: 14.5126
2021-11-27 21:33:14,442 [INFO] tensorflow: global_step/sec: 14.5126
INFO:tensorflow:global_step/sec: 13.7883
2021-11-27 21:33:14,587 [INFO] tensorflow: global_step/sec: 13.7883
INFO:tensorflow:global_step/sec: 14.328
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INFO:tensorflow:global_step/sec: 14.7833
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INFO:tensorflow:global_step/sec: 14.4733
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INFO:tensorflow:global_step/sec: 15.3278
2021-11-27 21:33:15,130 [INFO] tensorflow: global_step/sec: 15.3278
2021-11-27 21:33:15,131 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.833
INFO:tensorflow:global_step/sec: 15.042
2021-11-27 21:33:15,263 [INFO] tensorflow: global_step/sec: 15.042
INFO:tensorflow:epoch = 46.72727272727273, learning_rate = 0.00049999997, loss = 0.0013563591, step = 1028 (5.081 sec)
2021-11-27 21:33:15,401 [INFO] tensorflow: epoch = 46.72727272727273, learning_rate = 0.00049999997, loss = 0.0013563591, step = 1028 (5.081 sec)
INFO:tensorflow:global_step/sec: 14.4092
2021-11-27 21:33:15,402 [INFO] tensorflow: global_step/sec: 14.4092
INFO:tensorflow:global_step/sec: 14.5178
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INFO:tensorflow:global_step/sec: 14.1935
2021-11-27 21:33:15,820 [INFO] tensorflow: global_step/sec: 14.1935
2021-11-27 21:33:15,821 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 47/120: loss: 0.00134 learning rate: 0.00050 Time taken: 0:00:01.514091 ETA: 0:01:50.528644
INFO:tensorflow:global_step/sec: 14.7633
2021-11-27 21:33:15,955 [INFO] tensorflow: global_step/sec: 14.7633
INFO:tensorflow:global_step/sec: 14.9801
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2021-11-27 21:33:16,774 [INFO] tensorflow: global_step/sec: 14.6741
2021-11-27 21:33:16,842 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.461
INFO:tensorflow:global_step/sec: 14.6539
2021-11-27 21:33:16,910 [INFO] tensorflow: global_step/sec: 14.6539
INFO:tensorflow:global_step/sec: 14.5254
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INFO:tensorflow:global_step/sec: 13.5828
2021-11-27 21:33:17,195 [INFO] tensorflow: global_step/sec: 13.5828
INFO:tensorflow:global_step/sec: 13.3352
2021-11-27 21:33:17,345 [INFO] tensorflow: global_step/sec: 13.3352
2021-11-27 21:33:17,346 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 48/120: loss: 0.00141 learning rate: 0.00050 Time taken: 0:00:01.521384 ETA: 0:01:49.539682
INFO:tensorflow:global_step/sec: 14.2792
2021-11-27 21:33:17,485 [INFO] tensorflow: global_step/sec: 14.2792
INFO:tensorflow:global_step/sec: 14.968
2021-11-27 21:33:17,619 [INFO] tensorflow: global_step/sec: 14.968
INFO:tensorflow:global_step/sec: 14.8724
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INFO:tensorflow:global_step/sec: 14.6931
2021-11-27 21:33:17,890 [INFO] tensorflow: global_step/sec: 14.6931
INFO:tensorflow:global_step/sec: 14.7765
2021-11-27 21:33:18,025 [INFO] tensorflow: global_step/sec: 14.7765
INFO:tensorflow:global_step/sec: 14.2299
2021-11-27 21:33:18,165 [INFO] tensorflow: global_step/sec: 14.2299
INFO:tensorflow:global_step/sec: 14.5137
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INFO:tensorflow:global_step/sec: 14.1807
2021-11-27 21:33:18,444 [INFO] tensorflow: global_step/sec: 14.1807
INFO:tensorflow:global_step/sec: 14.9438
2021-11-27 21:33:18,578 [INFO] tensorflow: global_step/sec: 14.9438
2021-11-27 21:33:18,579 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.576
INFO:tensorflow:global_step/sec: 14.3488
2021-11-27 21:33:18,717 [INFO] tensorflow: global_step/sec: 14.3488
INFO:tensorflow:global_step/sec: 13.2164
2021-11-27 21:33:18,869 [INFO] tensorflow: global_step/sec: 13.2164
2021-11-27 21:33:18,870 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 49/120: loss: 0.00120 learning rate: 0.00050 Time taken: 0:00:01.521893 ETA: 0:01:48.054388
INFO:tensorflow:global_step/sec: 15.5876
2021-11-27 21:33:18,997 [INFO] tensorflow: global_step/sec: 15.5876
INFO:tensorflow:global_step/sec: 14.0888
2021-11-27 21:33:19,139 [INFO] tensorflow: global_step/sec: 14.0888
INFO:tensorflow:global_step/sec: 14.3642
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INFO:tensorflow:global_step/sec: 14.677
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INFO:tensorflow:global_step/sec: 14.908
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INFO:tensorflow:global_step/sec: 14.4925
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INFO:tensorflow:global_step/sec: 14.0443
2021-11-27 21:33:19,829 [INFO] tensorflow: global_step/sec: 14.0443
INFO:tensorflow:global_step/sec: 14.4353
2021-11-27 21:33:19,968 [INFO] tensorflow: global_step/sec: 14.4353
INFO:tensorflow:global_step/sec: 14.8685
2021-11-27 21:33:20,102 [INFO] tensorflow: global_step/sec: 14.8685
INFO:tensorflow:global_step/sec: 14.9292
2021-11-27 21:33:20,236 [INFO] tensorflow: global_step/sec: 14.9292
INFO:tensorflow:Saving checkpoints for step-1100.
2021-11-27 21:33:20,301 [INFO] tensorflow: Saving checkpoints for step-1100.
WARNING:tensorflow:Ignoring: /tmp/tmpsfb6vaed; No such file or directory
2021-11-27 21:33:20,397 [WARNING] tensorflow: Ignoring: /tmp/tmpsfb6vaed; No such file or directory
2021-11-27 21:33:22,688 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 2494/2494 [00:00<00:00, 27644.71it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 7938/7938 [00:00<00:00, 29075.50it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 1117/1117 [00:00<00:00, 25596.68it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 12650/12650 [00:00<00:00, 30824.90it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 3730/3730 [00:00<00:00, 30261.88it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 2686/2686 [00:00<00:00, 23651.51it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 5494/5494 [00:00<00:00, 36513.88it/s]
Epoch 50/120
=========================
Validation cost: 0.000885
Mean average_precision (in %): 8.5120
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 6.51931
floor 0
palette 0.0310058
pillar 9.62457
pushcart 0
rackframe 17.0854
rackshelf 22.4368
wall 20.9107
Median Inference Time: 0.007654
2021-11-27 21:33:30,380 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 8.474
INFO:tensorflow:epoch = 50.0, learning_rate = 0.00049999997, loss = 0.0012902536, step = 1100 (15.046 sec)
2021-11-27 21:33:30,447 [INFO] tensorflow: epoch = 50.0, learning_rate = 0.00049999997, loss = 0.0012902536, step = 1100 (15.046 sec)
INFO:tensorflow:global_step/sec: 0.19585
2021-11-27 21:33:30,448 [INFO] tensorflow: global_step/sec: 0.19585
2021-11-27 21:33:30,449 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 50/120: loss: 0.00129 learning rate: 0.00050 Time taken: 0:00:11.578965 ETA: 0:13:30.527546
INFO:tensorflow:global_step/sec: 14.1983
2021-11-27 21:33:30,589 [INFO] tensorflow: global_step/sec: 14.1983
INFO:tensorflow:global_step/sec: 14.5205
2021-11-27 21:33:30,727 [INFO] tensorflow: global_step/sec: 14.5205
INFO:tensorflow:global_step/sec: 14.2919
2021-11-27 21:33:30,867 [INFO] tensorflow: global_step/sec: 14.2919
INFO:tensorflow:global_step/sec: 14.8691
2021-11-27 21:33:31,001 [INFO] tensorflow: global_step/sec: 14.8691
INFO:tensorflow:global_step/sec: 14.7885
2021-11-27 21:33:31,136 [INFO] tensorflow: global_step/sec: 14.7885
INFO:tensorflow:global_step/sec: 14.2814
2021-11-27 21:33:31,276 [INFO] tensorflow: global_step/sec: 14.2814
INFO:tensorflow:global_step/sec: 15.189
2021-11-27 21:33:31,408 [INFO] tensorflow: global_step/sec: 15.189
INFO:tensorflow:global_step/sec: 14.6988
2021-11-27 21:33:31,544 [INFO] tensorflow: global_step/sec: 14.6988
INFO:tensorflow:global_step/sec: 14.3512
2021-11-27 21:33:31,684 [INFO] tensorflow: global_step/sec: 14.3512
INFO:tensorflow:global_step/sec: 14.9409
2021-11-27 21:33:31,817 [INFO] tensorflow: global_step/sec: 14.9409
INFO:tensorflow:global_step/sec: 13.5658
2021-11-27 21:33:31,965 [INFO] tensorflow: global_step/sec: 13.5658
2021-11-27 21:33:31,966 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 51/120: loss: 0.00139 learning rate: 0.00050 Time taken: 0:00:01.514344 ETA: 0:01:44.489734
INFO:tensorflow:global_step/sec: 14.9051
2021-11-27 21:33:32,099 [INFO] tensorflow: global_step/sec: 14.9051
2021-11-27 21:33:32,100 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.182
INFO:tensorflow:global_step/sec: 14.706
2021-11-27 21:33:32,235 [INFO] tensorflow: global_step/sec: 14.706
INFO:tensorflow:global_step/sec: 14.6407
2021-11-27 21:33:32,372 [INFO] tensorflow: global_step/sec: 14.6407
INFO:tensorflow:global_step/sec: 15.2104
2021-11-27 21:33:32,503 [INFO] tensorflow: global_step/sec: 15.2104
INFO:tensorflow:global_step/sec: 14.7969
2021-11-27 21:33:32,638 [INFO] tensorflow: global_step/sec: 14.7969
INFO:tensorflow:global_step/sec: 15.3496
2021-11-27 21:33:32,769 [INFO] tensorflow: global_step/sec: 15.3496
INFO:tensorflow:global_step/sec: 14.49
2021-11-27 21:33:32,907 [INFO] tensorflow: global_step/sec: 14.49
INFO:tensorflow:global_step/sec: 14.5508
2021-11-27 21:33:33,044 [INFO] tensorflow: global_step/sec: 14.5508
INFO:tensorflow:global_step/sec: 14.5053
2021-11-27 21:33:33,182 [INFO] tensorflow: global_step/sec: 14.5053
INFO:tensorflow:global_step/sec: 15.0849
2021-11-27 21:33:33,315 [INFO] tensorflow: global_step/sec: 15.0849
INFO:tensorflow:global_step/sec: 14.0417
2021-11-27 21:33:33,457 [INFO] tensorflow: global_step/sec: 14.0417
2021-11-27 21:33:33,458 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 52/120: loss: 0.00132 learning rate: 0.00050 Time taken: 0:00:01.492121 ETA: 0:01:41.464227
INFO:tensorflow:global_step/sec: 14.4571
2021-11-27 21:33:33,595 [INFO] tensorflow: global_step/sec: 14.4571
INFO:tensorflow:global_step/sec: 14.5691
2021-11-27 21:33:33,733 [INFO] tensorflow: global_step/sec: 14.5691
2021-11-27 21:33:33,801 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.801
INFO:tensorflow:global_step/sec: 14.2178
2021-11-27 21:33:33,873 [INFO] tensorflow: global_step/sec: 14.2178
INFO:tensorflow:global_step/sec: 14.1132
2021-11-27 21:33:34,015 [INFO] tensorflow: global_step/sec: 14.1132
INFO:tensorflow:global_step/sec: 14.3817
2021-11-27 21:33:34,154 [INFO] tensorflow: global_step/sec: 14.3817
INFO:tensorflow:global_step/sec: 14.8803
2021-11-27 21:33:34,288 [INFO] tensorflow: global_step/sec: 14.8803
INFO:tensorflow:global_step/sec: 14.1958
2021-11-27 21:33:34,429 [INFO] tensorflow: global_step/sec: 14.1958
INFO:tensorflow:global_step/sec: 14.7728
2021-11-27 21:33:34,565 [INFO] tensorflow: global_step/sec: 14.7728
INFO:tensorflow:global_step/sec: 13.882
2021-11-27 21:33:34,709 [INFO] tensorflow: global_step/sec: 13.882
INFO:tensorflow:global_step/sec: 14.4162
2021-11-27 21:33:34,847 [INFO] tensorflow: global_step/sec: 14.4162
INFO:tensorflow:global_step/sec: 15.0644
2021-11-27 21:33:34,980 [INFO] tensorflow: global_step/sec: 15.0644
2021-11-27 21:33:34,981 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 53/120: loss: 0.00155 learning rate: 0.00050 Time taken: 0:00:01.523912 ETA: 0:01:42.102133
INFO:tensorflow:global_step/sec: 14.9325
2021-11-27 21:33:35,114 [INFO] tensorflow: global_step/sec: 14.9325
INFO:tensorflow:global_step/sec: 13.6267
2021-11-27 21:33:35,261 [INFO] tensorflow: global_step/sec: 13.6267
INFO:tensorflow:global_step/sec: 14.4439
2021-11-27 21:33:35,399 [INFO] tensorflow: global_step/sec: 14.4439
INFO:tensorflow:epoch = 53.36363636363637, learning_rate = 0.00049999997, loss = 0.0015671041, step = 1174 (5.095 sec)
2021-11-27 21:33:35,542 [INFO] tensorflow: epoch = 53.36363636363637, learning_rate = 0.00049999997, loss = 0.0015671041, step = 1174 (5.095 sec)
INFO:tensorflow:global_step/sec: 13.9204
2021-11-27 21:33:35,543 [INFO] tensorflow: global_step/sec: 13.9204
2021-11-27 21:33:35,544 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.388
INFO:tensorflow:global_step/sec: 15.1313
2021-11-27 21:33:35,675 [INFO] tensorflow: global_step/sec: 15.1313
INFO:tensorflow:global_step/sec: 14.0623
2021-11-27 21:33:35,817 [INFO] tensorflow: global_step/sec: 14.0623
INFO:tensorflow:global_step/sec: 14.245
2021-11-27 21:33:35,958 [INFO] tensorflow: global_step/sec: 14.245
INFO:tensorflow:global_step/sec: 14.8979
2021-11-27 21:33:36,092 [INFO] tensorflow: global_step/sec: 14.8979
INFO:tensorflow:global_step/sec: 13.5534
2021-11-27 21:33:36,240 [INFO] tensorflow: global_step/sec: 13.5534
INFO:tensorflow:global_step/sec: 13.8358
2021-11-27 21:33:36,384 [INFO] tensorflow: global_step/sec: 13.8358
INFO:tensorflow:global_step/sec: 13.4675
2021-11-27 21:33:36,533 [INFO] tensorflow: global_step/sec: 13.4675
2021-11-27 21:33:36,534 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 54/120: loss: 0.00139 learning rate: 0.00050 Time taken: 0:00:01.544009 ETA: 0:01:41.904576
INFO:tensorflow:global_step/sec: 14.913
2021-11-27 21:33:36,667 [INFO] tensorflow: global_step/sec: 14.913
INFO:tensorflow:global_step/sec: 15.1723
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INFO:tensorflow:global_step/sec: 14.7418
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INFO:tensorflow:global_step/sec: 14.8257
2021-11-27 21:33:37,069 [INFO] tensorflow: global_step/sec: 14.8257
INFO:tensorflow:global_step/sec: 14.4484
2021-11-27 21:33:37,208 [INFO] tensorflow: global_step/sec: 14.4484
2021-11-27 21:33:37,278 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.698
INFO:tensorflow:global_step/sec: 14.3609
2021-11-27 21:33:37,347 [INFO] tensorflow: global_step/sec: 14.3609
INFO:tensorflow:global_step/sec: 14.6544
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INFO:tensorflow:global_step/sec: 14.3337
2021-11-27 21:33:37,623 [INFO] tensorflow: global_step/sec: 14.3337
INFO:tensorflow:global_step/sec: 15.0066
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INFO:tensorflow:global_step/sec: 13.9024
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INFO:tensorflow:global_step/sec: 14.1419
2021-11-27 21:33:38,041 [INFO] tensorflow: global_step/sec: 14.1419
2021-11-27 21:33:38,043 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 55/120: loss: 0.00153 learning rate: 0.00050 Time taken: 0:00:01.511989 ETA: 0:01:38.279277
INFO:tensorflow:global_step/sec: 14.3633
2021-11-27 21:33:38,181 [INFO] tensorflow: global_step/sec: 14.3633
INFO:tensorflow:global_step/sec: 14.9576
2021-11-27 21:33:38,314 [INFO] tensorflow: global_step/sec: 14.9576
INFO:tensorflow:global_step/sec: 15.1663
2021-11-27 21:33:38,446 [INFO] tensorflow: global_step/sec: 15.1663
INFO:tensorflow:global_step/sec: 14.5145
2021-11-27 21:33:38,584 [INFO] tensorflow: global_step/sec: 14.5145
INFO:tensorflow:global_step/sec: 14.6171
2021-11-27 21:33:38,721 [INFO] tensorflow: global_step/sec: 14.6171
INFO:tensorflow:global_step/sec: 14.1905
2021-11-27 21:33:38,862 [INFO] tensorflow: global_step/sec: 14.1905
INFO:tensorflow:global_step/sec: 14.0799
2021-11-27 21:33:39,004 [INFO] tensorflow: global_step/sec: 14.0799
2021-11-27 21:33:39,005 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.910
INFO:tensorflow:global_step/sec: 14.5196
2021-11-27 21:33:39,142 [INFO] tensorflow: global_step/sec: 14.5196
INFO:tensorflow:global_step/sec: 15.2052
2021-11-27 21:33:39,273 [INFO] tensorflow: global_step/sec: 15.2052
INFO:tensorflow:global_step/sec: 14.7164
2021-11-27 21:33:39,409 [INFO] tensorflow: global_step/sec: 14.7164
INFO:tensorflow:global_step/sec: 14.3408
2021-11-27 21:33:39,549 [INFO] tensorflow: global_step/sec: 14.3408
2021-11-27 21:33:39,550 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 56/120: loss: 0.00129 learning rate: 0.00050 Time taken: 0:00:01.503366 ETA: 0:01:36.215393
INFO:tensorflow:global_step/sec: 15.0761
2021-11-27 21:33:39,681 [INFO] tensorflow: global_step/sec: 15.0761
INFO:tensorflow:global_step/sec: 14.5313
2021-11-27 21:33:39,819 [INFO] tensorflow: global_step/sec: 14.5313
INFO:tensorflow:global_step/sec: 14.1581
2021-11-27 21:33:39,960 [INFO] tensorflow: global_step/sec: 14.1581
INFO:tensorflow:global_step/sec: 15.0281
2021-11-27 21:33:40,093 [INFO] tensorflow: global_step/sec: 15.0281
INFO:tensorflow:global_step/sec: 14.4851
2021-11-27 21:33:40,231 [INFO] tensorflow: global_step/sec: 14.4851
INFO:tensorflow:global_step/sec: 14.5866
2021-11-27 21:33:40,368 [INFO] tensorflow: global_step/sec: 14.5866
INFO:tensorflow:global_step/sec: 14.3521
2021-11-27 21:33:40,508 [INFO] tensorflow: global_step/sec: 14.3521
INFO:tensorflow:epoch = 56.72727272727273, learning_rate = 0.00049999997, loss = 0.0015351584, step = 1248 (5.100 sec)
2021-11-27 21:33:40,642 [INFO] tensorflow: epoch = 56.72727272727273, learning_rate = 0.00049999997, loss = 0.0015351584, step = 1248 (5.100 sec)
INFO:tensorflow:global_step/sec: 14.7948
2021-11-27 21:33:40,643 [INFO] tensorflow: global_step/sec: 14.7948
2021-11-27 21:33:40,709 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.683
INFO:tensorflow:global_step/sec: 14.304
2021-11-27 21:33:40,783 [INFO] tensorflow: global_step/sec: 14.304
INFO:tensorflow:global_step/sec: 14.3902
2021-11-27 21:33:40,922 [INFO] tensorflow: global_step/sec: 14.3902
INFO:tensorflow:global_step/sec: 13.755
2021-11-27 21:33:41,067 [INFO] tensorflow: global_step/sec: 13.755
2021-11-27 21:33:41,068 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 57/120: loss: 0.00155 learning rate: 0.00050 Time taken: 0:00:01.519072 ETA: 0:01:35.701509
INFO:tensorflow:global_step/sec: 14.761
2021-11-27 21:33:41,203 [INFO] tensorflow: global_step/sec: 14.761
INFO:tensorflow:global_step/sec: 14.7625
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INFO:tensorflow:global_step/sec: 14.8115
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INFO:tensorflow:global_step/sec: 13.8933
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INFO:tensorflow:global_step/sec: 13.9201
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INFO:tensorflow:global_step/sec: 14.4722
2021-11-27 21:33:41,899 [INFO] tensorflow: global_step/sec: 14.4722
INFO:tensorflow:global_step/sec: 14.1865
2021-11-27 21:33:42,040 [INFO] tensorflow: global_step/sec: 14.1865
INFO:tensorflow:global_step/sec: 14.6606
2021-11-27 21:33:42,176 [INFO] tensorflow: global_step/sec: 14.6606
INFO:tensorflow:global_step/sec: 14.9574
2021-11-27 21:33:42,310 [INFO] tensorflow: global_step/sec: 14.9574
INFO:tensorflow:global_step/sec: 14.4513
2021-11-27 21:33:42,448 [INFO] tensorflow: global_step/sec: 14.4513
2021-11-27 21:33:42,449 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.476
INFO:tensorflow:global_step/sec: 13.3929
2021-11-27 21:33:42,598 [INFO] tensorflow: global_step/sec: 13.3929
2021-11-27 21:33:42,599 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 58/120: loss: 0.00148 learning rate: 0.00050 Time taken: 0:00:01.527693 ETA: 0:01:34.716938
INFO:tensorflow:global_step/sec: 14.7503
2021-11-27 21:33:42,733 [INFO] tensorflow: global_step/sec: 14.7503
INFO:tensorflow:global_step/sec: 14.3179
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INFO:tensorflow:global_step/sec: 14.5708
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INFO:tensorflow:global_step/sec: 14.463
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INFO:tensorflow:global_step/sec: 14.7799
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INFO:tensorflow:global_step/sec: 14.8605
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INFO:tensorflow:global_step/sec: 15.2307
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INFO:tensorflow:global_step/sec: 14.6198
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INFO:tensorflow:global_step/sec: 14.6943
2021-11-27 21:33:43,823 [INFO] tensorflow: global_step/sec: 14.6943
INFO:tensorflow:global_step/sec: 15.3027
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INFO:tensorflow:global_step/sec: 14.2585
2021-11-27 21:33:44,094 [INFO] tensorflow: global_step/sec: 14.2585
2021-11-27 21:33:44,095 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 59/120: loss: 0.00151 learning rate: 0.00050 Time taken: 0:00:01.495363 ETA: 0:01:31.217143
2021-11-27 21:33:44,161 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.454
INFO:tensorflow:global_step/sec: 14.9341
2021-11-27 21:33:44,228 [INFO] tensorflow: global_step/sec: 14.9341
INFO:tensorflow:global_step/sec: 14.5881
2021-11-27 21:33:44,365 [INFO] tensorflow: global_step/sec: 14.5881
INFO:tensorflow:global_step/sec: 14.4416
2021-11-27 21:33:44,503 [INFO] tensorflow: global_step/sec: 14.4416
INFO:tensorflow:global_step/sec: 14.8175
2021-11-27 21:33:44,638 [INFO] tensorflow: global_step/sec: 14.8175
INFO:tensorflow:global_step/sec: 14.8709
2021-11-27 21:33:44,773 [INFO] tensorflow: global_step/sec: 14.8709
INFO:tensorflow:global_step/sec: 14.5072
2021-11-27 21:33:44,911 [INFO] tensorflow: global_step/sec: 14.5072
INFO:tensorflow:global_step/sec: 15.1607
2021-11-27 21:33:45,042 [INFO] tensorflow: global_step/sec: 15.1607
INFO:tensorflow:global_step/sec: 15.0658
2021-11-27 21:33:45,175 [INFO] tensorflow: global_step/sec: 15.0658
INFO:tensorflow:global_step/sec: 14.855
2021-11-27 21:33:45,310 [INFO] tensorflow: global_step/sec: 14.855
INFO:tensorflow:global_step/sec: 14.5366
2021-11-27 21:33:45,447 [INFO] tensorflow: global_step/sec: 14.5366
INFO:tensorflow:Saving checkpoints for step-1320.
2021-11-27 21:33:45,516 [INFO] tensorflow: Saving checkpoints for step-1320.
WARNING:tensorflow:Ignoring: /tmp/tmp74wm50jo; No such file or directory
2021-11-27 21:33:45,617 [WARNING] tensorflow: Ignoring: /tmp/tmp74wm50jo; No such file or directory
2021-11-27 21:33:47,983 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 2297/2297 [00:00<00:00, 25240.81it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 9125/9125 [00:00<00:00, 27755.90it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 1392/1392 [00:00<00:00, 24972.40it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 13010/13010 [00:00<00:00, 29365.38it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 2259/2259 [00:00<00:00, 26658.26it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 2538/2538 [00:00<00:00, 24626.54it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 10772/10772 [00:00<00:00, 40784.59it/s]
Epoch 60/120
=========================
Validation cost: 0.000975
Mean average_precision (in %): 10.1440
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 3.48893
floor 0
palette 0.200376
pillar 6.69095
pushcart 0
rackframe 19.7687
rackshelf 34.2332
wall 26.9136
Median Inference Time: 0.008690
INFO:tensorflow:epoch = 60.0, learning_rate = 0.00049999997, loss = 0.0014266176, step = 1320 (15.120 sec)
2021-11-27 21:33:55,762 [INFO] tensorflow: epoch = 60.0, learning_rate = 0.00049999997, loss = 0.0014266176, step = 1320 (15.120 sec)
INFO:tensorflow:global_step/sec: 0.193885
2021-11-27 21:33:55,763 [INFO] tensorflow: global_step/sec: 0.193885
2021-11-27 21:33:55,764 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 60/120: loss: 0.00143 learning rate: 0.00050 Time taken: 0:00:11.666830 ETA: 0:11:40.009789
INFO:tensorflow:global_step/sec: 14.7872
2021-11-27 21:33:55,898 [INFO] tensorflow: global_step/sec: 14.7872
INFO:tensorflow:global_step/sec: 14.4633
2021-11-27 21:33:56,036 [INFO] tensorflow: global_step/sec: 14.4633
2021-11-27 21:33:56,037 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 8.420
INFO:tensorflow:global_step/sec: 14.5349
2021-11-27 21:33:56,174 [INFO] tensorflow: global_step/sec: 14.5349
INFO:tensorflow:global_step/sec: 14.286
2021-11-27 21:33:56,314 [INFO] tensorflow: global_step/sec: 14.286
INFO:tensorflow:global_step/sec: 14.7936
2021-11-27 21:33:56,449 [INFO] tensorflow: global_step/sec: 14.7936
INFO:tensorflow:global_step/sec: 14.6724
2021-11-27 21:33:56,585 [INFO] tensorflow: global_step/sec: 14.6724
INFO:tensorflow:global_step/sec: 14.963
2021-11-27 21:33:56,719 [INFO] tensorflow: global_step/sec: 14.963
INFO:tensorflow:global_step/sec: 14.7648
2021-11-27 21:33:56,855 [INFO] tensorflow: global_step/sec: 14.7648
INFO:tensorflow:global_step/sec: 15.0408
2021-11-27 21:33:56,988 [INFO] tensorflow: global_step/sec: 15.0408
INFO:tensorflow:global_step/sec: 14.432
2021-11-27 21:33:57,126 [INFO] tensorflow: global_step/sec: 14.432
INFO:tensorflow:global_step/sec: 13.9501
2021-11-27 21:33:57,270 [INFO] tensorflow: global_step/sec: 13.9501
2021-11-27 21:33:57,271 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 61/120: loss: 0.00132 learning rate: 0.00050 Time taken: 0:00:01.509826 ETA: 0:01:29.079759
INFO:tensorflow:global_step/sec: 14.4909
2021-11-27 21:33:57,408 [INFO] tensorflow: global_step/sec: 14.4909
INFO:tensorflow:global_step/sec: 15.0177
2021-11-27 21:33:57,541 [INFO] tensorflow: global_step/sec: 15.0177
INFO:tensorflow:global_step/sec: 14.6552
2021-11-27 21:33:57,677 [INFO] tensorflow: global_step/sec: 14.6552
2021-11-27 21:33:57,747 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.489
INFO:tensorflow:global_step/sec: 14.3625
2021-11-27 21:33:57,816 [INFO] tensorflow: global_step/sec: 14.3625
INFO:tensorflow:global_step/sec: 14.8119
2021-11-27 21:33:57,951 [INFO] tensorflow: global_step/sec: 14.8119
INFO:tensorflow:global_step/sec: 13.9939
2021-11-27 21:33:58,094 [INFO] tensorflow: global_step/sec: 13.9939
INFO:tensorflow:global_step/sec: 14.699
2021-11-27 21:33:58,230 [INFO] tensorflow: global_step/sec: 14.699
INFO:tensorflow:global_step/sec: 14.7073
2021-11-27 21:33:58,366 [INFO] tensorflow: global_step/sec: 14.7073
INFO:tensorflow:global_step/sec: 15.3871
2021-11-27 21:33:58,496 [INFO] tensorflow: global_step/sec: 15.3871
INFO:tensorflow:global_step/sec: 14.9723
2021-11-27 21:33:58,630 [INFO] tensorflow: global_step/sec: 14.9723
INFO:tensorflow:global_step/sec: 14.2827
2021-11-27 21:33:58,770 [INFO] tensorflow: global_step/sec: 14.2827
2021-11-27 21:33:58,771 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 62/120: loss: 0.00138 learning rate: 0.00050 Time taken: 0:00:01.494721 ETA: 0:01:26.693814
INFO:tensorflow:global_step/sec: 14.4427
2021-11-27 21:33:58,908 [INFO] tensorflow: global_step/sec: 14.4427
INFO:tensorflow:global_step/sec: 14.0075
2021-11-27 21:33:59,051 [INFO] tensorflow: global_step/sec: 14.0075
INFO:tensorflow:global_step/sec: 14.571
2021-11-27 21:33:59,189 [INFO] tensorflow: global_step/sec: 14.571
INFO:tensorflow:global_step/sec: 14.5474
2021-11-27 21:33:59,326 [INFO] tensorflow: global_step/sec: 14.5474
INFO:tensorflow:global_step/sec: 14.6023
2021-11-27 21:33:59,463 [INFO] tensorflow: global_step/sec: 14.6023
2021-11-27 21:33:59,464 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.266
INFO:tensorflow:global_step/sec: 14.4687
2021-11-27 21:33:59,601 [INFO] tensorflow: global_step/sec: 14.4687
INFO:tensorflow:global_step/sec: 14.2795
2021-11-27 21:33:59,741 [INFO] tensorflow: global_step/sec: 14.2795
INFO:tensorflow:global_step/sec: 14.1805
2021-11-27 21:33:59,882 [INFO] tensorflow: global_step/sec: 14.1805
INFO:tensorflow:global_step/sec: 14.4587
2021-11-27 21:34:00,021 [INFO] tensorflow: global_step/sec: 14.4587
INFO:tensorflow:global_step/sec: 14.6281
2021-11-27 21:34:00,157 [INFO] tensorflow: global_step/sec: 14.6281
INFO:tensorflow:global_step/sec: 14.199
2021-11-27 21:34:00,298 [INFO] tensorflow: global_step/sec: 14.199
2021-11-27 21:34:00,299 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 63/120: loss: 0.00152 learning rate: 0.00050 Time taken: 0:00:01.528007 ETA: 0:01:27.096401
INFO:tensorflow:global_step/sec: 15.1165
2021-11-27 21:34:00,430 [INFO] tensorflow: global_step/sec: 15.1165
INFO:tensorflow:global_step/sec: 14.651
2021-11-27 21:34:00,567 [INFO] tensorflow: global_step/sec: 14.651
INFO:tensorflow:global_step/sec: 15.2323
2021-11-27 21:34:00,698 [INFO] tensorflow: global_step/sec: 15.2323
INFO:tensorflow:epoch = 63.36363636363637, learning_rate = 0.00049999997, loss = 0.0015953407, step = 1394 (5.071 sec)
2021-11-27 21:34:00,832 [INFO] tensorflow: epoch = 63.36363636363637, learning_rate = 0.00049999997, loss = 0.0015953407, step = 1394 (5.071 sec)
INFO:tensorflow:global_step/sec: 14.7972
2021-11-27 21:34:00,833 [INFO] tensorflow: global_step/sec: 14.7972
INFO:tensorflow:global_step/sec: 14.4147
2021-11-27 21:34:00,972 [INFO] tensorflow: global_step/sec: 14.4147
INFO:tensorflow:global_step/sec: 14.5532
2021-11-27 21:34:01,110 [INFO] tensorflow: global_step/sec: 14.5532
2021-11-27 21:34:01,179 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.329
INFO:tensorflow:global_step/sec: 14.0159
2021-11-27 21:34:01,252 [INFO] tensorflow: global_step/sec: 14.0159
INFO:tensorflow:global_step/sec: 14.8762
2021-11-27 21:34:01,387 [INFO] tensorflow: global_step/sec: 14.8762
INFO:tensorflow:global_step/sec: 14.9651
2021-11-27 21:34:01,520 [INFO] tensorflow: global_step/sec: 14.9651
INFO:tensorflow:global_step/sec: 14.8619
2021-11-27 21:34:01,655 [INFO] tensorflow: global_step/sec: 14.8619
INFO:tensorflow:global_step/sec: 14.4586
2021-11-27 21:34:01,793 [INFO] tensorflow: global_step/sec: 14.4586
2021-11-27 21:34:01,794 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 64/120: loss: 0.00158 learning rate: 0.00050 Time taken: 0:00:01.494732 ETA: 0:01:23.705000
INFO:tensorflow:global_step/sec: 14.57
2021-11-27 21:34:01,931 [INFO] tensorflow: global_step/sec: 14.57
INFO:tensorflow:global_step/sec: 15.0004
2021-11-27 21:34:02,064 [INFO] tensorflow: global_step/sec: 15.0004
INFO:tensorflow:global_step/sec: 14.5424
2021-11-27 21:34:02,201 [INFO] tensorflow: global_step/sec: 14.5424
INFO:tensorflow:global_step/sec: 14.3588
2021-11-27 21:34:02,341 [INFO] tensorflow: global_step/sec: 14.3588
INFO:tensorflow:global_step/sec: 14.7167
2021-11-27 21:34:02,477 [INFO] tensorflow: global_step/sec: 14.7167
INFO:tensorflow:global_step/sec: 14.7886
2021-11-27 21:34:02,612 [INFO] tensorflow: global_step/sec: 14.7886
INFO:tensorflow:global_step/sec: 14.397
2021-11-27 21:34:02,751 [INFO] tensorflow: global_step/sec: 14.397
INFO:tensorflow:global_step/sec: 14.6402
2021-11-27 21:34:02,887 [INFO] tensorflow: global_step/sec: 14.6402
2021-11-27 21:34:02,888 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.511
INFO:tensorflow:global_step/sec: 13.7666
2021-11-27 21:34:03,033 [INFO] tensorflow: global_step/sec: 13.7666
INFO:tensorflow:global_step/sec: 14.9609
2021-11-27 21:34:03,166 [INFO] tensorflow: global_step/sec: 14.9609
INFO:tensorflow:global_step/sec: 13.4594
2021-11-27 21:34:03,315 [INFO] tensorflow: global_step/sec: 13.4594
2021-11-27 21:34:03,317 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 65/120: loss: 0.00134 learning rate: 0.00050 Time taken: 0:00:01.514543 ETA: 0:01:23.299855
INFO:tensorflow:global_step/sec: 14.6825
2021-11-27 21:34:03,451 [INFO] tensorflow: global_step/sec: 14.6825
INFO:tensorflow:global_step/sec: 13.662
2021-11-27 21:34:03,598 [INFO] tensorflow: global_step/sec: 13.662
INFO:tensorflow:global_step/sec: 14.2616
2021-11-27 21:34:03,738 [INFO] tensorflow: global_step/sec: 14.2616
INFO:tensorflow:global_step/sec: 14.3427
2021-11-27 21:34:03,877 [INFO] tensorflow: global_step/sec: 14.3427
INFO:tensorflow:global_step/sec: 14.0508
2021-11-27 21:34:04,020 [INFO] tensorflow: global_step/sec: 14.0508
INFO:tensorflow:global_step/sec: 13.8025
2021-11-27 21:34:04,164 [INFO] tensorflow: global_step/sec: 13.8025
INFO:tensorflow:global_step/sec: 13.9506
2021-11-27 21:34:04,308 [INFO] tensorflow: global_step/sec: 13.9506
INFO:tensorflow:global_step/sec: 14.5483
2021-11-27 21:34:04,445 [INFO] tensorflow: global_step/sec: 14.5483
INFO:tensorflow:global_step/sec: 13.6996
2021-11-27 21:34:04,591 [INFO] tensorflow: global_step/sec: 13.6996
2021-11-27 21:34:04,662 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 56.385
INFO:tensorflow:global_step/sec: 14.1634
2021-11-27 21:34:04,733 [INFO] tensorflow: global_step/sec: 14.1634
INFO:tensorflow:global_step/sec: 13.6234
2021-11-27 21:34:04,879 [INFO] tensorflow: global_step/sec: 13.6234
2021-11-27 21:34:04,881 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 66/120: loss: 0.00124 learning rate: 0.00050 Time taken: 0:00:01.562478 ETA: 0:01:24.373828
INFO:tensorflow:global_step/sec: 14.7475
2021-11-27 21:34:05,015 [INFO] tensorflow: global_step/sec: 14.7475
INFO:tensorflow:global_step/sec: 14.5771
2021-11-27 21:34:05,152 [INFO] tensorflow: global_step/sec: 14.5771
INFO:tensorflow:global_step/sec: 13.9188
2021-11-27 21:34:05,296 [INFO] tensorflow: global_step/sec: 13.9188
INFO:tensorflow:global_step/sec: 14.4473
2021-11-27 21:34:05,434 [INFO] tensorflow: global_step/sec: 14.4473
INFO:tensorflow:global_step/sec: 14.6541
2021-11-27 21:34:05,571 [INFO] tensorflow: global_step/sec: 14.6541
INFO:tensorflow:global_step/sec: 14.5884
2021-11-27 21:34:05,708 [INFO] tensorflow: global_step/sec: 14.5884
INFO:tensorflow:global_step/sec: 14.0189
2021-11-27 21:34:05,851 [INFO] tensorflow: global_step/sec: 14.0189
INFO:tensorflow:epoch = 66.68181818181819, learning_rate = 0.00049999997, loss = 0.0015700122, step = 1467 (5.090 sec)
2021-11-27 21:34:05,922 [INFO] tensorflow: epoch = 66.68181818181819, learning_rate = 0.00049999997, loss = 0.0015700122, step = 1467 (5.090 sec)
INFO:tensorflow:global_step/sec: 14.047
2021-11-27 21:34:05,993 [INFO] tensorflow: global_step/sec: 14.047
INFO:tensorflow:global_step/sec: 14.1691
2021-11-27 21:34:06,134 [INFO] tensorflow: global_step/sec: 14.1691
INFO:tensorflow:global_step/sec: 13.9246
2021-11-27 21:34:06,278 [INFO] tensorflow: global_step/sec: 13.9246
INFO:tensorflow:global_step/sec: 13.2248
2021-11-27 21:34:06,429 [INFO] tensorflow: global_step/sec: 13.2248
2021-11-27 21:34:06,430 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 67/120: loss: 0.00128 learning rate: 0.00050 Time taken: 0:00:01.548004 ETA: 0:01:22.044195
2021-11-27 21:34:06,430 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 56.566
INFO:tensorflow:global_step/sec: 14.2627
2021-11-27 21:34:06,569 [INFO] tensorflow: global_step/sec: 14.2627
INFO:tensorflow:global_step/sec: 14.5494
2021-11-27 21:34:06,707 [INFO] tensorflow: global_step/sec: 14.5494
INFO:tensorflow:global_step/sec: 14.3561
2021-11-27 21:34:06,846 [INFO] tensorflow: global_step/sec: 14.3561
INFO:tensorflow:global_step/sec: 14.9612
2021-11-27 21:34:06,980 [INFO] tensorflow: global_step/sec: 14.9612
INFO:tensorflow:global_step/sec: 14.6478
2021-11-27 21:34:07,116 [INFO] tensorflow: global_step/sec: 14.6478
INFO:tensorflow:global_step/sec: 14.3624
2021-11-27 21:34:07,255 [INFO] tensorflow: global_step/sec: 14.3624
INFO:tensorflow:global_step/sec: 14.6491
2021-11-27 21:34:07,392 [INFO] tensorflow: global_step/sec: 14.6491
INFO:tensorflow:global_step/sec: 14.3361
2021-11-27 21:34:07,531 [INFO] tensorflow: global_step/sec: 14.3361
INFO:tensorflow:global_step/sec: 14.5416
2021-11-27 21:34:07,669 [INFO] tensorflow: global_step/sec: 14.5416
INFO:tensorflow:global_step/sec: 13.5281
2021-11-27 21:34:07,817 [INFO] tensorflow: global_step/sec: 13.5281
INFO:tensorflow:global_step/sec: 13.5429
2021-11-27 21:34:07,965 [INFO] tensorflow: global_step/sec: 13.5429
2021-11-27 21:34:07,966 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 68/120: loss: 0.00117 learning rate: 0.00050 Time taken: 0:00:01.531856 ETA: 0:01:19.656528
INFO:tensorflow:global_step/sec: 14.4414
2021-11-27 21:34:08,103 [INFO] tensorflow: global_step/sec: 14.4414
2021-11-27 21:34:08,173 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.403
INFO:tensorflow:global_step/sec: 14.1548
2021-11-27 21:34:08,244 [INFO] tensorflow: global_step/sec: 14.1548
INFO:tensorflow:global_step/sec: 14.5714
2021-11-27 21:34:08,382 [INFO] tensorflow: global_step/sec: 14.5714
INFO:tensorflow:global_step/sec: 14.1127
2021-11-27 21:34:08,523 [INFO] tensorflow: global_step/sec: 14.1127
INFO:tensorflow:global_step/sec: 14.6206
2021-11-27 21:34:08,660 [INFO] tensorflow: global_step/sec: 14.6206
INFO:tensorflow:global_step/sec: 14.6829
2021-11-27 21:34:08,796 [INFO] tensorflow: global_step/sec: 14.6829
INFO:tensorflow:global_step/sec: 14.1628
2021-11-27 21:34:08,937 [INFO] tensorflow: global_step/sec: 14.1628
INFO:tensorflow:global_step/sec: 14.0238
2021-11-27 21:34:09,080 [INFO] tensorflow: global_step/sec: 14.0238
INFO:tensorflow:global_step/sec: 14.3273
2021-11-27 21:34:09,220 [INFO] tensorflow: global_step/sec: 14.3273
INFO:tensorflow:global_step/sec: 14.6254
2021-11-27 21:34:09,356 [INFO] tensorflow: global_step/sec: 14.6254
INFO:tensorflow:global_step/sec: 13.9285
2021-11-27 21:34:09,500 [INFO] tensorflow: global_step/sec: 13.9285
2021-11-27 21:34:09,501 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 69/120: loss: 0.00114 learning rate: 0.00050 Time taken: 0:00:01.539276 ETA: 0:01:18.503094
INFO:tensorflow:global_step/sec: 13.9658
2021-11-27 21:34:09,643 [INFO] tensorflow: global_step/sec: 13.9658
INFO:tensorflow:global_step/sec: 14.5352
2021-11-27 21:34:09,781 [INFO] tensorflow: global_step/sec: 14.5352
INFO:tensorflow:global_step/sec: 14.4218
2021-11-27 21:34:09,919 [INFO] tensorflow: global_step/sec: 14.4218
2021-11-27 21:34:09,920 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.232
INFO:tensorflow:global_step/sec: 14.9071
2021-11-27 21:34:10,054 [INFO] tensorflow: global_step/sec: 14.9071
INFO:tensorflow:global_step/sec: 15.1406
2021-11-27 21:34:10,186 [INFO] tensorflow: global_step/sec: 15.1406
INFO:tensorflow:global_step/sec: 14.9649
2021-11-27 21:34:10,319 [INFO] tensorflow: global_step/sec: 14.9649
INFO:tensorflow:global_step/sec: 15.2856
2021-11-27 21:34:10,450 [INFO] tensorflow: global_step/sec: 15.2856
INFO:tensorflow:global_step/sec: 14.8341
2021-11-27 21:34:10,585 [INFO] tensorflow: global_step/sec: 14.8341
INFO:tensorflow:global_step/sec: 14.4841
2021-11-27 21:34:10,723 [INFO] tensorflow: global_step/sec: 14.4841
INFO:tensorflow:global_step/sec: 14.5442
2021-11-27 21:34:10,861 [INFO] tensorflow: global_step/sec: 14.5442
INFO:tensorflow:Saving checkpoints for step-1540.
2021-11-27 21:34:10,929 [INFO] tensorflow: Saving checkpoints for step-1540.
WARNING:tensorflow:Ignoring: /tmp/tmpvpflokst; No such file or directory
2021-11-27 21:34:11,026 [WARNING] tensorflow: Ignoring: /tmp/tmpvpflokst; No such file or directory
2021-11-27 21:34:13,381 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 2346/2346 [00:00<00:00, 25264.88it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 6486/6486 [00:00<00:00, 26272.45it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 1366/1366 [00:00<00:00, 24581.45it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 11294/11294 [00:00<00:00, 26045.82it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 1633/1633 [00:00<00:00, 25001.00it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 2259/2259 [00:00<00:00, 23735.57it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 7430/7430 [00:00<00:00, 35866.04it/s]
Epoch 70/120
=========================
Validation cost: 0.000967
Mean average_precision (in %): 12.0589
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 11.3192
floor 0
palette 0.58884
pillar 8.05643
pushcart 0
rackframe 24.3459
rackshelf 36.9012
wall 27.319
Median Inference Time: 0.007168
INFO:tensorflow:epoch = 70.0, learning_rate = 0.00049999997, loss = 0.0012142942, step = 1540 (14.693 sec)
2021-11-27 21:34:20,615 [INFO] tensorflow: epoch = 70.0, learning_rate = 0.00049999997, loss = 0.0012142942, step = 1540 (14.693 sec)
INFO:tensorflow:global_step/sec: 0.20501
2021-11-27 21:34:20,616 [INFO] tensorflow: global_step/sec: 0.20501
2021-11-27 21:34:20,618 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 70/120: loss: 0.00121 learning rate: 0.00050 Time taken: 0:00:11.112018 ETA: 0:09:15.600917
INFO:tensorflow:global_step/sec: 13.776
2021-11-27 21:34:20,761 [INFO] tensorflow: global_step/sec: 13.776
INFO:tensorflow:global_step/sec: 14.4703
2021-11-27 21:34:20,900 [INFO] tensorflow: global_step/sec: 14.4703
INFO:tensorflow:global_step/sec: 14.5335
2021-11-27 21:34:21,037 [INFO] tensorflow: global_step/sec: 14.5335
INFO:tensorflow:global_step/sec: 15.0228
2021-11-27 21:34:21,170 [INFO] tensorflow: global_step/sec: 15.0228
2021-11-27 21:34:21,240 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 8.834
INFO:tensorflow:global_step/sec: 14.2342
2021-11-27 21:34:21,311 [INFO] tensorflow: global_step/sec: 14.2342
INFO:tensorflow:global_step/sec: 14.0878
2021-11-27 21:34:21,453 [INFO] tensorflow: global_step/sec: 14.0878
INFO:tensorflow:global_step/sec: 14.4293
2021-11-27 21:34:21,591 [INFO] tensorflow: global_step/sec: 14.4293
INFO:tensorflow:global_step/sec: 14.688
2021-11-27 21:34:21,728 [INFO] tensorflow: global_step/sec: 14.688
INFO:tensorflow:global_step/sec: 14.3982
2021-11-27 21:34:21,867 [INFO] tensorflow: global_step/sec: 14.3982
INFO:tensorflow:global_step/sec: 14.4479
2021-11-27 21:34:22,005 [INFO] tensorflow: global_step/sec: 14.4479
INFO:tensorflow:global_step/sec: 14.0586
2021-11-27 21:34:22,147 [INFO] tensorflow: global_step/sec: 14.0586
2021-11-27 21:34:22,148 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 71/120: loss: 0.00137 learning rate: 0.00050 Time taken: 0:00:01.530263 ETA: 0:01:14.982896
INFO:tensorflow:global_step/sec: 14.5517
2021-11-27 21:34:22,285 [INFO] tensorflow: global_step/sec: 14.5517
INFO:tensorflow:global_step/sec: 14.3151
2021-11-27 21:34:22,424 [INFO] tensorflow: global_step/sec: 14.3151
INFO:tensorflow:global_step/sec: 15.027
2021-11-27 21:34:22,557 [INFO] tensorflow: global_step/sec: 15.027
INFO:tensorflow:global_step/sec: 15.0643
2021-11-27 21:34:22,690 [INFO] tensorflow: global_step/sec: 15.0643
INFO:tensorflow:global_step/sec: 15.4816
2021-11-27 21:34:22,819 [INFO] tensorflow: global_step/sec: 15.4816
INFO:tensorflow:global_step/sec: 14.5782
2021-11-27 21:34:22,957 [INFO] tensorflow: global_step/sec: 14.5782
2021-11-27 21:34:22,957 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.240
INFO:tensorflow:global_step/sec: 14.4347
2021-11-27 21:34:23,095 [INFO] tensorflow: global_step/sec: 14.4347
INFO:tensorflow:global_step/sec: 14.7888
2021-11-27 21:34:23,230 [INFO] tensorflow: global_step/sec: 14.7888
INFO:tensorflow:global_step/sec: 14.7487
2021-11-27 21:34:23,366 [INFO] tensorflow: global_step/sec: 14.7487
INFO:tensorflow:global_step/sec: 14.8161
2021-11-27 21:34:23,501 [INFO] tensorflow: global_step/sec: 14.8161
INFO:tensorflow:global_step/sec: 14.4414
2021-11-27 21:34:23,639 [INFO] tensorflow: global_step/sec: 14.4414
2021-11-27 21:34:23,641 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 72/120: loss: 0.00114 learning rate: 0.00050 Time taken: 0:00:01.495012 ETA: 0:01:11.760590
INFO:tensorflow:global_step/sec: 14.3069
2021-11-27 21:34:23,779 [INFO] tensorflow: global_step/sec: 14.3069
INFO:tensorflow:global_step/sec: 14.1935
2021-11-27 21:34:23,920 [INFO] tensorflow: global_step/sec: 14.1935
INFO:tensorflow:global_step/sec: 14.8528
2021-11-27 21:34:24,055 [INFO] tensorflow: global_step/sec: 14.8528
INFO:tensorflow:global_step/sec: 14.3566
2021-11-27 21:34:24,194 [INFO] tensorflow: global_step/sec: 14.3566
INFO:tensorflow:global_step/sec: 14.8619
2021-11-27 21:34:24,329 [INFO] tensorflow: global_step/sec: 14.8619
INFO:tensorflow:global_step/sec: 15.3738
2021-11-27 21:34:24,459 [INFO] tensorflow: global_step/sec: 15.3738
INFO:tensorflow:global_step/sec: 14.9988
2021-11-27 21:34:24,592 [INFO] tensorflow: global_step/sec: 14.9988
2021-11-27 21:34:24,661 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.708
INFO:tensorflow:global_step/sec: 14.3551
2021-11-27 21:34:24,732 [INFO] tensorflow: global_step/sec: 14.3551
INFO:tensorflow:global_step/sec: 14.6924
2021-11-27 21:34:24,868 [INFO] tensorflow: global_step/sec: 14.6924
INFO:tensorflow:global_step/sec: 14.3516
2021-11-27 21:34:25,007 [INFO] tensorflow: global_step/sec: 14.3516
INFO:tensorflow:global_step/sec: 13.0972
2021-11-27 21:34:25,160 [INFO] tensorflow: global_step/sec: 13.0972
2021-11-27 21:34:25,161 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 73/120: loss: 0.00124 learning rate: 0.00050 Time taken: 0:00:01.513754 ETA: 0:01:11.146455
INFO:tensorflow:global_step/sec: 13.6495
2021-11-27 21:34:25,306 [INFO] tensorflow: global_step/sec: 13.6495
INFO:tensorflow:global_step/sec: 14.3687
2021-11-27 21:34:25,445 [INFO] tensorflow: global_step/sec: 14.3687
INFO:tensorflow:global_step/sec: 14.519
2021-11-27 21:34:25,583 [INFO] tensorflow: global_step/sec: 14.519
INFO:tensorflow:epoch = 73.36363636363636, learning_rate = 0.00049999997, loss = 0.0014130131, step = 1614 (5.101 sec)
2021-11-27 21:34:25,716 [INFO] tensorflow: epoch = 73.36363636363636, learning_rate = 0.00049999997, loss = 0.0014130131, step = 1614 (5.101 sec)
INFO:tensorflow:global_step/sec: 14.9241
2021-11-27 21:34:25,717 [INFO] tensorflow: global_step/sec: 14.9241
INFO:tensorflow:global_step/sec: 14.7477
2021-11-27 21:34:25,853 [INFO] tensorflow: global_step/sec: 14.7477
INFO:tensorflow:global_step/sec: 14.3344
2021-11-27 21:34:25,992 [INFO] tensorflow: global_step/sec: 14.3344
INFO:tensorflow:global_step/sec: 14.4996
2021-11-27 21:34:26,130 [INFO] tensorflow: global_step/sec: 14.4996
INFO:tensorflow:global_step/sec: 14.8608
2021-11-27 21:34:26,265 [INFO] tensorflow: global_step/sec: 14.8608
INFO:tensorflow:global_step/sec: 14.4108
2021-11-27 21:34:26,404 [INFO] tensorflow: global_step/sec: 14.4108
2021-11-27 21:34:26,404 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.381
INFO:tensorflow:global_step/sec: 14.2613
2021-11-27 21:34:26,544 [INFO] tensorflow: global_step/sec: 14.2613
INFO:tensorflow:global_step/sec: 13.998
2021-11-27 21:34:26,687 [INFO] tensorflow: global_step/sec: 13.998
2021-11-27 21:34:26,688 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 74/120: loss: 0.00122 learning rate: 0.00050 Time taken: 0:00:01.528346 ETA: 0:01:10.303919
INFO:tensorflow:global_step/sec: 14.2722
2021-11-27 21:34:26,827 [INFO] tensorflow: global_step/sec: 14.2722
INFO:tensorflow:global_step/sec: 14.412
2021-11-27 21:34:26,966 [INFO] tensorflow: global_step/sec: 14.412
INFO:tensorflow:global_step/sec: 14.3109
2021-11-27 21:34:27,105 [INFO] tensorflow: global_step/sec: 14.3109
INFO:tensorflow:global_step/sec: 14.6225
2021-11-27 21:34:27,242 [INFO] tensorflow: global_step/sec: 14.6225
INFO:tensorflow:global_step/sec: 14.0999
2021-11-27 21:34:27,384 [INFO] tensorflow: global_step/sec: 14.0999
INFO:tensorflow:global_step/sec: 14.8791
2021-11-27 21:34:27,518 [INFO] tensorflow: global_step/sec: 14.8791
INFO:tensorflow:global_step/sec: 14.4281
2021-11-27 21:34:27,657 [INFO] tensorflow: global_step/sec: 14.4281
INFO:tensorflow:global_step/sec: 14.3792
2021-11-27 21:34:27,796 [INFO] tensorflow: global_step/sec: 14.3792
INFO:tensorflow:global_step/sec: 15.1858
2021-11-27 21:34:27,928 [INFO] tensorflow: global_step/sec: 15.1858
INFO:tensorflow:global_step/sec: 14.9495
2021-11-27 21:34:28,062 [INFO] tensorflow: global_step/sec: 14.9495
2021-11-27 21:34:28,137 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.738
INFO:tensorflow:global_step/sec: 13.426
2021-11-27 21:34:28,211 [INFO] tensorflow: global_step/sec: 13.426
2021-11-27 21:34:28,212 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 75/120: loss: 0.00146 learning rate: 0.00050 Time taken: 0:00:01.515880 ETA: 0:01:08.214605
INFO:tensorflow:global_step/sec: 14.5916
2021-11-27 21:34:28,348 [INFO] tensorflow: global_step/sec: 14.5916
INFO:tensorflow:global_step/sec: 13.9949
2021-11-27 21:34:28,491 [INFO] tensorflow: global_step/sec: 13.9949
INFO:tensorflow:global_step/sec: 14.6617
2021-11-27 21:34:28,627 [INFO] tensorflow: global_step/sec: 14.6617
INFO:tensorflow:global_step/sec: 12.6905
2021-11-27 21:34:28,785 [INFO] tensorflow: global_step/sec: 12.6905
INFO:tensorflow:global_step/sec: 14.5777
2021-11-27 21:34:28,922 [INFO] tensorflow: global_step/sec: 14.5777
INFO:tensorflow:global_step/sec: 14.3469
2021-11-27 21:34:29,061 [INFO] tensorflow: global_step/sec: 14.3469
INFO:tensorflow:global_step/sec: 14.4457
2021-11-27 21:34:29,200 [INFO] tensorflow: global_step/sec: 14.4457
INFO:tensorflow:global_step/sec: 14.2087
2021-11-27 21:34:29,340 [INFO] tensorflow: global_step/sec: 14.2087
INFO:tensorflow:global_step/sec: 13.8875
2021-11-27 21:34:29,484 [INFO] tensorflow: global_step/sec: 13.8875
INFO:tensorflow:global_step/sec: 14.5319
2021-11-27 21:34:29,622 [INFO] tensorflow: global_step/sec: 14.5319
INFO:tensorflow:global_step/sec: 14.0259
2021-11-27 21:34:29,765 [INFO] tensorflow: global_step/sec: 14.0259
2021-11-27 21:34:29,766 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 76/120: loss: 0.00117 learning rate: 0.00050 Time taken: 0:00:01.555900 ETA: 0:01:08.459604
INFO:tensorflow:global_step/sec: 14.8202
2021-11-27 21:34:29,900 [INFO] tensorflow: global_step/sec: 14.8202
2021-11-27 21:34:29,900 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 56.760
INFO:tensorflow:global_step/sec: 14.9207
2021-11-27 21:34:30,034 [INFO] tensorflow: global_step/sec: 14.9207
INFO:tensorflow:global_step/sec: 14.5463
2021-11-27 21:34:30,171 [INFO] tensorflow: global_step/sec: 14.5463
INFO:tensorflow:global_step/sec: 14.4229
2021-11-27 21:34:30,310 [INFO] tensorflow: global_step/sec: 14.4229
INFO:tensorflow:global_step/sec: 14.949
2021-11-27 21:34:30,444 [INFO] tensorflow: global_step/sec: 14.949
INFO:tensorflow:global_step/sec: 14.6615
2021-11-27 21:34:30,580 [INFO] tensorflow: global_step/sec: 14.6615
INFO:tensorflow:global_step/sec: 15.0605
2021-11-27 21:34:30,713 [INFO] tensorflow: global_step/sec: 15.0605
INFO:tensorflow:epoch = 76.72727272727273, learning_rate = 0.00049999997, loss = 0.0012775091, step = 1688 (5.132 sec)
2021-11-27 21:34:30,848 [INFO] tensorflow: epoch = 76.72727272727273, learning_rate = 0.00049999997, loss = 0.0012775091, step = 1688 (5.132 sec)
INFO:tensorflow:global_step/sec: 14.6622
2021-11-27 21:34:30,849 [INFO] tensorflow: global_step/sec: 14.6622
INFO:tensorflow:global_step/sec: 14.5107
2021-11-27 21:34:30,987 [INFO] tensorflow: global_step/sec: 14.5107
INFO:tensorflow:global_step/sec: 14.4567
2021-11-27 21:34:31,125 [INFO] tensorflow: global_step/sec: 14.4567
INFO:tensorflow:global_step/sec: 14.1026
2021-11-27 21:34:31,267 [INFO] tensorflow: global_step/sec: 14.1026
2021-11-27 21:34:31,268 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 77/120: loss: 0.00115 learning rate: 0.00050 Time taken: 0:00:01.501561 ETA: 0:01:04.567130
INFO:tensorflow:global_step/sec: 14.3782
2021-11-27 21:34:31,406 [INFO] tensorflow: global_step/sec: 14.3782
INFO:tensorflow:global_step/sec: 14.88
2021-11-27 21:34:31,541 [INFO] tensorflow: global_step/sec: 14.88
2021-11-27 21:34:31,606 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.644
INFO:tensorflow:global_step/sec: 15.1397
2021-11-27 21:34:31,673 [INFO] tensorflow: global_step/sec: 15.1397
INFO:tensorflow:global_step/sec: 13.9983
2021-11-27 21:34:31,816 [INFO] tensorflow: global_step/sec: 13.9983
INFO:tensorflow:global_step/sec: 14.7001
2021-11-27 21:34:31,952 [INFO] tensorflow: global_step/sec: 14.7001
INFO:tensorflow:global_step/sec: 14.054
2021-11-27 21:34:32,094 [INFO] tensorflow: global_step/sec: 14.054
INFO:tensorflow:global_step/sec: 14.7756
2021-11-27 21:34:32,229 [INFO] tensorflow: global_step/sec: 14.7756
INFO:tensorflow:global_step/sec: 14.2503
2021-11-27 21:34:32,370 [INFO] tensorflow: global_step/sec: 14.2503
INFO:tensorflow:global_step/sec: 14.7584
2021-11-27 21:34:32,505 [INFO] tensorflow: global_step/sec: 14.7584
INFO:tensorflow:global_step/sec: 14.4373
2021-11-27 21:34:32,644 [INFO] tensorflow: global_step/sec: 14.4373
INFO:tensorflow:global_step/sec: 13.5848
2021-11-27 21:34:32,791 [INFO] tensorflow: global_step/sec: 13.5848
2021-11-27 21:34:32,792 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 78/120: loss: 0.00139 learning rate: 0.00050 Time taken: 0:00:01.521880 ETA: 0:01:03.918946
INFO:tensorflow:global_step/sec: 14.8891
2021-11-27 21:34:32,925 [INFO] tensorflow: global_step/sec: 14.8891
INFO:tensorflow:global_step/sec: 14.9327
2021-11-27 21:34:33,059 [INFO] tensorflow: global_step/sec: 14.9327
INFO:tensorflow:global_step/sec: 14.9107
2021-11-27 21:34:33,193 [INFO] tensorflow: global_step/sec: 14.9107
INFO:tensorflow:global_step/sec: 14.9896
2021-11-27 21:34:33,327 [INFO] tensorflow: global_step/sec: 14.9896
2021-11-27 21:34:33,328 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.073
INFO:tensorflow:global_step/sec: 14.3774
2021-11-27 21:34:33,466 [INFO] tensorflow: global_step/sec: 14.3774
INFO:tensorflow:global_step/sec: 14.2351
2021-11-27 21:34:33,606 [INFO] tensorflow: global_step/sec: 14.2351
INFO:tensorflow:global_step/sec: 14.9278
2021-11-27 21:34:33,740 [INFO] tensorflow: global_step/sec: 14.9278
INFO:tensorflow:global_step/sec: 14.0899
2021-11-27 21:34:33,882 [INFO] tensorflow: global_step/sec: 14.0899
INFO:tensorflow:global_step/sec: 15.2613
2021-11-27 21:34:34,013 [INFO] tensorflow: global_step/sec: 15.2613
INFO:tensorflow:global_step/sec: 14.5882
2021-11-27 21:34:34,150 [INFO] tensorflow: global_step/sec: 14.5882
INFO:tensorflow:global_step/sec: 14.2557
2021-11-27 21:34:34,291 [INFO] tensorflow: global_step/sec: 14.2557
2021-11-27 21:34:34,292 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 79/120: loss: 0.00119 learning rate: 0.00050 Time taken: 0:00:01.498712 ETA: 0:01:01.447175
INFO:tensorflow:global_step/sec: 14.3685
2021-11-27 21:34:34,430 [INFO] tensorflow: global_step/sec: 14.3685
INFO:tensorflow:global_step/sec: 14.7481
2021-11-27 21:34:34,566 [INFO] tensorflow: global_step/sec: 14.7481
INFO:tensorflow:global_step/sec: 14.2165
2021-11-27 21:34:34,706 [INFO] tensorflow: global_step/sec: 14.2165
INFO:tensorflow:global_step/sec: 14.2292
2021-11-27 21:34:34,847 [INFO] tensorflow: global_step/sec: 14.2292
INFO:tensorflow:global_step/sec: 14.6549
2021-11-27 21:34:34,983 [INFO] tensorflow: global_step/sec: 14.6549
2021-11-27 21:34:35,053 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.972
INFO:tensorflow:global_step/sec: 14.3731
2021-11-27 21:34:35,122 [INFO] tensorflow: global_step/sec: 14.3731
INFO:tensorflow:global_step/sec: 14.8295
2021-11-27 21:34:35,257 [INFO] tensorflow: global_step/sec: 14.8295
INFO:tensorflow:global_step/sec: 14.4415
2021-11-27 21:34:35,396 [INFO] tensorflow: global_step/sec: 14.4415
INFO:tensorflow:global_step/sec: 14.2979
2021-11-27 21:34:35,536 [INFO] tensorflow: global_step/sec: 14.2979
INFO:tensorflow:global_step/sec: 14.9839
2021-11-27 21:34:35,669 [INFO] tensorflow: global_step/sec: 14.9839
INFO:tensorflow:Saving checkpoints for step-1760.
2021-11-27 21:34:35,736 [INFO] tensorflow: Saving checkpoints for step-1760.
WARNING:tensorflow:Ignoring: /tmp/tmpekj3crvr; No such file or directory
2021-11-27 21:34:35,830 [WARNING] tensorflow: Ignoring: /tmp/tmpekj3crvr; No such file or directory
2021-11-27 21:34:38,126 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 1627/1627 [00:00<00:00, 24505.02it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 5925/5925 [00:00<00:00, 27407.25it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 906/906 [00:00<00:00, 23760.94it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 12133/12133 [00:00<00:00, 29910.78it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 1348/1348 [00:00<00:00, 24285.88it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 2479/2479 [00:00<00:00, 22614.22it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 9584/9584 [00:00<00:00, 44486.04it/s]
Epoch 80/120
=========================
Validation cost: 0.000840
Mean average_precision (in %): 13.8389
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 11.8029
floor 0
palette 0.137305
pillar 18.2058
pushcart 0
rackframe 23.6567
rackshelf 43.7159
wall 27.0316
Median Inference Time: 0.008084
INFO:tensorflow:epoch = 80.0, learning_rate = 0.00049999997, loss = 0.0011845097, step = 1760 (13.873 sec)
2021-11-27 21:34:44,721 [INFO] tensorflow: epoch = 80.0, learning_rate = 0.00049999997, loss = 0.0011845097, step = 1760 (13.873 sec)
INFO:tensorflow:global_step/sec: 0.220905
2021-11-27 21:34:44,723 [INFO] tensorflow: global_step/sec: 0.220905
2021-11-27 21:34:44,724 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 80/120: loss: 0.00118 learning rate: 0.00050 Time taken: 0:00:10.425916 ETA: 0:06:57.036638
INFO:tensorflow:global_step/sec: 14.2907
2021-11-27 21:34:44,863 [INFO] tensorflow: global_step/sec: 14.2907
INFO:tensorflow:global_step/sec: 14.0531
2021-11-27 21:34:45,005 [INFO] tensorflow: global_step/sec: 14.0531
INFO:tensorflow:global_step/sec: 14.8085
2021-11-27 21:34:45,140 [INFO] tensorflow: global_step/sec: 14.8085
INFO:tensorflow:global_step/sec: 14.7211
2021-11-27 21:34:45,276 [INFO] tensorflow: global_step/sec: 14.7211
INFO:tensorflow:global_step/sec: 14.6629
2021-11-27 21:34:45,412 [INFO] tensorflow: global_step/sec: 14.6629
INFO:tensorflow:global_step/sec: 14.6983
2021-11-27 21:34:45,548 [INFO] tensorflow: global_step/sec: 14.6983
INFO:tensorflow:global_step/sec: 15.3822
2021-11-27 21:34:45,678 [INFO] tensorflow: global_step/sec: 15.3822
2021-11-27 21:34:45,679 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 9.411
INFO:tensorflow:global_step/sec: 14.8743
2021-11-27 21:34:45,813 [INFO] tensorflow: global_step/sec: 14.8743
INFO:tensorflow:global_step/sec: 14.7434
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INFO:tensorflow:global_step/sec: 14.5496
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INFO:tensorflow:global_step/sec: 13.3026
2021-11-27 21:34:46,236 [INFO] tensorflow: global_step/sec: 13.3026
2021-11-27 21:34:46,238 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 81/120: loss: 0.00114 learning rate: 0.00050 Time taken: 0:00:01.513497 ETA: 0:00:59.026397
INFO:tensorflow:global_step/sec: 14.3686
2021-11-27 21:34:46,376 [INFO] tensorflow: global_step/sec: 14.3686
INFO:tensorflow:global_step/sec: 14.3921
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INFO:tensorflow:global_step/sec: 14.979
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INFO:tensorflow:global_step/sec: 14.5853
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INFO:tensorflow:global_step/sec: 14.4833
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INFO:tensorflow:global_step/sec: 14.4501
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INFO:tensorflow:global_step/sec: 14.9246
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INFO:tensorflow:global_step/sec: 14.2703
2021-11-27 21:34:47,336 [INFO] tensorflow: global_step/sec: 14.2703
2021-11-27 21:34:47,405 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.979
INFO:tensorflow:global_step/sec: 14.1464
2021-11-27 21:34:47,477 [INFO] tensorflow: global_step/sec: 14.1464
INFO:tensorflow:global_step/sec: 15.0662
2021-11-27 21:34:47,610 [INFO] tensorflow: global_step/sec: 15.0662
INFO:tensorflow:global_step/sec: 13.8454
2021-11-27 21:34:47,754 [INFO] tensorflow: global_step/sec: 13.8454
2021-11-27 21:34:47,755 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 82/120: loss: 0.00141 learning rate: 0.00050 Time taken: 0:00:01.518401 ETA: 0:00:57.699225
INFO:tensorflow:global_step/sec: 14.2523
2021-11-27 21:34:47,895 [INFO] tensorflow: global_step/sec: 14.2523
INFO:tensorflow:global_step/sec: 15.1105
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INFO:tensorflow:global_step/sec: 14.7304
2021-11-27 21:34:49,116 [INFO] tensorflow: global_step/sec: 14.7304
2021-11-27 21:34:49,116 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.430
INFO:tensorflow:global_step/sec: 13.1519
2021-11-27 21:34:49,268 [INFO] tensorflow: global_step/sec: 13.1519
2021-11-27 21:34:49,269 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 83/120: loss: 0.00171 learning rate: 0.00050 Time taken: 0:00:01.513774 ETA: 0:00:56.009653
INFO:tensorflow:global_step/sec: 14.3226
2021-11-27 21:34:49,408 [INFO] tensorflow: global_step/sec: 14.3226
INFO:tensorflow:global_step/sec: 14.8665
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INFO:tensorflow:global_step/sec: 14.5181
2021-11-27 21:34:49,680 [INFO] tensorflow: global_step/sec: 14.5181
INFO:tensorflow:epoch = 83.36363636363636, learning_rate = 0.00049999997, loss = 0.0014218773, step = 1834 (5.094 sec)
2021-11-27 21:34:49,815 [INFO] tensorflow: epoch = 83.36363636363636, learning_rate = 0.00049999997, loss = 0.0014218773, step = 1834 (5.094 sec)
INFO:tensorflow:global_step/sec: 14.6294
2021-11-27 21:34:49,817 [INFO] tensorflow: global_step/sec: 14.6294
INFO:tensorflow:global_step/sec: 14.379
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INFO:tensorflow:global_step/sec: 15.2834
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INFO:tensorflow:global_step/sec: 13.7457
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INFO:tensorflow:global_step/sec: 14.677
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2021-11-27 21:34:50,796 [INFO] tensorflow: global_step/sec: 13.7561
2021-11-27 21:34:50,798 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 84/120: loss: 0.00156 learning rate: 0.00050 Time taken: 0:00:01.524529 ETA: 0:00:54.883026
2021-11-27 21:34:50,863 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.268
INFO:tensorflow:global_step/sec: 14.2628
2021-11-27 21:34:50,937 [INFO] tensorflow: global_step/sec: 14.2628
INFO:tensorflow:global_step/sec: 14.663
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INFO:tensorflow:global_step/sec: 14.3061
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INFO:tensorflow:global_step/sec: 15.0433
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INFO:tensorflow:global_step/sec: 14.5132
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INFO:tensorflow:global_step/sec: 14.5113
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INFO:tensorflow:global_step/sec: 13.8281
2021-11-27 21:34:52,309 [INFO] tensorflow: global_step/sec: 13.8281
2021-11-27 21:34:52,310 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 85/120: loss: 0.00105 learning rate: 0.00044 Time taken: 0:00:01.513268 ETA: 0:00:52.964396
INFO:tensorflow:global_step/sec: 15.1926
2021-11-27 21:34:52,441 [INFO] tensorflow: global_step/sec: 15.1926
INFO:tensorflow:global_step/sec: 14.6098
2021-11-27 21:34:52,578 [INFO] tensorflow: global_step/sec: 14.6098
2021-11-27 21:34:52,578 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.308
INFO:tensorflow:global_step/sec: 14.4815
2021-11-27 21:34:52,716 [INFO] tensorflow: global_step/sec: 14.4815
INFO:tensorflow:global_step/sec: 14.1837
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INFO:tensorflow:global_step/sec: 15.2271
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INFO:tensorflow:global_step/sec: 14.6873
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INFO:tensorflow:global_step/sec: 13.6832
2021-11-27 21:34:53,816 [INFO] tensorflow: global_step/sec: 13.6832
2021-11-27 21:34:53,817 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 86/120: loss: 0.00135 learning rate: 0.00039 Time taken: 0:00:01.503986 ETA: 0:00:51.135512
INFO:tensorflow:global_step/sec: 13.9949
2021-11-27 21:34:53,959 [INFO] tensorflow: global_step/sec: 13.9949
INFO:tensorflow:global_step/sec: 14.6031
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2021-11-27 21:34:54,227 [INFO] tensorflow: global_step/sec: 15.2417
2021-11-27 21:34:54,295 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.279
INFO:tensorflow:global_step/sec: 14.8025
2021-11-27 21:34:54,362 [INFO] tensorflow: global_step/sec: 14.8025
INFO:tensorflow:global_step/sec: 14.5147
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INFO:tensorflow:global_step/sec: 14.8458
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INFO:tensorflow:global_step/sec: 14.0443
2021-11-27 21:34:54,777 [INFO] tensorflow: global_step/sec: 14.0443
INFO:tensorflow:epoch = 86.72727272727273, learning_rate = 0.00035274026, loss = 0.0015209467, step = 1908 (5.102 sec)
2021-11-27 21:34:54,918 [INFO] tensorflow: epoch = 86.72727272727273, learning_rate = 0.00035274026, loss = 0.0015209467, step = 1908 (5.102 sec)
INFO:tensorflow:global_step/sec: 14.118
2021-11-27 21:34:54,919 [INFO] tensorflow: global_step/sec: 14.118
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INFO:tensorflow:global_step/sec: 14.113
2021-11-27 21:34:55,334 [INFO] tensorflow: global_step/sec: 14.113
2021-11-27 21:34:55,336 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 87/120: loss: 0.00118 learning rate: 0.00034 Time taken: 0:00:01.517369 ETA: 0:00:50.073178
INFO:tensorflow:global_step/sec: 14.3843
2021-11-27 21:34:55,473 [INFO] tensorflow: global_step/sec: 14.3843
INFO:tensorflow:global_step/sec: 14.3993
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2021-11-27 21:34:56,020 [INFO] tensorflow: global_step/sec: 14.7838
2021-11-27 21:34:56,021 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.935
INFO:tensorflow:global_step/sec: 14.9223
2021-11-27 21:34:56,154 [INFO] tensorflow: global_step/sec: 14.9223
INFO:tensorflow:global_step/sec: 14.0139
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INFO:tensorflow:global_step/sec: 13.6772
2021-11-27 21:34:56,867 [INFO] tensorflow: global_step/sec: 13.6772
2021-11-27 21:34:56,868 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 88/120: loss: 0.00126 learning rate: 0.00030 Time taken: 0:00:01.529029 ETA: 0:00:48.928925
INFO:tensorflow:global_step/sec: 14.526
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INFO:tensorflow:global_step/sec: 15.0615
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INFO:tensorflow:global_step/sec: 14.7487
2021-11-27 21:34:57,678 [INFO] tensorflow: global_step/sec: 14.7487
2021-11-27 21:34:57,745 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.002
INFO:tensorflow:global_step/sec: 14.3573
2021-11-27 21:34:57,817 [INFO] tensorflow: global_step/sec: 14.3573
INFO:tensorflow:global_step/sec: 14.3066
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INFO:tensorflow:global_step/sec: 14.4128
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INFO:tensorflow:global_step/sec: 14.5603
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INFO:tensorflow:global_step/sec: 14.186
2021-11-27 21:34:58,374 [INFO] tensorflow: global_step/sec: 14.186
2021-11-27 21:34:58,375 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 89/120: loss: 0.00119 learning rate: 0.00026 Time taken: 0:00:01.506305 ETA: 0:00:46.695454
INFO:tensorflow:global_step/sec: 14.9008
2021-11-27 21:34:58,508 [INFO] tensorflow: global_step/sec: 14.9008
INFO:tensorflow:global_step/sec: 14.5099
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INFO:tensorflow:global_step/sec: 14.4632
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INFO:tensorflow:global_step/sec: 14.4054
2021-11-27 21:34:59,482 [INFO] tensorflow: global_step/sec: 14.4054
2021-11-27 21:34:59,483 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.577
INFO:tensorflow:global_step/sec: 14.6121
2021-11-27 21:34:59,619 [INFO] tensorflow: global_step/sec: 14.6121
INFO:tensorflow:global_step/sec: 15.0874
2021-11-27 21:34:59,751 [INFO] tensorflow: global_step/sec: 15.0874
INFO:tensorflow:Saving checkpoints for step-1980.
2021-11-27 21:34:59,817 [INFO] tensorflow: Saving checkpoints for step-1980.
WARNING:tensorflow:Ignoring: /tmp/tmp3pkl2y1h; No such file or directory
2021-11-27 21:34:59,912 [WARNING] tensorflow: Ignoring: /tmp/tmp3pkl2y1h; No such file or directory
2021-11-27 21:35:02,234 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 1647/1647 [00:00<00:00, 24082.34it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 5875/5875 [00:00<00:00, 27444.22it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 763/763 [00:00<00:00, 24181.70it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 11353/11353 [00:00<00:00, 31859.56it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 841/841 [00:00<00:00, 25584.48it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 1649/1649 [00:00<00:00, 24725.47it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 9459/9459 [00:00<00:00, 46659.50it/s]
Epoch 90/120
=========================
Validation cost: 0.000776
Mean average_precision (in %): 13.8909
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 12.5771
floor 0
palette 0.441823
pillar 29.1041
pushcart 0
rackframe 21.7961
rackshelf 37.7476
wall 23.3511
Median Inference Time: 0.008147
INFO:tensorflow:epoch = 90.0, learning_rate = 0.00023207937, loss = 0.0013222524, step = 1980 (13.464 sec)
2021-11-27 21:35:08,382 [INFO] tensorflow: epoch = 90.0, learning_rate = 0.00023207937, loss = 0.0013222524, step = 1980 (13.464 sec)
INFO:tensorflow:global_step/sec: 0.231708
2021-11-27 21:35:08,383 [INFO] tensorflow: global_step/sec: 0.231708
2021-11-27 21:35:08,384 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 90/120: loss: 0.00132 learning rate: 0.00023 Time taken: 0:00:10.008223 ETA: 0:05:00.246699
INFO:tensorflow:global_step/sec: 14.7286
2021-11-27 21:35:08,519 [INFO] tensorflow: global_step/sec: 14.7286
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INFO:tensorflow:global_step/sec: 14.9078
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2021-11-27 21:35:09,682 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 9.805
INFO:tensorflow:global_step/sec: 13.7895
2021-11-27 21:35:09,750 [INFO] tensorflow: global_step/sec: 13.7895
INFO:tensorflow:global_step/sec: 14.0646
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2021-11-27 21:35:09,892 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 91/120: loss: 0.00137 learning rate: 0.00020 Time taken: 0:00:01.505357 ETA: 0:00:43.655340
INFO:tensorflow:global_step/sec: 13.7243
2021-11-27 21:35:10,038 [INFO] tensorflow: global_step/sec: 13.7243
INFO:tensorflow:global_step/sec: 14.1102
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INFO:tensorflow:global_step/sec: 13.8577
2021-11-27 21:35:11,426 [INFO] tensorflow: global_step/sec: 13.8577
2021-11-27 21:35:11,427 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 92/120: loss: 0.00125 learning rate: 0.00018 Time taken: 0:00:01.534882 ETA: 0:00:42.976698
2021-11-27 21:35:11,427 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.297
INFO:tensorflow:global_step/sec: 14.1337
2021-11-27 21:35:11,568 [INFO] tensorflow: global_step/sec: 14.1337
INFO:tensorflow:global_step/sec: 14.4379
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INFO:tensorflow:global_step/sec: 14.961
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INFO:tensorflow:global_step/sec: 14.8857
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INFO:tensorflow:global_step/sec: 13.7024
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INFO:tensorflow:global_step/sec: 14.0539
2021-11-27 21:35:12,955 [INFO] tensorflow: global_step/sec: 14.0539
2021-11-27 21:35:12,956 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 93/120: loss: 0.00135 learning rate: 0.00016 Time taken: 0:00:01.524205 ETA: 0:00:41.153541
INFO:tensorflow:global_step/sec: 14.6214
2021-11-27 21:35:13,092 [INFO] tensorflow: global_step/sec: 14.6214
2021-11-27 21:35:13,157 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.841
INFO:tensorflow:global_step/sec: 14.991
2021-11-27 21:35:13,225 [INFO] tensorflow: global_step/sec: 14.991
INFO:tensorflow:global_step/sec: 15.045
2021-11-27 21:35:13,358 [INFO] tensorflow: global_step/sec: 15.045
INFO:tensorflow:epoch = 93.36363636363636, learning_rate = 0.00015092737, loss = 0.0013996409, step = 2054 (5.109 sec)
2021-11-27 21:35:13,491 [INFO] tensorflow: epoch = 93.36363636363636, learning_rate = 0.00015092737, loss = 0.0013996409, step = 2054 (5.109 sec)
INFO:tensorflow:global_step/sec: 14.8748
2021-11-27 21:35:13,492 [INFO] tensorflow: global_step/sec: 14.8748
INFO:tensorflow:global_step/sec: 15.429
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INFO:tensorflow:global_step/sec: 15.2951
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INFO:tensorflow:global_step/sec: 13.9578
2021-11-27 21:35:14,440 [INFO] tensorflow: global_step/sec: 13.9578
2021-11-27 21:35:14,441 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 94/120: loss: 0.00135 learning rate: 0.00014 Time taken: 0:00:01.479801 ETA: 0:00:38.474837
INFO:tensorflow:global_step/sec: 14.8581
2021-11-27 21:35:14,575 [INFO] tensorflow: global_step/sec: 14.8581
INFO:tensorflow:global_step/sec: 14.3782
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INFO:tensorflow:global_step/sec: 15.0407
2021-11-27 21:35:14,847 [INFO] tensorflow: global_step/sec: 15.0407
2021-11-27 21:35:14,848 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.153
INFO:tensorflow:global_step/sec: 14.9827
2021-11-27 21:35:14,980 [INFO] tensorflow: global_step/sec: 14.9827
INFO:tensorflow:global_step/sec: 14.7556
2021-11-27 21:35:15,116 [INFO] tensorflow: global_step/sec: 14.7556
INFO:tensorflow:global_step/sec: 15.1277
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INFO:tensorflow:global_step/sec: 14.8112
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INFO:tensorflow:global_step/sec: 15.1719
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INFO:tensorflow:global_step/sec: 14.2263
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INFO:tensorflow:global_step/sec: 14.8977
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INFO:tensorflow:global_step/sec: 13.9151
2021-11-27 21:35:15,933 [INFO] tensorflow: global_step/sec: 13.9151
2021-11-27 21:35:15,934 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 95/120: loss: 0.00113 learning rate: 0.00012 Time taken: 0:00:01.496423 ETA: 0:00:37.410563
INFO:tensorflow:global_step/sec: 14.3405
2021-11-27 21:35:16,073 [INFO] tensorflow: global_step/sec: 14.3405
INFO:tensorflow:global_step/sec: 14.9439
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INFO:tensorflow:global_step/sec: 14.7437
2021-11-27 21:35:16,475 [INFO] tensorflow: global_step/sec: 14.7437
2021-11-27 21:35:16,540 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.093
INFO:tensorflow:global_step/sec: 14.5183
2021-11-27 21:35:16,613 [INFO] tensorflow: global_step/sec: 14.5183
INFO:tensorflow:global_step/sec: 14.6761
2021-11-27 21:35:16,749 [INFO] tensorflow: global_step/sec: 14.6761
INFO:tensorflow:global_step/sec: 14.2031
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2021-11-27 21:35:17,023 [INFO] tensorflow: global_step/sec: 15.091
INFO:tensorflow:global_step/sec: 14.4802
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INFO:tensorflow:global_step/sec: 14.8266
2021-11-27 21:35:17,296 [INFO] tensorflow: global_step/sec: 14.8266
INFO:tensorflow:global_step/sec: 13.8621
2021-11-27 21:35:17,440 [INFO] tensorflow: global_step/sec: 13.8621
2021-11-27 21:35:17,441 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 96/120: loss: 0.00121 learning rate: 0.00011 Time taken: 0:00:01.506193 ETA: 0:00:36.148630
INFO:tensorflow:global_step/sec: 14.4166
2021-11-27 21:35:17,579 [INFO] tensorflow: global_step/sec: 14.4166
INFO:tensorflow:global_step/sec: 14.8186
2021-11-27 21:35:17,714 [INFO] tensorflow: global_step/sec: 14.8186
INFO:tensorflow:global_step/sec: 14.0358
2021-11-27 21:35:17,856 [INFO] tensorflow: global_step/sec: 14.0358
INFO:tensorflow:global_step/sec: 14.5551
2021-11-27 21:35:17,994 [INFO] tensorflow: global_step/sec: 14.5551
INFO:tensorflow:global_step/sec: 14.868
2021-11-27 21:35:18,128 [INFO] tensorflow: global_step/sec: 14.868
INFO:tensorflow:global_step/sec: 14.9172
2021-11-27 21:35:18,262 [INFO] tensorflow: global_step/sec: 14.9172
2021-11-27 21:35:18,263 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.060
INFO:tensorflow:global_step/sec: 14.5207
2021-11-27 21:35:18,400 [INFO] tensorflow: global_step/sec: 14.5207
INFO:tensorflow:global_step/sec: 14.3903
2021-11-27 21:35:18,539 [INFO] tensorflow: global_step/sec: 14.3903
INFO:tensorflow:epoch = 96.77272727272728, learning_rate = 9.7583026e-05, loss = 0.0013394309, step = 2129 (5.117 sec)
2021-11-27 21:35:18,609 [INFO] tensorflow: epoch = 96.77272727272728, learning_rate = 9.7583026e-05, loss = 0.0013394309, step = 2129 (5.117 sec)
INFO:tensorflow:global_step/sec: 14.5563
2021-11-27 21:35:18,676 [INFO] tensorflow: global_step/sec: 14.5563
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2021-11-27 21:35:18,954 [INFO] tensorflow: global_step/sec: 14.0031
2021-11-27 21:35:18,956 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 97/120: loss: 0.00141 learning rate: 0.00009 Time taken: 0:00:01.512452 ETA: 0:00:34.786388
INFO:tensorflow:global_step/sec: 14.9382
2021-11-27 21:35:19,088 [INFO] tensorflow: global_step/sec: 14.9382
INFO:tensorflow:global_step/sec: 15.3043
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INFO:tensorflow:global_step/sec: 14.5213
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INFO:tensorflow:global_step/sec: 13.9693
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INFO:tensorflow:global_step/sec: 14.5096
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INFO:tensorflow:global_step/sec: 14.6345
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INFO:tensorflow:global_step/sec: 14.7515
2021-11-27 21:35:19,910 [INFO] tensorflow: global_step/sec: 14.7515
2021-11-27 21:35:19,978 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.330
INFO:tensorflow:global_step/sec: 14.5179
2021-11-27 21:35:20,048 [INFO] tensorflow: global_step/sec: 14.5179
INFO:tensorflow:global_step/sec: 14.4686
2021-11-27 21:35:20,186 [INFO] tensorflow: global_step/sec: 14.4686
INFO:tensorflow:global_step/sec: 13.6545
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INFO:tensorflow:global_step/sec: 13.7842
2021-11-27 21:35:20,478 [INFO] tensorflow: global_step/sec: 13.7842
2021-11-27 21:35:20,479 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 98/120: loss: 0.00117 learning rate: 0.00008 Time taken: 0:00:01.519034 ETA: 0:00:33.418756
INFO:tensorflow:global_step/sec: 14.7348
2021-11-27 21:35:20,613 [INFO] tensorflow: global_step/sec: 14.7348
INFO:tensorflow:global_step/sec: 13.7975
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INFO:tensorflow:global_step/sec: 14.1297
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INFO:tensorflow:global_step/sec: 14.7217
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INFO:tensorflow:global_step/sec: 14.2836
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INFO:tensorflow:global_step/sec: 14.0326
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INFO:tensorflow:global_step/sec: 14.2434
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INFO:tensorflow:global_step/sec: 14.3313
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INFO:tensorflow:global_step/sec: 14.5912
2021-11-27 21:35:21,735 [INFO] tensorflow: global_step/sec: 14.5912
2021-11-27 21:35:21,736 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 56.877
INFO:tensorflow:global_step/sec: 15.0834
2021-11-27 21:35:21,868 [INFO] tensorflow: global_step/sec: 15.0834
INFO:tensorflow:global_step/sec: 13.3732
2021-11-27 21:35:22,017 [INFO] tensorflow: global_step/sec: 13.3732
2021-11-27 21:35:22,018 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 99/120: loss: 0.00128 learning rate: 0.00007 Time taken: 0:00:01.537152 ETA: 0:00:32.280188
INFO:tensorflow:global_step/sec: 14.1282
2021-11-27 21:35:22,159 [INFO] tensorflow: global_step/sec: 14.1282
INFO:tensorflow:global_step/sec: 13.4403
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INFO:tensorflow:global_step/sec: 14.0766
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INFO:tensorflow:global_step/sec: 14.4103
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INFO:tensorflow:global_step/sec: 14.6719
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INFO:tensorflow:global_step/sec: 14.4152
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INFO:tensorflow:global_step/sec: 15.1272
2021-11-27 21:35:22,996 [INFO] tensorflow: global_step/sec: 15.1272
INFO:tensorflow:global_step/sec: 14.5333
2021-11-27 21:35:23,133 [INFO] tensorflow: global_step/sec: 14.5333
INFO:tensorflow:global_step/sec: 14.3483
2021-11-27 21:35:23,273 [INFO] tensorflow: global_step/sec: 14.3483
INFO:tensorflow:global_step/sec: 14.3102
2021-11-27 21:35:23,413 [INFO] tensorflow: global_step/sec: 14.3102
INFO:tensorflow:Saving checkpoints for step-2200.
2021-11-27 21:35:23,480 [INFO] tensorflow: Saving checkpoints for step-2200.
WARNING:tensorflow:Ignoring: /tmp/tmp8a1h3_i_; No such file or directory
2021-11-27 21:35:23,575 [WARNING] tensorflow: Ignoring: /tmp/tmp8a1h3_i_; No such file or directory
2021-11-27 21:35:25,910 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 1822/1822 [00:00<00:00, 22950.88it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 5876/5876 [00:00<00:00, 27574.04it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 806/806 [00:00<00:00, 24645.58it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 11124/11124 [00:00<00:00, 30912.46it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 799/799 [00:00<00:00, 23863.01it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 1690/1690 [00:00<00:00, 23003.97it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 9019/9019 [00:00<00:00, 39716.72it/s]
Epoch 100/120
=========================
Validation cost: 0.000779
Mean average_precision (in %): 14.6698
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 21.653
floor 0
palette 0.330446
pillar 20.8337
pushcart 0
rackframe 26.1576
rackshelf 38.0292
wall 25.0239
Median Inference Time: 0.007951
2021-11-27 21:35:32,175 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 9.580
INFO:tensorflow:epoch = 100.0, learning_rate = 6.457747e-05, loss = 0.0013396268, step = 2200 (13.636 sec)
2021-11-27 21:35:32,244 [INFO] tensorflow: epoch = 100.0, learning_rate = 6.457747e-05, loss = 0.0013396268, step = 2200 (13.636 sec)
INFO:tensorflow:global_step/sec: 0.226428
2021-11-27 21:35:32,245 [INFO] tensorflow: global_step/sec: 0.226428
2021-11-27 21:35:32,247 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 100/120: loss: 0.00134 learning rate: 0.00006 Time taken: 0:00:10.228996 ETA: 0:03:24.579926
INFO:tensorflow:global_step/sec: 13.6637
2021-11-27 21:35:32,392 [INFO] tensorflow: global_step/sec: 13.6637
INFO:tensorflow:global_step/sec: 14.6139
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INFO:tensorflow:global_step/sec: 14.3413
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INFO:tensorflow:global_step/sec: 14.6871
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INFO:tensorflow:global_step/sec: 14.1301
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INFO:tensorflow:global_step/sec: 14.109
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INFO:tensorflow:global_step/sec: 15.0507
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INFO:tensorflow:global_step/sec: 14.0124
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INFO:tensorflow:global_step/sec: 14.6492
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INFO:tensorflow:global_step/sec: 14.0557
2021-11-27 21:35:33,779 [INFO] tensorflow: global_step/sec: 14.0557
2021-11-27 21:35:33,781 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 101/120: loss: 0.00114 learning rate: 0.00006 Time taken: 0:00:01.532828 ETA: 0:00:29.123729
INFO:tensorflow:global_step/sec: 13.9943
2021-11-27 21:35:33,922 [INFO] tensorflow: global_step/sec: 13.9943
2021-11-27 21:35:33,923 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.268
INFO:tensorflow:global_step/sec: 14.3667
2021-11-27 21:35:34,061 [INFO] tensorflow: global_step/sec: 14.3667
INFO:tensorflow:global_step/sec: 14.418
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INFO:tensorflow:global_step/sec: 15.0591
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INFO:tensorflow:global_step/sec: 15.318
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INFO:tensorflow:global_step/sec: 15.2168
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INFO:tensorflow:global_step/sec: 14.9169
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INFO:tensorflow:global_step/sec: 14.4049
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INFO:tensorflow:global_step/sec: 13.916
2021-11-27 21:35:35,284 [INFO] tensorflow: global_step/sec: 13.916
2021-11-27 21:35:35,285 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 102/120: loss: 0.00132 learning rate: 0.00005 Time taken: 0:00:01.499300 ETA: 0:00:26.987391
INFO:tensorflow:global_step/sec: 14.2846
2021-11-27 21:35:35,424 [INFO] tensorflow: global_step/sec: 14.2846
INFO:tensorflow:global_step/sec: 14.8159
2021-11-27 21:35:35,559 [INFO] tensorflow: global_step/sec: 14.8159
2021-11-27 21:35:35,629 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.616
INFO:tensorflow:global_step/sec: 14.0791
2021-11-27 21:35:35,701 [INFO] tensorflow: global_step/sec: 14.0791
INFO:tensorflow:global_step/sec: 14.041
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INFO:tensorflow:global_step/sec: 14.8507
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INFO:tensorflow:global_step/sec: 15.1198
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INFO:tensorflow:global_step/sec: 14.5406
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INFO:tensorflow:global_step/sec: 15.185
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INFO:tensorflow:global_step/sec: 14.9202
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INFO:tensorflow:global_step/sec: 13.2881
2021-11-27 21:35:36,800 [INFO] tensorflow: global_step/sec: 13.2881
2021-11-27 21:35:36,801 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 103/120: loss: 0.00107 learning rate: 0.00004 Time taken: 0:00:01.515983 ETA: 0:00:25.771705
INFO:tensorflow:global_step/sec: 14.3614
2021-11-27 21:35:36,939 [INFO] tensorflow: global_step/sec: 14.3614
INFO:tensorflow:global_step/sec: 14.68
2021-11-27 21:35:37,075 [INFO] tensorflow: global_step/sec: 14.68
INFO:tensorflow:global_step/sec: 14.847
2021-11-27 21:35:37,210 [INFO] tensorflow: global_step/sec: 14.847
INFO:tensorflow:epoch = 103.36363636363636, learning_rate = 4.199648e-05, loss = 0.0011573608, step = 2274 (5.101 sec)
2021-11-27 21:35:37,345 [INFO] tensorflow: epoch = 103.36363636363636, learning_rate = 4.199648e-05, loss = 0.0011573608, step = 2274 (5.101 sec)
INFO:tensorflow:global_step/sec: 14.7002
2021-11-27 21:35:37,346 [INFO] tensorflow: global_step/sec: 14.7002
2021-11-27 21:35:37,347 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.240
INFO:tensorflow:global_step/sec: 14.6742
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INFO:tensorflow:global_step/sec: 14.9433
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2021-11-27 21:35:38,307 [INFO] tensorflow: global_step/sec: 14.2234
2021-11-27 21:35:38,308 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 104/120: loss: 0.00120 learning rate: 0.00004 Time taken: 0:00:01.509660 ETA: 0:00:24.154564
INFO:tensorflow:global_step/sec: 14.7124
2021-11-27 21:35:38,443 [INFO] tensorflow: global_step/sec: 14.7124
INFO:tensorflow:global_step/sec: 14.3736
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2021-11-27 21:35:38,992 [INFO] tensorflow: global_step/sec: 14.5671
2021-11-27 21:35:39,059 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.434
INFO:tensorflow:global_step/sec: 14.6847
2021-11-27 21:35:39,128 [INFO] tensorflow: global_step/sec: 14.6847
INFO:tensorflow:global_step/sec: 14.7299
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INFO:tensorflow:global_step/sec: 14.7238
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INFO:tensorflow:global_step/sec: 14.4188
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INFO:tensorflow:global_step/sec: 15.2661
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2021-11-27 21:35:39,809 [INFO] tensorflow: global_step/sec: 14.3406
2021-11-27 21:35:39,810 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 105/120: loss: 0.00117 learning rate: 0.00003 Time taken: 0:00:01.497093 ETA: 0:00:22.456398
INFO:tensorflow:global_step/sec: 14.3046
2021-11-27 21:35:39,949 [INFO] tensorflow: global_step/sec: 14.3046
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INFO:tensorflow:global_step/sec: 12.8602
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INFO:tensorflow:global_step/sec: 14.6077
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2021-11-27 21:35:40,795 [INFO] tensorflow: global_step/sec: 14.6743
2021-11-27 21:35:40,796 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.588
INFO:tensorflow:global_step/sec: 14.1359
2021-11-27 21:35:40,936 [INFO] tensorflow: global_step/sec: 14.1359
INFO:tensorflow:global_step/sec: 14.4868
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INFO:tensorflow:global_step/sec: 13.1142
2021-11-27 21:35:41,367 [INFO] tensorflow: global_step/sec: 13.1142
2021-11-27 21:35:41,368 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 106/120: loss: 0.00113 learning rate: 0.00003 Time taken: 0:00:01.550979 ETA: 0:00:21.713708
INFO:tensorflow:global_step/sec: 14.7387
2021-11-27 21:35:41,503 [INFO] tensorflow: global_step/sec: 14.7387
INFO:tensorflow:global_step/sec: 14.5735
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INFO:tensorflow:global_step/sec: 14.4609
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INFO:tensorflow:global_step/sec: 15.0615
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INFO:tensorflow:global_step/sec: 14.6288
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INFO:tensorflow:global_step/sec: 15.0564
2021-11-27 21:35:42,181 [INFO] tensorflow: global_step/sec: 15.0564
INFO:tensorflow:global_step/sec: 14.7608
2021-11-27 21:35:42,316 [INFO] tensorflow: global_step/sec: 14.7608
INFO:tensorflow:epoch = 106.72727272727273, learning_rate = 2.7311375e-05, loss = 0.0011277084, step = 2348 (5.107 sec)
2021-11-27 21:35:42,452 [INFO] tensorflow: epoch = 106.72727272727273, learning_rate = 2.7311375e-05, loss = 0.0011277084, step = 2348 (5.107 sec)
INFO:tensorflow:global_step/sec: 14.6291
2021-11-27 21:35:42,453 [INFO] tensorflow: global_step/sec: 14.6291
2021-11-27 21:35:42,527 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.776
INFO:tensorflow:global_step/sec: 14.0281
2021-11-27 21:35:42,595 [INFO] tensorflow: global_step/sec: 14.0281
INFO:tensorflow:global_step/sec: 15.2541
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INFO:tensorflow:global_step/sec: 13.6049
2021-11-27 21:35:42,874 [INFO] tensorflow: global_step/sec: 13.6049
2021-11-27 21:35:42,875 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 107/120: loss: 0.00121 learning rate: 0.00003 Time taken: 0:00:01.508691 ETA: 0:00:19.612987
INFO:tensorflow:global_step/sec: 14.4248
2021-11-27 21:35:43,012 [INFO] tensorflow: global_step/sec: 14.4248
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INFO:tensorflow:global_step/sec: 14.3164
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INFO:tensorflow:global_step/sec: 14.6862
2021-11-27 21:35:44,245 [INFO] tensorflow: global_step/sec: 14.6862
2021-11-27 21:35:44,246 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.168
INFO:tensorflow:global_step/sec: 13.7198
2021-11-27 21:35:44,391 [INFO] tensorflow: global_step/sec: 13.7198
2021-11-27 21:35:44,392 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 108/120: loss: 0.00130 learning rate: 0.00002 Time taken: 0:00:01.517764 ETA: 0:00:18.213169
INFO:tensorflow:global_step/sec: 14.5431
2021-11-27 21:35:44,528 [INFO] tensorflow: global_step/sec: 14.5431
INFO:tensorflow:global_step/sec: 15.0616
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INFO:tensorflow:global_step/sec: 14.5943
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INFO:tensorflow:global_step/sec: 14.2082
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INFO:tensorflow:global_step/sec: 14.8151
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INFO:tensorflow:global_step/sec: 14.045
2021-11-27 21:35:45,899 [INFO] tensorflow: global_step/sec: 14.045
2021-11-27 21:35:45,901 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 109/120: loss: 0.00124 learning rate: 0.00002 Time taken: 0:00:01.505586 ETA: 0:00:16.561448
2021-11-27 21:35:45,966 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.176
INFO:tensorflow:global_step/sec: 14.3847
2021-11-27 21:35:46,038 [INFO] tensorflow: global_step/sec: 14.3847
INFO:tensorflow:global_step/sec: 13.7534
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INFO:tensorflow:global_step/sec: 14.4915
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INFO:tensorflow:global_step/sec: 13.9169
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INFO:tensorflow:global_step/sec: 15.2077
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INFO:tensorflow:global_step/sec: 14.4556
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INFO:tensorflow:global_step/sec: 14.8107
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INFO:tensorflow:global_step/sec: 14.3055
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INFO:tensorflow:global_step/sec: 14.1957
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INFO:tensorflow:global_step/sec: 14.3315
2021-11-27 21:35:47,291 [INFO] tensorflow: global_step/sec: 14.3315
INFO:tensorflow:Saving checkpoints for step-2420.
2021-11-27 21:35:47,360 [INFO] tensorflow: Saving checkpoints for step-2420.
WARNING:tensorflow:Ignoring: /tmp/tmpz90rnvlh; No such file or directory
2021-11-27 21:35:47,457 [WARNING] tensorflow: Ignoring: /tmp/tmpz90rnvlh; No such file or directory
2021-11-27 21:35:49,844 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 1760/1760 [00:00<00:00, 24874.90it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 5767/5767 [00:00<00:00, 26724.34it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 817/817 [00:00<00:00, 23928.62it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 10932/10932 [00:00<00:00, 30652.30it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 860/860 [00:00<00:00, 23725.62it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 1724/1724 [00:00<00:00, 22774.88it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 8834/8834 [00:00<00:00, 40835.35it/s]
Epoch 110/120
=========================
Validation cost: 0.000783
Mean average_precision (in %): 15.8793
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 18.5792
floor 0
palette 0.665045
pillar 24.7584
pushcart 0
rackframe 27.9509
rackshelf 45.0106
wall 25.9497
Median Inference Time: 0.007589
INFO:tensorflow:epoch = 110.0, learning_rate = 1.7969083e-05, loss = 0.0011130697, step = 2420 (13.516 sec)
2021-11-27 21:35:55,968 [INFO] tensorflow: epoch = 110.0, learning_rate = 1.7969083e-05, loss = 0.0011130697, step = 2420 (13.516 sec)
INFO:tensorflow:global_step/sec: 0.230465
2021-11-27 21:35:55,969 [INFO] tensorflow: global_step/sec: 0.230465
2021-11-27 21:35:55,970 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 110/120: loss: 0.00111 learning rate: 0.00002 Time taken: 0:00:10.068641 ETA: 0:01:40.686409
INFO:tensorflow:global_step/sec: 14.0386
2021-11-27 21:35:56,111 [INFO] tensorflow: global_step/sec: 14.0386
INFO:tensorflow:global_step/sec: 14.6238
2021-11-27 21:35:56,248 [INFO] tensorflow: global_step/sec: 14.6238
2021-11-27 21:35:56,249 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 9.725
INFO:tensorflow:global_step/sec: 14.9234
2021-11-27 21:35:56,382 [INFO] tensorflow: global_step/sec: 14.9234
INFO:tensorflow:global_step/sec: 15.0584
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2021-11-27 21:35:57,480 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 111/120: loss: 0.00134 learning rate: 0.00002 Time taken: 0:00:01.508971 ETA: 0:00:13.580737
INFO:tensorflow:global_step/sec: 13.8962
2021-11-27 21:35:57,623 [INFO] tensorflow: global_step/sec: 13.8962
INFO:tensorflow:global_step/sec: 15.2558
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INFO:tensorflow:global_step/sec: 14.4751
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2021-11-27 21:35:57,961 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.426
INFO:tensorflow:global_step/sec: 14.7563
2021-11-27 21:35:58,027 [INFO] tensorflow: global_step/sec: 14.7563
INFO:tensorflow:global_step/sec: 14.4116
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INFO:tensorflow:global_step/sec: 15.0452
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2021-11-27 21:35:58,996 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 112/120: loss: 0.00123 learning rate: 0.00001 Time taken: 0:00:01.513649 ETA: 0:00:12.109188
INFO:tensorflow:global_step/sec: 15.1151
2021-11-27 21:35:59,127 [INFO] tensorflow: global_step/sec: 15.1151
INFO:tensorflow:global_step/sec: 14.6876
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INFO:tensorflow:global_step/sec: 14.772
2021-11-27 21:35:59,679 [INFO] tensorflow: global_step/sec: 14.772
2021-11-27 21:35:59,679 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.208
INFO:tensorflow:global_step/sec: 14.3154
2021-11-27 21:35:59,818 [INFO] tensorflow: global_step/sec: 14.3154
INFO:tensorflow:global_step/sec: 14.9752
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INFO:tensorflow:global_step/sec: 14.2423
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INFO:tensorflow:global_step/sec: 15.0859
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INFO:tensorflow:global_step/sec: 14.384
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INFO:tensorflow:global_step/sec: 13.4957
2021-11-27 21:36:00,512 [INFO] tensorflow: global_step/sec: 13.4957
2021-11-27 21:36:00,513 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 113/120: loss: 0.00116 learning rate: 0.00001 Time taken: 0:00:01.511973 ETA: 0:00:10.583814
INFO:tensorflow:global_step/sec: 14.4038
2021-11-27 21:36:00,651 [INFO] tensorflow: global_step/sec: 14.4038
INFO:tensorflow:global_step/sec: 14.575
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INFO:tensorflow:global_step/sec: 14.5516
2021-11-27 21:36:00,926 [INFO] tensorflow: global_step/sec: 14.5516
INFO:tensorflow:epoch = 113.36363636363636, learning_rate = 1.168576e-05, loss = 0.001296784, step = 2494 (5.100 sec)
2021-11-27 21:36:01,067 [INFO] tensorflow: epoch = 113.36363636363636, learning_rate = 1.168576e-05, loss = 0.001296784, step = 2494 (5.100 sec)
INFO:tensorflow:global_step/sec: 14.0108
2021-11-27 21:36:01,068 [INFO] tensorflow: global_step/sec: 14.0108
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INFO:tensorflow:global_step/sec: 14.5619
2021-11-27 21:36:01,340 [INFO] tensorflow: global_step/sec: 14.5619
2021-11-27 21:36:01,409 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.840
INFO:tensorflow:global_step/sec: 14.1717
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INFO:tensorflow:global_step/sec: 14.1797
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INFO:tensorflow:global_step/sec: 15.052
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INFO:tensorflow:global_step/sec: 14.9264
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INFO:tensorflow:global_step/sec: 13.5556
2021-11-27 21:36:02,036 [INFO] tensorflow: global_step/sec: 13.5556
2021-11-27 21:36:02,038 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 114/120: loss: 0.00119 learning rate: 0.00001 Time taken: 0:00:01.523275 ETA: 0:00:09.139651
INFO:tensorflow:global_step/sec: 14.282
2021-11-27 21:36:02,176 [INFO] tensorflow: global_step/sec: 14.282
INFO:tensorflow:global_step/sec: 14.2101
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2021-11-27 21:36:02,454 [INFO] tensorflow: global_step/sec: 14.6109
INFO:tensorflow:global_step/sec: 14.6366
2021-11-27 21:36:02,590 [INFO] tensorflow: global_step/sec: 14.6366
INFO:tensorflow:global_step/sec: 14.2613
2021-11-27 21:36:02,731 [INFO] tensorflow: global_step/sec: 14.2613
INFO:tensorflow:global_step/sec: 14.6908
2021-11-27 21:36:02,867 [INFO] tensorflow: global_step/sec: 14.6908
INFO:tensorflow:global_step/sec: 14.262
2021-11-27 21:36:03,007 [INFO] tensorflow: global_step/sec: 14.262
INFO:tensorflow:global_step/sec: 14.4426
2021-11-27 21:36:03,146 [INFO] tensorflow: global_step/sec: 14.4426
2021-11-27 21:36:03,146 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.568
INFO:tensorflow:global_step/sec: 14.7975
2021-11-27 21:36:03,281 [INFO] tensorflow: global_step/sec: 14.7975
INFO:tensorflow:global_step/sec: 14.638
2021-11-27 21:36:03,417 [INFO] tensorflow: global_step/sec: 14.638
INFO:tensorflow:global_step/sec: 14.1673
2021-11-27 21:36:03,559 [INFO] tensorflow: global_step/sec: 14.1673
2021-11-27 21:36:03,560 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 115/120: loss: 0.00119 learning rate: 0.00001 Time taken: 0:00:01.521498 ETA: 0:00:07.607490
INFO:tensorflow:global_step/sec: 14.2907
2021-11-27 21:36:03,698 [INFO] tensorflow: global_step/sec: 14.2907
INFO:tensorflow:global_step/sec: 14.6035
2021-11-27 21:36:03,835 [INFO] tensorflow: global_step/sec: 14.6035
INFO:tensorflow:global_step/sec: 14.4161
2021-11-27 21:36:03,974 [INFO] tensorflow: global_step/sec: 14.4161
INFO:tensorflow:global_step/sec: 15.1211
2021-11-27 21:36:04,106 [INFO] tensorflow: global_step/sec: 15.1211
INFO:tensorflow:global_step/sec: 14.6253
2021-11-27 21:36:04,243 [INFO] tensorflow: global_step/sec: 14.6253
INFO:tensorflow:global_step/sec: 14.5254
2021-11-27 21:36:04,381 [INFO] tensorflow: global_step/sec: 14.5254
INFO:tensorflow:global_step/sec: 14.308
2021-11-27 21:36:04,521 [INFO] tensorflow: global_step/sec: 14.308
INFO:tensorflow:global_step/sec: 14.8227
2021-11-27 21:36:04,656 [INFO] tensorflow: global_step/sec: 14.8227
INFO:tensorflow:global_step/sec: 14.3412
2021-11-27 21:36:04,795 [INFO] tensorflow: global_step/sec: 14.3412
2021-11-27 21:36:04,862 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.297
INFO:tensorflow:global_step/sec: 14.4972
2021-11-27 21:36:04,933 [INFO] tensorflow: global_step/sec: 14.4972
INFO:tensorflow:global_step/sec: 13.8729
2021-11-27 21:36:05,077 [INFO] tensorflow: global_step/sec: 13.8729
2021-11-27 21:36:05,078 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 116/120: loss: 0.00121 learning rate: 0.00001 Time taken: 0:00:01.517640 ETA: 0:00:06.070560
INFO:tensorflow:global_step/sec: 14.8861
2021-11-27 21:36:05,211 [INFO] tensorflow: global_step/sec: 14.8861
INFO:tensorflow:global_step/sec: 14.3998
2021-11-27 21:36:05,350 [INFO] tensorflow: global_step/sec: 14.3998
INFO:tensorflow:global_step/sec: 14.2438
2021-11-27 21:36:05,491 [INFO] tensorflow: global_step/sec: 14.2438
INFO:tensorflow:global_step/sec: 14.1094
2021-11-27 21:36:05,633 [INFO] tensorflow: global_step/sec: 14.1094
INFO:tensorflow:global_step/sec: 13.9956
2021-11-27 21:36:05,775 [INFO] tensorflow: global_step/sec: 13.9956
INFO:tensorflow:global_step/sec: 14.6737
2021-11-27 21:36:05,912 [INFO] tensorflow: global_step/sec: 14.6737
INFO:tensorflow:global_step/sec: 14.1703
2021-11-27 21:36:06,053 [INFO] tensorflow: global_step/sec: 14.1703
INFO:tensorflow:epoch = 116.72727272727273, learning_rate = 7.5995595e-06, loss = 0.0012394936, step = 2568 (5.124 sec)
2021-11-27 21:36:06,191 [INFO] tensorflow: epoch = 116.72727272727273, learning_rate = 7.5995595e-06, loss = 0.0012394936, step = 2568 (5.124 sec)
INFO:tensorflow:global_step/sec: 14.3231
2021-11-27 21:36:06,193 [INFO] tensorflow: global_step/sec: 14.3231
INFO:tensorflow:global_step/sec: 14.611
2021-11-27 21:36:06,329 [INFO] tensorflow: global_step/sec: 14.611
INFO:tensorflow:global_step/sec: 14.8816
2021-11-27 21:36:06,464 [INFO] tensorflow: global_step/sec: 14.8816
INFO:tensorflow:global_step/sec: 13.4691
2021-11-27 21:36:06,612 [INFO] tensorflow: global_step/sec: 13.4691
2021-11-27 21:36:06,613 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 117/120: loss: 0.00138 learning rate: 0.00001 Time taken: 0:00:01.534928 ETA: 0:00:04.604785
2021-11-27 21:36:06,613 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.105
INFO:tensorflow:global_step/sec: 14.7677
2021-11-27 21:36:06,748 [INFO] tensorflow: global_step/sec: 14.7677
INFO:tensorflow:global_step/sec: 14.1354
2021-11-27 21:36:06,889 [INFO] tensorflow: global_step/sec: 14.1354
INFO:tensorflow:global_step/sec: 14.3794
2021-11-27 21:36:07,028 [INFO] tensorflow: global_step/sec: 14.3794
INFO:tensorflow:global_step/sec: 14.2387
2021-11-27 21:36:07,169 [INFO] tensorflow: global_step/sec: 14.2387
INFO:tensorflow:global_step/sec: 14.4183
2021-11-27 21:36:07,308 [INFO] tensorflow: global_step/sec: 14.4183
INFO:tensorflow:global_step/sec: 14.5625
2021-11-27 21:36:07,445 [INFO] tensorflow: global_step/sec: 14.5625
INFO:tensorflow:global_step/sec: 14.7991
2021-11-27 21:36:07,580 [INFO] tensorflow: global_step/sec: 14.7991
INFO:tensorflow:global_step/sec: 13.978
2021-11-27 21:36:07,723 [INFO] tensorflow: global_step/sec: 13.978
INFO:tensorflow:global_step/sec: 13.9176
2021-11-27 21:36:07,867 [INFO] tensorflow: global_step/sec: 13.9176
INFO:tensorflow:global_step/sec: 14.3272
2021-11-27 21:36:08,006 [INFO] tensorflow: global_step/sec: 14.3272
INFO:tensorflow:global_step/sec: 13.9617
2021-11-27 21:36:08,150 [INFO] tensorflow: global_step/sec: 13.9617
2021-11-27 21:36:08,150 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 118/120: loss: 0.00145 learning rate: 0.00001 Time taken: 0:00:01.533602 ETA: 0:00:03.067203
INFO:tensorflow:global_step/sec: 14.3395
2021-11-27 21:36:08,289 [INFO] tensorflow: global_step/sec: 14.3395
2021-11-27 21:36:08,357 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.347
INFO:tensorflow:global_step/sec: 14.0976
2021-11-27 21:36:08,431 [INFO] tensorflow: global_step/sec: 14.0976
INFO:tensorflow:global_step/sec: 14.6155
2021-11-27 21:36:08,568 [INFO] tensorflow: global_step/sec: 14.6155
INFO:tensorflow:global_step/sec: 14.7138
2021-11-27 21:36:08,704 [INFO] tensorflow: global_step/sec: 14.7138
INFO:tensorflow:global_step/sec: 14.8451
2021-11-27 21:36:08,838 [INFO] tensorflow: global_step/sec: 14.8451
INFO:tensorflow:global_step/sec: 14.41
2021-11-27 21:36:08,977 [INFO] tensorflow: global_step/sec: 14.41
INFO:tensorflow:global_step/sec: 13.8988
2021-11-27 21:36:09,121 [INFO] tensorflow: global_step/sec: 13.8988
INFO:tensorflow:global_step/sec: 14.2431
2021-11-27 21:36:09,262 [INFO] tensorflow: global_step/sec: 14.2431
INFO:tensorflow:global_step/sec: 14.5307
2021-11-27 21:36:09,399 [INFO] tensorflow: global_step/sec: 14.5307
INFO:tensorflow:global_step/sec: 14.5938
2021-11-27 21:36:09,536 [INFO] tensorflow: global_step/sec: 14.5938
INFO:tensorflow:global_step/sec: 13.8167
2021-11-27 21:36:09,681 [INFO] tensorflow: global_step/sec: 13.8167
2021-11-27 21:36:09,682 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 119/120: loss: 0.00121 learning rate: 0.00001 Time taken: 0:00:01.529356 ETA: 0:00:01.529356
INFO:tensorflow:global_step/sec: 14.7229
2021-11-27 21:36:09,817 [INFO] tensorflow: global_step/sec: 14.7229
INFO:tensorflow:global_step/sec: 14.6472
2021-11-27 21:36:09,953 [INFO] tensorflow: global_step/sec: 14.6472
INFO:tensorflow:global_step/sec: 14.428
2021-11-27 21:36:10,092 [INFO] tensorflow: global_step/sec: 14.428
2021-11-27 21:36:10,093 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.627
INFO:tensorflow:global_step/sec: 14.2148
2021-11-27 21:36:10,233 [INFO] tensorflow: global_step/sec: 14.2148
INFO:tensorflow:global_step/sec: 14.3256
2021-11-27 21:36:10,372 [INFO] tensorflow: global_step/sec: 14.3256
INFO:tensorflow:global_step/sec: 14.4748
2021-11-27 21:36:10,510 [INFO] tensorflow: global_step/sec: 14.4748
INFO:tensorflow:global_step/sec: 15.2355
2021-11-27 21:36:10,642 [INFO] tensorflow: global_step/sec: 15.2355
INFO:tensorflow:global_step/sec: 15.0577
2021-11-27 21:36:10,775 [INFO] tensorflow: global_step/sec: 15.0577
INFO:tensorflow:global_step/sec: 14.5631
2021-11-27 21:36:10,912 [INFO] tensorflow: global_step/sec: 14.5631
INFO:tensorflow:global_step/sec: 14.3989
2021-11-27 21:36:11,051 [INFO] tensorflow: global_step/sec: 14.3989
INFO:tensorflow:Saving checkpoints for step-2640.
2021-11-27 21:36:11,121 [INFO] tensorflow: Saving checkpoints for step-2640.
WARNING:tensorflow:Ignoring: /tmp/tmp604f7xq1; No such file or directory
2021-11-27 21:36:11,218 [WARNING] tensorflow: Ignoring: /tmp/tmp604f7xq1; No such file or directory
2021-11-27 21:36:13,520 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 1652/1652 [00:00<00:00, 24822.55it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 5352/5352 [00:00<00:00, 28319.69it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 743/743 [00:00<00:00, 24934.13it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 11263/11263 [00:00<00:00, 30549.78it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 665/665 [00:00<00:00, 25427.90it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 1576/1576 [00:00<00:00, 23787.28it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 8785/8785 [00:00<00:00, 41250.82it/s]
Epoch 120/120
=========================
Validation cost: 0.000682
Mean average_precision (in %): 16.7417
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 24.4347
floor 0
palette 1.55316
pillar 31.1881
pushcart 0
rackframe 26.8855
rackshelf 43.3584
wall 23.2551
Median Inference Time: 0.007639
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:95: The name tf.reset_default_graph is deprecated. Please use tf.compat.v1.reset_default_graph instead.
2021-11-27 21:36:19,837 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:95: The name tf.reset_default_graph is deprecated. Please use tf.compat.v1.reset_default_graph instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:98: The name tf.placeholder_with_default is deprecated. Please use tf.compat.v1.placeholder_with_default instead.
2021-11-27 21:36:19,837 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:98: The name tf.placeholder_with_default is deprecated. Please use tf.compat.v1.placeholder_with_default instead.
2021-11-27 21:36:19,839 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.627
Time taken to run __main__:main: 0:05:15.499475.
2021-11-27 16:36:21,873 [INFO] tlt.components.docker_handler.docker_handler: Stopping container.
|
pantelis-classes/omniverse-ai/training_output/dataset1/train_prune_1_summary.txt | Mean average_precision (in %): 21.7641
Mean average_precision (in %): 21.1592
Mean average_precision (in %): 24.4442
Mean average_precision (in %): 26.8432
Mean average_precision (in %): 27.0035
Mean average_precision (in %): 28.1822
Mean average_precision (in %): 28.8910
Mean average_precision (in %): 30.8107
Mean average_precision (in %): 32.1409
Mean average_precision (in %): 30.6785
Validation cost: 0.000636
Validation cost: 0.000671
Validation cost: 0.000479
Validation cost: 0.000544
Validation cost: 0.000533
Validation cost: 0.000479
Validation cost: 0.000422
Validation cost: 0.000361
Validation cost: 0.000356
Validation cost: 0.000278 |
pantelis-classes/omniverse-ai/training_output/dataset1/train_prune_1.txt | 2021-11-27 17:09:53,809 [INFO] root: Registry: ['nvcr.io']
2021-11-27 17:09:53,862 [INFO] tlt.components.instance_handler.local_instance: Running command in container: nvcr.io/nvidia/tao/tao-toolkit-tf:v3.21.11-tf1.15.4-py3
Matplotlib created a temporary config/cache directory at /tmp/matplotlib-1kd6oqh2 because the default path (/.config/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.
Using TensorFlow backend.
WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
Using TensorFlow backend.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:43: The name tf.train.SessionRunHook is deprecated. Please use tf.estimator.SessionRunHook instead.
2021-11-27 22:09:58,345 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:43: The name tf.train.SessionRunHook is deprecated. Please use tf.estimator.SessionRunHook instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/checkpoint_saver_hook.py:25: The name tf.train.CheckpointSaverHook is deprecated. Please use tf.estimator.CheckpointSaverHook instead.
2021-11-27 22:09:58,440 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/checkpoint_saver_hook.py:25: The name tf.train.CheckpointSaverHook is deprecated. Please use tf.estimator.CheckpointSaverHook instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:69: The name tf.logging.set_verbosity is deprecated. Please use tf.compat.v1.logging.set_verbosity instead.
2021-11-27 22:09:58,442 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:69: The name tf.logging.set_verbosity is deprecated. Please use tf.compat.v1.logging.set_verbosity instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:69: The name tf.logging.INFO is deprecated. Please use tf.compat.v1.logging.INFO instead.
2021-11-27 22:09:58,442 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:69: The name tf.logging.INFO is deprecated. Please use tf.compat.v1.logging.INFO instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:117: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.
2021-11-27 22:09:58,447 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:117: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:143: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.
2021-11-27 22:09:58,447 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:143: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.
2021-11-27 22:09:58,711 [INFO] __main__: Loading experiment spec at /workspace/tao-experiments/detectnet_v2/specs/detectnet_v2_retrain_resnet18_kitti.txt.
2021-11-27 22:09:58,712 [INFO] iva.detectnet_v2.spec_handler.spec_loader: Merging specification from /workspace/tao-experiments/detectnet_v2/specs/detectnet_v2_retrain_resnet18_kitti.txt
2021-11-27 22:09:58,809 [INFO] __main__: Cannot iterate over exactly 86 samples with a batch size of 4; each epoch will therefore take one extra step.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:107: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
2021-11-27 22:09:58,812 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:107: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:110: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.
2021-11-27 22:09:58,812 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:110: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:113: The name tf.assign is deprecated. Please use tf.compat.v1.assign instead.
2021-11-27 22:09:58,814 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:113: The name tf.assign is deprecated. Please use tf.compat.v1.assign instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
2021-11-27 22:09:59,233 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
2021-11-27 22:09:59,246 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1834: The name tf.nn.fused_batch_norm is deprecated. Please use tf.compat.v1.nn.fused_batch_norm instead.
2021-11-27 22:09:59,260 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1834: The name tf.nn.fused_batch_norm is deprecated. Please use tf.compat.v1.nn.fused_batch_norm instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:174: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.
2021-11-27 22:09:59,773 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:174: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:199: The name tf.is_variable_initialized is deprecated. Please use tf.compat.v1.is_variable_initialized instead.
2021-11-27 22:09:59,773 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:199: The name tf.is_variable_initialized is deprecated. Please use tf.compat.v1.is_variable_initialized instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:206: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.
2021-11-27 22:09:59,886 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:206: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.
/usr/local/lib/python3.6/dist-packages/keras/engine/saving.py:292: UserWarning: No training configuration found in save file: the model was *not* compiled. Compile it manually.
warnings.warn('No training configuration found in save file: '
2021-11-27 22:10:00,086 [INFO] iva.detectnet_v2.objectives.bbox_objective: Default L1 loss function will be used.
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) (None, 3, 384, 1248) 0
__________________________________________________________________________________________________
conv1 (Conv2D) (None, 64, 192, 624) 9472 input_1[0][0]
__________________________________________________________________________________________________
bn_conv1 (BatchNormalization) (None, 64, 192, 624) 256 conv1[0][0]
__________________________________________________________________________________________________
activation_1 (Activation) (None, 64, 192, 624) 0 bn_conv1[0][0]
__________________________________________________________________________________________________
block_1a_conv_1 (Conv2D) (None, 64, 96, 312) 36928 activation_1[0][0]
__________________________________________________________________________________________________
block_1a_bn_1 (BatchNormalizati (None, 64, 96, 312) 256 block_1a_conv_1[0][0]
__________________________________________________________________________________________________
block_1a_relu_1 (Activation) (None, 64, 96, 312) 0 block_1a_bn_1[0][0]
__________________________________________________________________________________________________
block_1a_conv_2 (Conv2D) (None, 64, 96, 312) 36928 block_1a_relu_1[0][0]
__________________________________________________________________________________________________
block_1a_conv_shortcut (Conv2D) (None, 64, 96, 312) 4160 activation_1[0][0]
__________________________________________________________________________________________________
block_1a_bn_2 (BatchNormalizati (None, 64, 96, 312) 256 block_1a_conv_2[0][0]
__________________________________________________________________________________________________
block_1a_bn_shortcut (BatchNorm (None, 64, 96, 312) 256 block_1a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, 64, 96, 312) 0 block_1a_bn_2[0][0]
block_1a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_1a_relu (Activation) (None, 64, 96, 312) 0 add_1[0][0]
__________________________________________________________________________________________________
block_1b_conv_1 (Conv2D) (None, 64, 96, 312) 36928 block_1a_relu[0][0]
__________________________________________________________________________________________________
block_1b_bn_1 (BatchNormalizati (None, 64, 96, 312) 256 block_1b_conv_1[0][0]
__________________________________________________________________________________________________
block_1b_relu_1 (Activation) (None, 64, 96, 312) 0 block_1b_bn_1[0][0]
__________________________________________________________________________________________________
block_1b_conv_2 (Conv2D) (None, 64, 96, 312) 36928 block_1b_relu_1[0][0]
__________________________________________________________________________________________________
block_1b_bn_2 (BatchNormalizati (None, 64, 96, 312) 256 block_1b_conv_2[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, 64, 96, 312) 0 block_1b_bn_2[0][0]
block_1a_relu[0][0]
__________________________________________________________________________________________________
block_1b_relu (Activation) (None, 64, 96, 312) 0 add_2[0][0]
__________________________________________________________________________________________________
block_2a_conv_1 (Conv2D) (None, 128, 48, 156) 73856 block_1b_relu[0][0]
__________________________________________________________________________________________________
block_2a_bn_1 (BatchNormalizati (None, 128, 48, 156) 512 block_2a_conv_1[0][0]
__________________________________________________________________________________________________
block_2a_relu_1 (Activation) (None, 128, 48, 156) 0 block_2a_bn_1[0][0]
__________________________________________________________________________________________________
block_2a_conv_2 (Conv2D) (None, 128, 48, 156) 147584 block_2a_relu_1[0][0]
__________________________________________________________________________________________________
block_2a_conv_shortcut (Conv2D) (None, 128, 48, 156) 8320 block_1b_relu[0][0]
__________________________________________________________________________________________________
block_2a_bn_2 (BatchNormalizati (None, 128, 48, 156) 512 block_2a_conv_2[0][0]
__________________________________________________________________________________________________
block_2a_bn_shortcut (BatchNorm (None, 128, 48, 156) 512 block_2a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_3 (Add) (None, 128, 48, 156) 0 block_2a_bn_2[0][0]
block_2a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_2a_relu (Activation) (None, 128, 48, 156) 0 add_3[0][0]
__________________________________________________________________________________________________
block_2b_conv_1 (Conv2D) (None, 128, 48, 156) 147584 block_2a_relu[0][0]
__________________________________________________________________________________________________
block_2b_bn_1 (BatchNormalizati (None, 128, 48, 156) 512 block_2b_conv_1[0][0]
__________________________________________________________________________________________________
block_2b_relu_1 (Activation) (None, 128, 48, 156) 0 block_2b_bn_1[0][0]
__________________________________________________________________________________________________
block_2b_conv_2 (Conv2D) (None, 128, 48, 156) 147584 block_2b_relu_1[0][0]
__________________________________________________________________________________________________
block_2b_bn_2 (BatchNormalizati (None, 128, 48, 156) 512 block_2b_conv_2[0][0]
__________________________________________________________________________________________________
add_4 (Add) (None, 128, 48, 156) 0 block_2b_bn_2[0][0]
block_2a_relu[0][0]
__________________________________________________________________________________________________
block_2b_relu (Activation) (None, 128, 48, 156) 0 add_4[0][0]
__________________________________________________________________________________________________
block_3a_conv_1 (Conv2D) (None, 256, 24, 78) 295168 block_2b_relu[0][0]
__________________________________________________________________________________________________
block_3a_bn_1 (BatchNormalizati (None, 256, 24, 78) 1024 block_3a_conv_1[0][0]
__________________________________________________________________________________________________
block_3a_relu_1 (Activation) (None, 256, 24, 78) 0 block_3a_bn_1[0][0]
__________________________________________________________________________________________________
block_3a_conv_2 (Conv2D) (None, 256, 24, 78) 590080 block_3a_relu_1[0][0]
__________________________________________________________________________________________________
block_3a_conv_shortcut (Conv2D) (None, 256, 24, 78) 33024 block_2b_relu[0][0]
__________________________________________________________________________________________________
block_3a_bn_2 (BatchNormalizati (None, 256, 24, 78) 1024 block_3a_conv_2[0][0]
__________________________________________________________________________________________________
block_3a_bn_shortcut (BatchNorm (None, 256, 24, 78) 1024 block_3a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_5 (Add) (None, 256, 24, 78) 0 block_3a_bn_2[0][0]
block_3a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_3a_relu (Activation) (None, 256, 24, 78) 0 add_5[0][0]
__________________________________________________________________________________________________
block_3b_conv_1 (Conv2D) (None, 256, 24, 78) 590080 block_3a_relu[0][0]
__________________________________________________________________________________________________
block_3b_bn_1 (BatchNormalizati (None, 256, 24, 78) 1024 block_3b_conv_1[0][0]
__________________________________________________________________________________________________
block_3b_relu_1 (Activation) (None, 256, 24, 78) 0 block_3b_bn_1[0][0]
__________________________________________________________________________________________________
block_3b_conv_2 (Conv2D) (None, 256, 24, 78) 590080 block_3b_relu_1[0][0]
__________________________________________________________________________________________________
block_3b_bn_2 (BatchNormalizati (None, 256, 24, 78) 1024 block_3b_conv_2[0][0]
__________________________________________________________________________________________________
add_6 (Add) (None, 256, 24, 78) 0 block_3b_bn_2[0][0]
block_3a_relu[0][0]
__________________________________________________________________________________________________
block_3b_relu (Activation) (None, 256, 24, 78) 0 add_6[0][0]
__________________________________________________________________________________________________
block_4a_conv_1 (Conv2D) (None, 512, 24, 78) 1180160 block_3b_relu[0][0]
__________________________________________________________________________________________________
block_4a_bn_1 (BatchNormalizati (None, 512, 24, 78) 2048 block_4a_conv_1[0][0]
__________________________________________________________________________________________________
block_4a_relu_1 (Activation) (None, 512, 24, 78) 0 block_4a_bn_1[0][0]
__________________________________________________________________________________________________
block_4a_conv_2 (Conv2D) (None, 512, 24, 78) 2359808 block_4a_relu_1[0][0]
__________________________________________________________________________________________________
block_4a_conv_shortcut (Conv2D) (None, 512, 24, 78) 131584 block_3b_relu[0][0]
__________________________________________________________________________________________________
block_4a_bn_2 (BatchNormalizati (None, 512, 24, 78) 2048 block_4a_conv_2[0][0]
__________________________________________________________________________________________________
block_4a_bn_shortcut (BatchNorm (None, 512, 24, 78) 2048 block_4a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_7 (Add) (None, 512, 24, 78) 0 block_4a_bn_2[0][0]
block_4a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_4a_relu (Activation) (None, 512, 24, 78) 0 add_7[0][0]
__________________________________________________________________________________________________
block_4b_conv_1 (Conv2D) (None, 512, 24, 78) 2359808 block_4a_relu[0][0]
__________________________________________________________________________________________________
block_4b_bn_1 (BatchNormalizati (None, 512, 24, 78) 2048 block_4b_conv_1[0][0]
__________________________________________________________________________________________________
block_4b_relu_1 (Activation) (None, 512, 24, 78) 0 block_4b_bn_1[0][0]
__________________________________________________________________________________________________
block_4b_conv_2 (Conv2D) (None, 512, 24, 78) 2359808 block_4b_relu_1[0][0]
__________________________________________________________________________________________________
block_4b_bn_2 (BatchNormalizati (None, 512, 24, 78) 2048 block_4b_conv_2[0][0]
__________________________________________________________________________________________________
add_8 (Add) (None, 512, 24, 78) 0 block_4b_bn_2[0][0]
block_4a_relu[0][0]
__________________________________________________________________________________________________
block_4b_relu (Activation) (None, 512, 24, 78) 0 add_8[0][0]
__________________________________________________________________________________________________
output_bbox (Conv2D) (None, 36, 24, 78) 18468 block_4b_relu[0][0]
__________________________________________________________________________________________________
output_cov (Conv2D) (None, 9, 24, 78) 4617 block_4b_relu[0][0]
==================================================================================================
Total params: 11,218,413
Trainable params: 11,208,685
Non-trainable params: 9,728
__________________________________________________________________________________________________
2021-11-27 22:10:00,888 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Serial augmentation enabled = False
2021-11-27 22:10:00,888 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Pseudo sharding enabled = False
2021-11-27 22:10:00,889 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Max Image Dimensions (all sources): (0, 0)
2021-11-27 22:10:00,889 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: number of cpus: 16, io threads: 32, compute threads: 16, buffered batches: 4
2021-11-27 22:10:00,889 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: total dataset size 86, number of sources: 1, batch size per gpu: 4, steps: 22
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/autograph/converters/directives.py:119: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
2021-11-27 22:10:00,920 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/autograph/converters/directives.py:119: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
WARNING:tensorflow:Entity <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7f85a9c8c7f0>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7f85a9c8c7f0>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 22:10:00,954 [WARNING] tensorflow: Entity <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7f85a9c8c7f0>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7f85a9c8c7f0>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 22:10:00,967 [INFO] iva.detectnet_v2.dataloader.default_dataloader: Bounding box coordinates were detected in the input specification! Bboxes will be automatically converted to polygon coordinates.
2021-11-27 22:10:01,137 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: shuffle: True - shard 0 of 1
2021-11-27 22:10:01,141 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: sampling 1 datasets with weights:
2021-11-27 22:10:01,141 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: source: 0 weight: 1.000000
WARNING:tensorflow:Entity <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7f85e8be5860>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7f85e8be5860>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 22:10:01,153 [WARNING] tensorflow: Entity <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7f85e8be5860>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7f85e8be5860>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 22:10:01,400 [INFO] __main__: Found 86 samples in training set
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/rasterizers/bbox_rasterizer.py:347: The name tf.bincount is deprecated. Please use tf.math.bincount instead.
2021-11-27 22:10:01,471 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/rasterizers/bbox_rasterizer.py:347: The name tf.bincount is deprecated. Please use tf.math.bincount instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/training_proto_utilities.py:89: The name tf.train.get_or_create_global_step is deprecated. Please use tf.compat.v1.train.get_or_create_global_step instead.
2021-11-27 22:10:01,590 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/training_proto_utilities.py:89: The name tf.train.get_or_create_global_step is deprecated. Please use tf.compat.v1.train.get_or_create_global_step instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/training_proto_utilities.py:36: The name tf.train.AdamOptimizer is deprecated. Please use tf.compat.v1.train.AdamOptimizer instead.
2021-11-27 22:10:01,601 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/training_proto_utilities.py:36: The name tf.train.AdamOptimizer is deprecated. Please use tf.compat.v1.train.AdamOptimizer instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_functions.py:17: The name tf.log is deprecated. Please use tf.math.log instead.
2021-11-27 22:10:01,808 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_functions.py:17: The name tf.log is deprecated. Please use tf.math.log instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:235: The name tf.assign_add is deprecated. Please use tf.compat.v1.assign_add instead.
2021-11-27 22:10:01,902 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/cost_function/cost_auto_weight_hook.py:235: The name tf.assign_add is deprecated. Please use tf.compat.v1.assign_add instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/model/detectnet_model.py:591: The name tf.summary.scalar is deprecated. Please use tf.compat.v1.summary.scalar instead.
2021-11-27 22:10:01,920 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/model/detectnet_model.py:591: The name tf.summary.scalar is deprecated. Please use tf.compat.v1.summary.scalar instead.
2021-11-27 22:10:03,236 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Serial augmentation enabled = False
2021-11-27 22:10:03,236 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Pseudo sharding enabled = False
2021-11-27 22:10:03,236 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: Max Image Dimensions (all sources): (0, 0)
2021-11-27 22:10:03,236 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: number of cpus: 16, io threads: 32, compute threads: 16, buffered batches: 4
2021-11-27 22:10:03,236 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: total dataset size 14, number of sources: 1, batch size per gpu: 4, steps: 4
WARNING:tensorflow:Entity <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7f85a9c8c898>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7f85a9c8c898>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 22:10:03,243 [WARNING] tensorflow: Entity <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7f85a9c8c898>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method DriveNetTFRecordsParser.__call__ of <iva.detectnet_v2.dataloader.drivenet_dataloader.DriveNetTFRecordsParser object at 0x7f85a9c8c898>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 22:10:03,259 [INFO] iva.detectnet_v2.dataloader.default_dataloader: Bounding box coordinates were detected in the input specification! Bboxes will be automatically converted to polygon coordinates.
2021-11-27 22:10:03,417 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: shuffle: False - shard 0 of 1
2021-11-27 22:10:03,420 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: sampling 1 datasets with weights:
2021-11-27 22:10:03,420 [INFO] modulus.blocks.data_loaders.multi_source_loader.data_loader: source: 0 weight: 1.000000
WARNING:tensorflow:Entity <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7f85704ce8d0>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7f85704ce8d0>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 22:10:03,431 [WARNING] tensorflow: Entity <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7f85704ce8d0>> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Unable to locate the source code of <bound method Processor.__call__ of <modulus.blocks.data_loaders.multi_source_loader.processors.asset_loader.AssetLoader object at 0x7f85704ce8d0>>. Note that functions defined in certain environments, like the interactive Python shell do not expose their source code. If that is the case, you should to define them in a .py source file. If you are certain the code is graph-compatible, wrap the call using @tf.autograph.do_not_convert. Original error: could not get source code
2021-11-27 22:10:03,590 [INFO] __main__: Found 14 samples in validation set
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/validation_hook.py:40: The name tf.summary.FileWriterCache is deprecated. Please use tf.compat.v1.summary.FileWriterCache instead.
2021-11-27 22:10:04,205 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/validation_hook.py:40: The name tf.summary.FileWriterCache is deprecated. Please use tf.compat.v1.summary.FileWriterCache instead.
2021-11-27 22:10:05,025 [INFO] __main__: Checkpoint interval: 10
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:109: The name tf.train.Scaffold is deprecated. Please use tf.compat.v1.train.Scaffold instead.
2021-11-27 22:10:05,026 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/scripts/train.py:109: The name tf.train.Scaffold is deprecated. Please use tf.compat.v1.train.Scaffold instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:14: The name tf.local_variables_initializer is deprecated. Please use tf.compat.v1.local_variables_initializer instead.
2021-11-27 22:10:05,026 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:14: The name tf.local_variables_initializer is deprecated. Please use tf.compat.v1.local_variables_initializer instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:15: The name tf.tables_initializer is deprecated. Please use tf.compat.v1.tables_initializer instead.
2021-11-27 22:10:05,026 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:15: The name tf.tables_initializer is deprecated. Please use tf.compat.v1.tables_initializer instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:16: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
2021-11-27 22:10:05,027 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/common/graph/initializers.py:16: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:59: The name tf.train.LoggingTensorHook is deprecated. Please use tf.estimator.LoggingTensorHook instead.
2021-11-27 22:10:05,028 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:59: The name tf.train.LoggingTensorHook is deprecated. Please use tf.estimator.LoggingTensorHook instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:60: The name tf.train.StopAtStepHook is deprecated. Please use tf.estimator.StopAtStepHook instead.
2021-11-27 22:10:05,028 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:60: The name tf.train.StopAtStepHook is deprecated. Please use tf.estimator.StopAtStepHook instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:73: The name tf.train.StepCounterHook is deprecated. Please use tf.estimator.StepCounterHook instead.
2021-11-27 22:10:05,028 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:73: The name tf.train.StepCounterHook is deprecated. Please use tf.estimator.StepCounterHook instead.
INFO:tensorflow:Create CheckpointSaverHook.
2021-11-27 22:10:05,028 [INFO] tensorflow: Create CheckpointSaverHook.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:99: The name tf.train.SummarySaverHook is deprecated. Please use tf.estimator.SummarySaverHook instead.
2021-11-27 22:10:05,028 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/tfhooks/utils.py:99: The name tf.train.SummarySaverHook is deprecated. Please use tf.estimator.SummarySaverHook instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/utilities.py:140: The name tf.train.SingularMonitoredSession is deprecated. Please use tf.compat.v1.train.SingularMonitoredSession instead.
2021-11-27 22:10:05,029 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/75913d2aee35770fa76c4a63d877f3aa/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/training/utilities.py:140: The name tf.train.SingularMonitoredSession is deprecated. Please use tf.compat.v1.train.SingularMonitoredSession instead.
INFO:tensorflow:Graph was finalized.
2021-11-27 22:10:05,573 [INFO] tensorflow: Graph was finalized.
INFO:tensorflow:Running local_init_op.
2021-11-27 22:10:06,767 [INFO] tensorflow: Running local_init_op.
INFO:tensorflow:Done running local_init_op.
2021-11-27 22:10:07,176 [INFO] tensorflow: Done running local_init_op.
INFO:tensorflow:Saving checkpoints for step-0.
2021-11-27 22:10:11,761 [INFO] tensorflow: Saving checkpoints for step-0.
INFO:tensorflow:epoch = 0.0, learning_rate = 4.9999994e-06, loss = 0.0057869037, step = 0
2021-11-27 22:10:27,132 [INFO] tensorflow: epoch = 0.0, learning_rate = 4.9999994e-06, loss = 0.0057869037, step = 0
2021-11-27 22:10:27,135 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 0/120: loss: 0.00579 learning rate: 0.00000 Time taken: 0:00:00 ETA: 0:00:00
2021-11-27 22:10:27,135 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 0.886
INFO:tensorflow:global_step/sec: 1.28718
2021-11-27 22:10:28,688 [INFO] tensorflow: global_step/sec: 1.28718
INFO:tensorflow:global_step/sec: 14.0748
2021-11-27 22:10:28,830 [INFO] tensorflow: global_step/sec: 14.0748
INFO:tensorflow:global_step/sec: 14.3482
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INFO:tensorflow:global_step/sec: 13.9133
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INFO:tensorflow:global_step/sec: 14.2399
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INFO:tensorflow:global_step/sec: 14.7486
2021-11-27 22:10:29,527 [INFO] tensorflow: global_step/sec: 14.7486
INFO:tensorflow:global_step/sec: 14.9261
2021-11-27 22:10:29,661 [INFO] tensorflow: global_step/sec: 14.9261
INFO:tensorflow:global_step/sec: 13.9907
2021-11-27 22:10:29,804 [INFO] tensorflow: global_step/sec: 13.9907
INFO:tensorflow:global_step/sec: 14.7185
2021-11-27 22:10:29,939 [INFO] tensorflow: global_step/sec: 14.7185
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INFO:tensorflow:global_step/sec: 4.76802
2021-11-27 22:10:30,359 [INFO] tensorflow: global_step/sec: 4.76802
2021-11-27 22:10:30,360 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 1/120: loss: 0.00117 learning rate: 0.00001 Time taken: 0:00:07.667110 ETA: 0:15:12.386114
INFO:tensorflow:global_step/sec: 14.1503
2021-11-27 22:10:30,500 [INFO] tensorflow: global_step/sec: 14.1503
2021-11-27 22:10:30,502 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 12.688
INFO:tensorflow:global_step/sec: 13.962
2021-11-27 22:10:30,643 [INFO] tensorflow: global_step/sec: 13.962
INFO:tensorflow:global_step/sec: 14.2076
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2021-11-27 22:10:31,502 [INFO] tensorflow: global_step/sec: 12.7762
INFO:tensorflow:global_step/sec: 14.4759
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INFO:tensorflow:global_step/sec: 14.5683
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INFO:tensorflow:global_step/sec: 13.889
2021-11-27 22:10:31,921 [INFO] tensorflow: global_step/sec: 13.889
2021-11-27 22:10:31,922 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 2/120: loss: 0.00123 learning rate: 0.00001 Time taken: 0:00:01.565355 ETA: 0:03:04.711841
INFO:tensorflow:global_step/sec: 14.3858
2021-11-27 22:10:32,060 [INFO] tensorflow: global_step/sec: 14.3858
INFO:tensorflow:global_step/sec: 14.6394
2021-11-27 22:10:32,197 [INFO] tensorflow: global_step/sec: 14.6394
INFO:tensorflow:epoch = 2.2272727272727275, learning_rate = 1.1753905e-05, loss = 0.0011409044, step = 49 (5.136 sec)
2021-11-27 22:10:32,268 [INFO] tensorflow: epoch = 2.2272727272727275, learning_rate = 1.1753905e-05, loss = 0.0011409044, step = 49 (5.136 sec)
2021-11-27 22:10:32,268 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 56.623
INFO:tensorflow:global_step/sec: 14.1407
2021-11-27 22:10:32,338 [INFO] tensorflow: global_step/sec: 14.1407
INFO:tensorflow:global_step/sec: 14.5826
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INFO:tensorflow:global_step/sec: 13.6269
2021-11-27 22:10:33,458 [INFO] tensorflow: global_step/sec: 13.6269
2021-11-27 22:10:33,459 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 3/120: loss: 0.00113 learning rate: 0.00002 Time taken: 0:00:01.530060 ETA: 0:02:59.016998
INFO:tensorflow:global_step/sec: 14.4893
2021-11-27 22:10:33,596 [INFO] tensorflow: global_step/sec: 14.4893
INFO:tensorflow:global_step/sec: 14.6592
2021-11-27 22:10:33,733 [INFO] tensorflow: global_step/sec: 14.6592
INFO:tensorflow:global_step/sec: 14.2459
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INFO:tensorflow:global_step/sec: 14.5389
2021-11-27 22:10:34,011 [INFO] tensorflow: global_step/sec: 14.5389
2021-11-27 22:10:34,011 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.380
INFO:tensorflow:global_step/sec: 14.1133
2021-11-27 22:10:34,152 [INFO] tensorflow: global_step/sec: 14.1133
INFO:tensorflow:global_step/sec: 14.4133
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INFO:tensorflow:global_step/sec: 14.2858
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INFO:tensorflow:global_step/sec: 13.8519
2021-11-27 22:10:34,575 [INFO] tensorflow: global_step/sec: 13.8519
INFO:tensorflow:global_step/sec: 15.0399
2021-11-27 22:10:34,708 [INFO] tensorflow: global_step/sec: 15.0399
INFO:tensorflow:global_step/sec: 14.6715
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INFO:tensorflow:global_step/sec: 14.0326
2021-11-27 22:10:34,987 [INFO] tensorflow: global_step/sec: 14.0326
2021-11-27 22:10:34,989 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 4/120: loss: 0.00138 learning rate: 0.00002 Time taken: 0:00:01.529464 ETA: 0:02:57.417825
INFO:tensorflow:global_step/sec: 13.7093
2021-11-27 22:10:35,133 [INFO] tensorflow: global_step/sec: 13.7093
INFO:tensorflow:global_step/sec: 14.6254
2021-11-27 22:10:35,270 [INFO] tensorflow: global_step/sec: 14.6254
INFO:tensorflow:global_step/sec: 14.9256
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2021-11-27 22:10:35,745 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.687
INFO:tensorflow:global_step/sec: 14.5807
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2021-11-27 22:10:36,500 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 5/120: loss: 0.00136 learning rate: 0.00003 Time taken: 0:00:01.513087 ETA: 0:02:54.005009
INFO:tensorflow:global_step/sec: 14.3893
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INFO:tensorflow:global_step/sec: 15.2789
2021-11-27 22:10:37,308 [INFO] tensorflow: global_step/sec: 15.2789
INFO:tensorflow:epoch = 5.590909090909091, learning_rate = 4.273544e-05, loss = 0.0011919353, step = 123 (5.106 sec)
2021-11-27 22:10:37,375 [INFO] tensorflow: epoch = 5.590909090909091, learning_rate = 4.273544e-05, loss = 0.0011919353, step = 123 (5.106 sec)
INFO:tensorflow:global_step/sec: 14.1974
2021-11-27 22:10:37,449 [INFO] tensorflow: global_step/sec: 14.1974
2021-11-27 22:10:37,450 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.682
INFO:tensorflow:global_step/sec: 14.4085
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2021-11-27 22:10:38,016 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 6/120: loss: 0.00127 learning rate: 0.00005 Time taken: 0:00:01.511400 ETA: 0:02:52.299653
INFO:tensorflow:global_step/sec: 14.4003
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2021-11-27 22:10:39,135 [INFO] tensorflow: global_step/sec: 14.5577
2021-11-27 22:10:39,201 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.101
INFO:tensorflow:global_step/sec: 14.6615
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2021-11-27 22:10:39,562 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 7/120: loss: 0.00131 learning rate: 0.00007 Time taken: 0:00:01.544771 ETA: 0:02:54.559091
INFO:tensorflow:global_step/sec: 14.4595
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2021-11-27 22:10:40,957 [INFO] tensorflow: global_step/sec: 14.8374
2021-11-27 22:10:40,957 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 56.960
INFO:tensorflow:global_step/sec: 13.769
2021-11-27 22:10:41,102 [INFO] tensorflow: global_step/sec: 13.769
2021-11-27 22:10:41,103 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 8/120: loss: 0.00133 learning rate: 0.00011 Time taken: 0:00:01.539389 ETA: 0:02:52.411583
INFO:tensorflow:global_step/sec: 14.8138
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INFO:tensorflow:global_step/sec: 14.7607
2021-11-27 22:10:42,359 [INFO] tensorflow: global_step/sec: 14.7607
INFO:tensorflow:epoch = 8.90909090909091, learning_rate = 0.00015269278, loss = 0.0012858632, step = 196 (5.115 sec)
2021-11-27 22:10:42,489 [INFO] tensorflow: epoch = 8.90909090909091, learning_rate = 0.00015269278, loss = 0.0012858632, step = 196 (5.115 sec)
INFO:tensorflow:global_step/sec: 15.2785
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INFO:tensorflow:global_step/sec: 13.9753
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2021-11-27 22:10:42,634 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 9/120: loss: 0.00129 learning rate: 0.00016 Time taken: 0:00:01.528173 ETA: 0:02:49.627200
2021-11-27 22:10:42,702 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.329
INFO:tensorflow:global_step/sec: 14.7919
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INFO:tensorflow:global_step/sec: 14.805
2021-11-27 22:10:43,959 [INFO] tensorflow: global_step/sec: 14.805
INFO:tensorflow:Saving checkpoints for step-220.
2021-11-27 22:10:44,030 [INFO] tensorflow: Saving checkpoints for step-220.
INFO:tensorflow:global_step/sec: 0.804096
2021-11-27 22:10:46,446 [INFO] tensorflow: global_step/sec: 0.804096
2021-11-27 22:10:46,447 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 10/120: loss: 0.00132 learning rate: 0.00023 Time taken: 0:00:03.811719 ETA: 0:06:59.289083
INFO:tensorflow:global_step/sec: 14.5069
2021-11-27 22:10:46,584 [INFO] tensorflow: global_step/sec: 14.5069
INFO:tensorflow:global_step/sec: 15.36
2021-11-27 22:10:46,714 [INFO] tensorflow: global_step/sec: 15.36
2021-11-27 22:10:46,715 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 24.920
INFO:tensorflow:global_step/sec: 14.9594
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INFO:tensorflow:global_step/sec: 15.3257
2021-11-27 22:10:47,512 [INFO] tensorflow: global_step/sec: 15.3257
INFO:tensorflow:epoch = 10.772727272727273, learning_rate = 0.00031219394, loss = 0.0011556421, step = 237 (5.089 sec)
2021-11-27 22:10:47,578 [INFO] tensorflow: epoch = 10.772727272727273, learning_rate = 0.00031219394, loss = 0.0011556421, step = 237 (5.089 sec)
INFO:tensorflow:global_step/sec: 15.2045
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2021-11-27 22:10:47,924 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 11/120: loss: 0.00131 learning rate: 0.00034 Time taken: 0:00:01.477134 ETA: 0:02:41.007631
INFO:tensorflow:global_step/sec: 15.0237
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2021-11-27 22:10:48,394 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.565
INFO:tensorflow:global_step/sec: 15.2341
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2021-11-27 22:10:49,408 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 12/120: loss: 0.00111 learning rate: 0.00050 Time taken: 0:00:01.486349 ETA: 0:02:40.525652
INFO:tensorflow:global_step/sec: 15.4042
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2021-11-27 22:10:50,079 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.376
INFO:tensorflow:global_step/sec: 14.8204
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2021-11-27 22:10:50,910 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 13/120: loss: 0.00116 learning rate: 0.00050 Time taken: 0:00:01.494381 ETA: 0:02:39.898762
INFO:tensorflow:global_step/sec: 14.1955
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2021-11-27 22:10:51,793 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.327
INFO:tensorflow:global_step/sec: 15.4031
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2021-11-27 22:10:52,405 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 14/120: loss: 0.00146 learning rate: 0.00050 Time taken: 0:00:01.496245 ETA: 0:02:38.601935
INFO:tensorflow:global_step/sec: 14.9245
2021-11-27 22:10:52,538 [INFO] tensorflow: global_step/sec: 14.9245
INFO:tensorflow:epoch = 14.181818181818182, learning_rate = 0.00049999997, loss = 0.0012439513, step = 312 (5.092 sec)
2021-11-27 22:10:52,671 [INFO] tensorflow: epoch = 14.181818181818182, learning_rate = 0.00049999997, loss = 0.0012439513, step = 312 (5.092 sec)
INFO:tensorflow:global_step/sec: 15.0076
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2021-11-27 22:10:53,476 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.427
INFO:tensorflow:global_step/sec: 14.9793
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INFO:tensorflow:global_step/sec: 13.478
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2021-11-27 22:10:53,901 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 15/120: loss: 0.00104 learning rate: 0.00050 Time taken: 0:00:01.496183 ETA: 0:02:37.099231
INFO:tensorflow:global_step/sec: 14.6539
2021-11-27 22:10:54,037 [INFO] tensorflow: global_step/sec: 14.6539
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2021-11-27 22:10:55,177 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.829
INFO:tensorflow:global_step/sec: 14.5169
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2021-11-27 22:10:55,388 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 16/120: loss: 0.00133 learning rate: 0.00050 Time taken: 0:00:01.484068 ETA: 0:02:34.343039
INFO:tensorflow:global_step/sec: 14.5858
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2021-11-27 22:10:56,877 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 17/120: loss: 0.00114 learning rate: 0.00050 Time taken: 0:00:01.489300 ETA: 0:02:33.397877
2021-11-27 22:10:56,877 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.805
INFO:tensorflow:global_step/sec: 15.3294
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INFO:tensorflow:epoch = 17.59090909090909, learning_rate = 0.00049999997, loss = 0.001189148, step = 387 (5.085 sec)
2021-11-27 22:10:57,756 [INFO] tensorflow: epoch = 17.59090909090909, learning_rate = 0.00049999997, loss = 0.001189148, step = 387 (5.085 sec)
INFO:tensorflow:global_step/sec: 14.8551
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2021-11-27 22:10:58,362 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 18/120: loss: 0.00131 learning rate: 0.00050 Time taken: 0:00:01.484583 ETA: 0:02:31.427480
INFO:tensorflow:global_step/sec: 14.7218
2021-11-27 22:10:58,497 [INFO] tensorflow: global_step/sec: 14.7218
2021-11-27 22:10:58,566 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.217
INFO:tensorflow:global_step/sec: 14.806
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2021-11-27 22:10:59,882 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 19/120: loss: 0.00119 learning rate: 0.00050 Time taken: 0:00:01.514112 ETA: 0:02:32.925336
INFO:tensorflow:global_step/sec: 14.9618
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2021-11-27 22:11:00,286 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.149
INFO:tensorflow:global_step/sec: 14.6819
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INFO:tensorflow:global_step/sec: 15.1324
2021-11-27 22:11:01,252 [INFO] tensorflow: global_step/sec: 15.1324
INFO:tensorflow:Saving checkpoints for step-440.
2021-11-27 22:11:01,320 [INFO] tensorflow: Saving checkpoints for step-440.
INFO:tensorflow:epoch = 20.0, learning_rate = 0.00049999997, loss = 0.001208039, step = 440 (6.087 sec)
2021-11-27 22:11:03,843 [INFO] tensorflow: epoch = 20.0, learning_rate = 0.00049999997, loss = 0.001208039, step = 440 (6.087 sec)
INFO:tensorflow:global_step/sec: 0.771886
2021-11-27 22:11:03,844 [INFO] tensorflow: global_step/sec: 0.771886
2021-11-27 22:11:03,844 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 20/120: loss: 0.00121 learning rate: 0.00050 Time taken: 0:00:03.959430 ETA: 0:06:35.942974
INFO:tensorflow:global_step/sec: 14.5814
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2021-11-27 22:11:04,446 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 24.045
INFO:tensorflow:global_step/sec: 14.9826
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2021-11-27 22:11:05,319 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 21/120: loss: 0.00110 learning rate: 0.00050 Time taken: 0:00:01.475779 ETA: 0:02:26.102103
INFO:tensorflow:global_step/sec: 15.0104
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2021-11-27 22:11:06,116 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.867
INFO:tensorflow:global_step/sec: 15.4283
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2021-11-27 22:11:06,788 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 22/120: loss: 0.00107 learning rate: 0.00050 Time taken: 0:00:01.468107 ETA: 0:02:23.874461
INFO:tensorflow:global_step/sec: 14.8922
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2021-11-27 22:11:07,791 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.726
INFO:tensorflow:global_step/sec: 14.6321
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2021-11-27 22:11:08,263 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 23/120: loss: 0.00113 learning rate: 0.00050 Time taken: 0:00:01.475924 ETA: 0:02:23.164653
INFO:tensorflow:global_step/sec: 14.6945
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INFO:tensorflow:epoch = 23.454545454545457, learning_rate = 0.00049999997, loss = 0.0012071719, step = 516 (5.108 sec)
2021-11-27 22:11:08,950 [INFO] tensorflow: epoch = 23.454545454545457, learning_rate = 0.00049999997, loss = 0.0012071719, step = 516 (5.108 sec)
INFO:tensorflow:global_step/sec: 14.2175
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2021-11-27 22:11:09,528 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.583
INFO:tensorflow:global_step/sec: 14.9116
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INFO:tensorflow:global_step/sec: 14.2348
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2021-11-27 22:11:09,802 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 24/120: loss: 0.00094 learning rate: 0.00050 Time taken: 0:00:01.536662 ETA: 0:02:27.519539
INFO:tensorflow:global_step/sec: 14.5469
2021-11-27 22:11:09,939 [INFO] tensorflow: global_step/sec: 14.5469
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2021-11-27 22:11:11,137 [INFO] tensorflow: global_step/sec: 14.9696
2021-11-27 22:11:11,208 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.530
INFO:tensorflow:global_step/sec: 14.4151
2021-11-27 22:11:11,276 [INFO] tensorflow: global_step/sec: 14.4151
2021-11-27 22:11:11,277 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 25/120: loss: 0.00094 learning rate: 0.00050 Time taken: 0:00:01.472636 ETA: 0:02:19.900441
INFO:tensorflow:global_step/sec: 15.4258
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2021-11-27 22:11:12,743 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 26/120: loss: 0.00101 learning rate: 0.00050 Time taken: 0:00:01.464793 ETA: 0:02:17.690561
INFO:tensorflow:global_step/sec: 14.9314
2021-11-27 22:11:12,876 [INFO] tensorflow: global_step/sec: 14.9314
2021-11-27 22:11:12,877 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.974
INFO:tensorflow:global_step/sec: 14.3269
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INFO:tensorflow:global_step/sec: 15.3888
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INFO:tensorflow:global_step/sec: 14.9479
2021-11-27 22:11:13,965 [INFO] tensorflow: global_step/sec: 14.9479
INFO:tensorflow:epoch = 26.863636363636363, learning_rate = 0.00049999997, loss = 0.0008986265, step = 591 (5.084 sec)
2021-11-27 22:11:14,035 [INFO] tensorflow: epoch = 26.863636363636363, learning_rate = 0.00049999997, loss = 0.0008986265, step = 591 (5.084 sec)
INFO:tensorflow:global_step/sec: 14.6121
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INFO:tensorflow:global_step/sec: 13.803
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2021-11-27 22:11:14,248 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 27/120: loss: 0.00126 learning rate: 0.00050 Time taken: 0:00:01.501443 ETA: 0:02:19.634213
INFO:tensorflow:global_step/sec: 14.2036
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2021-11-27 22:11:14,600 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.040
INFO:tensorflow:global_step/sec: 14.8303
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2021-11-27 22:11:15,781 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 28/120: loss: 0.00106 learning rate: 0.00050 Time taken: 0:00:01.528614 ETA: 0:02:20.632470
INFO:tensorflow:global_step/sec: 14.566
2021-11-27 22:11:15,917 [INFO] tensorflow: global_step/sec: 14.566
INFO:tensorflow:global_step/sec: 14.862
2021-11-27 22:11:16,052 [INFO] tensorflow: global_step/sec: 14.862
INFO:tensorflow:global_step/sec: 14.9036
2021-11-27 22:11:16,186 [INFO] tensorflow: global_step/sec: 14.9036
INFO:tensorflow:global_step/sec: 14.8269
2021-11-27 22:11:16,321 [INFO] tensorflow: global_step/sec: 14.8269
2021-11-27 22:11:16,322 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.106
INFO:tensorflow:global_step/sec: 14.8342
2021-11-27 22:11:16,456 [INFO] tensorflow: global_step/sec: 14.8342
INFO:tensorflow:global_step/sec: 15.17
2021-11-27 22:11:16,588 [INFO] tensorflow: global_step/sec: 15.17
INFO:tensorflow:global_step/sec: 14.7169
2021-11-27 22:11:16,723 [INFO] tensorflow: global_step/sec: 14.7169
INFO:tensorflow:global_step/sec: 15.3192
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INFO:tensorflow:global_step/sec: 15.0176
2021-11-27 22:11:16,987 [INFO] tensorflow: global_step/sec: 15.0176
INFO:tensorflow:global_step/sec: 15.1061
2021-11-27 22:11:17,120 [INFO] tensorflow: global_step/sec: 15.1061
INFO:tensorflow:global_step/sec: 14.3527
2021-11-27 22:11:17,259 [INFO] tensorflow: global_step/sec: 14.3527
2021-11-27 22:11:17,260 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 29/120: loss: 0.00113 learning rate: 0.00050 Time taken: 0:00:01.482774 ETA: 0:02:14.932479
INFO:tensorflow:global_step/sec: 14.3115
2021-11-27 22:11:17,399 [INFO] tensorflow: global_step/sec: 14.3115
INFO:tensorflow:global_step/sec: 15.1028
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INFO:tensorflow:global_step/sec: 15.1985
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INFO:tensorflow:global_step/sec: 15.0616
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INFO:tensorflow:global_step/sec: 15.0648
2021-11-27 22:11:17,928 [INFO] tensorflow: global_step/sec: 15.0648
2021-11-27 22:11:17,993 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.826
INFO:tensorflow:global_step/sec: 15.0342
2021-11-27 22:11:18,061 [INFO] tensorflow: global_step/sec: 15.0342
INFO:tensorflow:global_step/sec: 15.4194
2021-11-27 22:11:18,191 [INFO] tensorflow: global_step/sec: 15.4194
INFO:tensorflow:global_step/sec: 14.9949
2021-11-27 22:11:18,324 [INFO] tensorflow: global_step/sec: 14.9949
INFO:tensorflow:global_step/sec: 15.3746
2021-11-27 22:11:18,454 [INFO] tensorflow: global_step/sec: 15.3746
INFO:tensorflow:global_step/sec: 14.5419
2021-11-27 22:11:18,592 [INFO] tensorflow: global_step/sec: 14.5419
INFO:tensorflow:Saving checkpoints for step-660.
2021-11-27 22:11:18,659 [INFO] tensorflow: Saving checkpoints for step-660.
2021-11-27 22:11:20,966 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 1324/1324 [00:00<00:00, 24445.17it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 312/312 [00:00<00:00, 24560.78it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 493/493 [00:00<00:00, 24947.72it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 2957/2957 [00:00<00:00, 26277.66it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 308/308 [00:00<00:00, 24123.20it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 1467/1467 [00:00<00:00, 23906.74it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 5428/5428 [00:00<00:00, 37996.65it/s]
Epoch 30/120
=========================
Validation cost: 0.000636
Mean average_precision (in %): 21.7641
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 36.48
floor 0
palette 4.23729
pillar 46.1714
pushcart 0
rackframe 31.5046
rackshelf 43.4762
wall 34.0071
Median Inference Time: 0.007186
INFO:tensorflow:epoch = 30.0, learning_rate = 0.00049999997, loss = 0.0010661148, step = 660 (11.681 sec)
2021-11-27 22:11:25,716 [INFO] tensorflow: epoch = 30.0, learning_rate = 0.00049999997, loss = 0.0010661148, step = 660 (11.681 sec)
INFO:tensorflow:global_step/sec: 0.280728
2021-11-27 22:11:25,716 [INFO] tensorflow: global_step/sec: 0.280728
2021-11-27 22:11:25,717 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 30/120: loss: 0.00107 learning rate: 0.00050 Time taken: 0:00:08.457013 ETA: 0:12:41.131139
INFO:tensorflow:global_step/sec: 14.6158
2021-11-27 22:11:25,853 [INFO] tensorflow: global_step/sec: 14.6158
INFO:tensorflow:global_step/sec: 15.3631
2021-11-27 22:11:25,983 [INFO] tensorflow: global_step/sec: 15.3631
INFO:tensorflow:global_step/sec: 15.403
2021-11-27 22:11:26,113 [INFO] tensorflow: global_step/sec: 15.403
INFO:tensorflow:global_step/sec: 14.9258
2021-11-27 22:11:26,247 [INFO] tensorflow: global_step/sec: 14.9258
INFO:tensorflow:global_step/sec: 15.5896
2021-11-27 22:11:26,375 [INFO] tensorflow: global_step/sec: 15.5896
INFO:tensorflow:global_step/sec: 15.1391
2021-11-27 22:11:26,508 [INFO] tensorflow: global_step/sec: 15.1391
INFO:tensorflow:global_step/sec: 15.2126
2021-11-27 22:11:26,639 [INFO] tensorflow: global_step/sec: 15.2126
2021-11-27 22:11:26,639 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 11.566
INFO:tensorflow:global_step/sec: 15.1938
2021-11-27 22:11:26,771 [INFO] tensorflow: global_step/sec: 15.1938
INFO:tensorflow:global_step/sec: 15.0149
2021-11-27 22:11:26,904 [INFO] tensorflow: global_step/sec: 15.0149
INFO:tensorflow:global_step/sec: 15.0113
2021-11-27 22:11:27,037 [INFO] tensorflow: global_step/sec: 15.0113
INFO:tensorflow:global_step/sec: 14.3837
2021-11-27 22:11:27,176 [INFO] tensorflow: global_step/sec: 14.3837
2021-11-27 22:11:27,177 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 31/120: loss: 0.00097 learning rate: 0.00050 Time taken: 0:00:01.459213 ETA: 0:02:09.869916
INFO:tensorflow:global_step/sec: 15.0813
2021-11-27 22:11:27,309 [INFO] tensorflow: global_step/sec: 15.0813
INFO:tensorflow:global_step/sec: 15.0764
2021-11-27 22:11:27,441 [INFO] tensorflow: global_step/sec: 15.0764
INFO:tensorflow:global_step/sec: 15.0761
2021-11-27 22:11:27,574 [INFO] tensorflow: global_step/sec: 15.0761
INFO:tensorflow:global_step/sec: 14.6736
2021-11-27 22:11:27,710 [INFO] tensorflow: global_step/sec: 14.6736
INFO:tensorflow:global_step/sec: 15.0927
2021-11-27 22:11:27,843 [INFO] tensorflow: global_step/sec: 15.0927
INFO:tensorflow:global_step/sec: 15.6125
2021-11-27 22:11:27,971 [INFO] tensorflow: global_step/sec: 15.6125
INFO:tensorflow:global_step/sec: 15.2638
2021-11-27 22:11:28,102 [INFO] tensorflow: global_step/sec: 15.2638
INFO:tensorflow:global_step/sec: 14.8265
2021-11-27 22:11:28,237 [INFO] tensorflow: global_step/sec: 14.8265
2021-11-27 22:11:28,304 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.083
INFO:tensorflow:global_step/sec: 15.2819
2021-11-27 22:11:28,368 [INFO] tensorflow: global_step/sec: 15.2819
INFO:tensorflow:global_step/sec: 16.0149
2021-11-27 22:11:28,493 [INFO] tensorflow: global_step/sec: 16.0149
INFO:tensorflow:global_step/sec: 14.1263
2021-11-27 22:11:28,634 [INFO] tensorflow: global_step/sec: 14.1263
2021-11-27 22:11:28,635 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 32/120: loss: 0.00104 learning rate: 0.00050 Time taken: 0:00:01.456547 ETA: 0:02:08.176180
INFO:tensorflow:global_step/sec: 15.3109
2021-11-27 22:11:28,765 [INFO] tensorflow: global_step/sec: 15.3109
INFO:tensorflow:global_step/sec: 14.6735
2021-11-27 22:11:28,901 [INFO] tensorflow: global_step/sec: 14.6735
INFO:tensorflow:global_step/sec: 15.0053
2021-11-27 22:11:29,034 [INFO] tensorflow: global_step/sec: 15.0053
INFO:tensorflow:global_step/sec: 15.0215
2021-11-27 22:11:29,168 [INFO] tensorflow: global_step/sec: 15.0215
INFO:tensorflow:global_step/sec: 15.5507
2021-11-27 22:11:29,296 [INFO] tensorflow: global_step/sec: 15.5507
INFO:tensorflow:global_step/sec: 14.7333
2021-11-27 22:11:29,432 [INFO] tensorflow: global_step/sec: 14.7333
INFO:tensorflow:global_step/sec: 15.1009
2021-11-27 22:11:29,564 [INFO] tensorflow: global_step/sec: 15.1009
INFO:tensorflow:global_step/sec: 14.8423
2021-11-27 22:11:29,699 [INFO] tensorflow: global_step/sec: 14.8423
INFO:tensorflow:global_step/sec: 15.1783
2021-11-27 22:11:29,831 [INFO] tensorflow: global_step/sec: 15.1783
INFO:tensorflow:global_step/sec: 14.637
2021-11-27 22:11:29,968 [INFO] tensorflow: global_step/sec: 14.637
2021-11-27 22:11:29,968 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.100
INFO:tensorflow:global_step/sec: 14.4493
2021-11-27 22:11:30,106 [INFO] tensorflow: global_step/sec: 14.4493
2021-11-27 22:11:30,107 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 33/120: loss: 0.00089 learning rate: 0.00050 Time taken: 0:00:01.468746 ETA: 0:02:07.780897
INFO:tensorflow:global_step/sec: 14.713
2021-11-27 22:11:30,242 [INFO] tensorflow: global_step/sec: 14.713
INFO:tensorflow:global_step/sec: 15.4372
2021-11-27 22:11:30,371 [INFO] tensorflow: global_step/sec: 15.4372
INFO:tensorflow:global_step/sec: 15.6585
2021-11-27 22:11:30,499 [INFO] tensorflow: global_step/sec: 15.6585
INFO:tensorflow:global_step/sec: 15.4361
2021-11-27 22:11:30,629 [INFO] tensorflow: global_step/sec: 15.4361
INFO:tensorflow:global_step/sec: 15.1946
2021-11-27 22:11:30,760 [INFO] tensorflow: global_step/sec: 15.1946
INFO:tensorflow:epoch = 33.5, learning_rate = 0.00049999997, loss = 0.00090900774, step = 737 (5.110 sec)
2021-11-27 22:11:30,826 [INFO] tensorflow: epoch = 33.5, learning_rate = 0.00049999997, loss = 0.00090900774, step = 737 (5.110 sec)
INFO:tensorflow:global_step/sec: 15.2787
2021-11-27 22:11:30,891 [INFO] tensorflow: global_step/sec: 15.2787
INFO:tensorflow:global_step/sec: 15.1715
2021-11-27 22:11:31,023 [INFO] tensorflow: global_step/sec: 15.1715
INFO:tensorflow:global_step/sec: 15.1485
2021-11-27 22:11:31,155 [INFO] tensorflow: global_step/sec: 15.1485
INFO:tensorflow:global_step/sec: 15.1495
2021-11-27 22:11:31,287 [INFO] tensorflow: global_step/sec: 15.1495
INFO:tensorflow:global_step/sec: 14.8119
2021-11-27 22:11:31,422 [INFO] tensorflow: global_step/sec: 14.8119
INFO:tensorflow:global_step/sec: 14.4204
2021-11-27 22:11:31,561 [INFO] tensorflow: global_step/sec: 14.4204
2021-11-27 22:11:31,562 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 34/120: loss: 0.00103 learning rate: 0.00050 Time taken: 0:00:01.453940 ETA: 0:02:05.038812
2021-11-27 22:11:31,627 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.285
INFO:tensorflow:global_step/sec: 15.0805
2021-11-27 22:11:31,693 [INFO] tensorflow: global_step/sec: 15.0805
INFO:tensorflow:global_step/sec: 15.137
2021-11-27 22:11:31,826 [INFO] tensorflow: global_step/sec: 15.137
INFO:tensorflow:global_step/sec: 14.6606
2021-11-27 22:11:31,962 [INFO] tensorflow: global_step/sec: 14.6606
INFO:tensorflow:global_step/sec: 14.9212
2021-11-27 22:11:32,096 [INFO] tensorflow: global_step/sec: 14.9212
INFO:tensorflow:global_step/sec: 15.3908
2021-11-27 22:11:32,226 [INFO] tensorflow: global_step/sec: 15.3908
INFO:tensorflow:global_step/sec: 15.2564
2021-11-27 22:11:32,357 [INFO] tensorflow: global_step/sec: 15.2564
INFO:tensorflow:global_step/sec: 15.2172
2021-11-27 22:11:32,489 [INFO] tensorflow: global_step/sec: 15.2172
INFO:tensorflow:global_step/sec: 15.2882
2021-11-27 22:11:32,619 [INFO] tensorflow: global_step/sec: 15.2882
INFO:tensorflow:global_step/sec: 14.9088
2021-11-27 22:11:32,753 [INFO] tensorflow: global_step/sec: 14.9088
INFO:tensorflow:global_step/sec: 15.0959
2021-11-27 22:11:32,886 [INFO] tensorflow: global_step/sec: 15.0959
INFO:tensorflow:global_step/sec: 13.8828
2021-11-27 22:11:33,030 [INFO] tensorflow: global_step/sec: 13.8828
2021-11-27 22:11:33,031 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 35/120: loss: 0.00098 learning rate: 0.00050 Time taken: 0:00:01.464580 ETA: 0:02:04.489325
INFO:tensorflow:global_step/sec: 14.9529
2021-11-27 22:11:33,164 [INFO] tensorflow: global_step/sec: 14.9529
INFO:tensorflow:global_step/sec: 15.2116
2021-11-27 22:11:33,295 [INFO] tensorflow: global_step/sec: 15.2116
2021-11-27 22:11:33,296 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.932
INFO:tensorflow:global_step/sec: 15.5088
2021-11-27 22:11:33,424 [INFO] tensorflow: global_step/sec: 15.5088
INFO:tensorflow:global_step/sec: 15.1949
2021-11-27 22:11:33,556 [INFO] tensorflow: global_step/sec: 15.1949
INFO:tensorflow:global_step/sec: 15.218
2021-11-27 22:11:33,687 [INFO] tensorflow: global_step/sec: 15.218
INFO:tensorflow:global_step/sec: 14.9059
2021-11-27 22:11:33,821 [INFO] tensorflow: global_step/sec: 14.9059
INFO:tensorflow:global_step/sec: 15.2427
2021-11-27 22:11:33,953 [INFO] tensorflow: global_step/sec: 15.2427
INFO:tensorflow:global_step/sec: 15.2945
2021-11-27 22:11:34,083 [INFO] tensorflow: global_step/sec: 15.2945
INFO:tensorflow:global_step/sec: 14.6933
2021-11-27 22:11:34,220 [INFO] tensorflow: global_step/sec: 14.6933
INFO:tensorflow:global_step/sec: 15.1993
2021-11-27 22:11:34,351 [INFO] tensorflow: global_step/sec: 15.1993
INFO:tensorflow:global_step/sec: 14.3273
2021-11-27 22:11:34,491 [INFO] tensorflow: global_step/sec: 14.3273
2021-11-27 22:11:34,492 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 36/120: loss: 0.00096 learning rate: 0.00050 Time taken: 0:00:01.460090 ETA: 0:02:02.647593
INFO:tensorflow:global_step/sec: 14.8868
2021-11-27 22:11:34,625 [INFO] tensorflow: global_step/sec: 14.8868
INFO:tensorflow:global_step/sec: 14.8503
2021-11-27 22:11:34,760 [INFO] tensorflow: global_step/sec: 14.8503
INFO:tensorflow:global_step/sec: 14.9171
2021-11-27 22:11:34,894 [INFO] tensorflow: global_step/sec: 14.9171
2021-11-27 22:11:34,961 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.066
INFO:tensorflow:global_step/sec: 15.0057
2021-11-27 22:11:35,027 [INFO] tensorflow: global_step/sec: 15.0057
INFO:tensorflow:global_step/sec: 14.8709
2021-11-27 22:11:35,162 [INFO] tensorflow: global_step/sec: 14.8709
INFO:tensorflow:global_step/sec: 14.7456
2021-11-27 22:11:35,297 [INFO] tensorflow: global_step/sec: 14.7456
INFO:tensorflow:global_step/sec: 15.0414
2021-11-27 22:11:35,430 [INFO] tensorflow: global_step/sec: 15.0414
INFO:tensorflow:global_step/sec: 15.4691
2021-11-27 22:11:35,559 [INFO] tensorflow: global_step/sec: 15.4691
INFO:tensorflow:global_step/sec: 15.559
2021-11-27 22:11:35,688 [INFO] tensorflow: global_step/sec: 15.559
INFO:tensorflow:global_step/sec: 14.9614
2021-11-27 22:11:35,822 [INFO] tensorflow: global_step/sec: 14.9614
INFO:tensorflow:epoch = 37.0, learning_rate = 0.00049999997, loss = 0.0008655512, step = 814 (5.134 sec)
2021-11-27 22:11:35,959 [INFO] tensorflow: epoch = 37.0, learning_rate = 0.00049999997, loss = 0.0008655512, step = 814 (5.134 sec)
INFO:tensorflow:global_step/sec: 14.4501
2021-11-27 22:11:35,960 [INFO] tensorflow: global_step/sec: 14.4501
2021-11-27 22:11:35,961 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 37/120: loss: 0.00087 learning rate: 0.00050 Time taken: 0:00:01.467804 ETA: 0:02:01.827708
INFO:tensorflow:global_step/sec: 15.2799
2021-11-27 22:11:36,091 [INFO] tensorflow: global_step/sec: 15.2799
INFO:tensorflow:global_step/sec: 14.9947
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INFO:tensorflow:global_step/sec: 15.4313
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INFO:tensorflow:global_step/sec: 15.3616
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INFO:tensorflow:global_step/sec: 15.0717
2021-11-27 22:11:36,617 [INFO] tensorflow: global_step/sec: 15.0717
2021-11-27 22:11:36,618 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.387
INFO:tensorflow:global_step/sec: 15.3582
2021-11-27 22:11:36,747 [INFO] tensorflow: global_step/sec: 15.3582
INFO:tensorflow:global_step/sec: 15.1001
2021-11-27 22:11:36,880 [INFO] tensorflow: global_step/sec: 15.1001
INFO:tensorflow:global_step/sec: 15.1579
2021-11-27 22:11:37,012 [INFO] tensorflow: global_step/sec: 15.1579
INFO:tensorflow:global_step/sec: 14.9862
2021-11-27 22:11:37,145 [INFO] tensorflow: global_step/sec: 14.9862
INFO:tensorflow:global_step/sec: 15.1072
2021-11-27 22:11:37,277 [INFO] tensorflow: global_step/sec: 15.1072
INFO:tensorflow:global_step/sec: 13.8528
2021-11-27 22:11:37,422 [INFO] tensorflow: global_step/sec: 13.8528
2021-11-27 22:11:37,423 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 38/120: loss: 0.00094 learning rate: 0.00050 Time taken: 0:00:01.461972 ETA: 0:01:59.881704
INFO:tensorflow:global_step/sec: 14.9911
2021-11-27 22:11:37,555 [INFO] tensorflow: global_step/sec: 14.9911
INFO:tensorflow:global_step/sec: 14.7256
2021-11-27 22:11:37,691 [INFO] tensorflow: global_step/sec: 14.7256
INFO:tensorflow:global_step/sec: 15.3151
2021-11-27 22:11:37,822 [INFO] tensorflow: global_step/sec: 15.3151
INFO:tensorflow:global_step/sec: 15.5691
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INFO:tensorflow:global_step/sec: 15.3719
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INFO:tensorflow:global_step/sec: 14.9469
2021-11-27 22:11:38,214 [INFO] tensorflow: global_step/sec: 14.9469
2021-11-27 22:11:38,280 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.161
INFO:tensorflow:global_step/sec: 15.1462
2021-11-27 22:11:38,346 [INFO] tensorflow: global_step/sec: 15.1462
INFO:tensorflow:global_step/sec: 15.398
2021-11-27 22:11:38,476 [INFO] tensorflow: global_step/sec: 15.398
INFO:tensorflow:global_step/sec: 14.9902
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INFO:tensorflow:global_step/sec: 15.1598
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INFO:tensorflow:global_step/sec: 14.5109
2021-11-27 22:11:38,879 [INFO] tensorflow: global_step/sec: 14.5109
2021-11-27 22:11:38,880 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 39/120: loss: 0.00096 learning rate: 0.00050 Time taken: 0:00:01.455826 ETA: 0:01:57.921890
INFO:tensorflow:global_step/sec: 14.7179
2021-11-27 22:11:39,015 [INFO] tensorflow: global_step/sec: 14.7179
INFO:tensorflow:global_step/sec: 15.1438
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INFO:tensorflow:global_step/sec: 15.1448
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INFO:tensorflow:global_step/sec: 15.0691
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INFO:tensorflow:global_step/sec: 15.0519
2021-11-27 22:11:39,545 [INFO] tensorflow: global_step/sec: 15.0519
INFO:tensorflow:global_step/sec: 15.5687
2021-11-27 22:11:39,673 [INFO] tensorflow: global_step/sec: 15.5687
INFO:tensorflow:global_step/sec: 15.4855
2021-11-27 22:11:39,802 [INFO] tensorflow: global_step/sec: 15.4855
INFO:tensorflow:global_step/sec: 15.1255
2021-11-27 22:11:39,934 [INFO] tensorflow: global_step/sec: 15.1255
2021-11-27 22:11:39,935 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.433
INFO:tensorflow:global_step/sec: 14.7001
2021-11-27 22:11:40,071 [INFO] tensorflow: global_step/sec: 14.7001
INFO:tensorflow:global_step/sec: 15.2318
2021-11-27 22:11:40,202 [INFO] tensorflow: global_step/sec: 15.2318
INFO:tensorflow:Saving checkpoints for step-880.
2021-11-27 22:11:40,266 [INFO] tensorflow: Saving checkpoints for step-880.
2021-11-27 22:11:42,590 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 1222/1222 [00:00<00:00, 23534.73it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 155/155 [00:00<00:00, 24321.63it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 545/545 [00:00<00:00, 23867.10it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 2017/2017 [00:00<00:00, 27095.91it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 459/459 [00:00<00:00, 24472.90it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 1452/1452 [00:00<00:00, 23857.51it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 3675/3675 [00:00<00:00, 38397.99it/s]
Epoch 40/120
=========================
Validation cost: 0.000671
Mean average_precision (in %): 21.1592
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 21.043
floor 0
palette 5.8561
pillar 44.3434
pushcart 0
rackframe 34.715
rackshelf 50.6217
wall 33.8539
Median Inference Time: 0.007315
INFO:tensorflow:epoch = 40.0, learning_rate = 0.00049999997, loss = 0.0009999337, step = 880 (10.303 sec)
2021-11-27 22:11:46,263 [INFO] tensorflow: epoch = 40.0, learning_rate = 0.00049999997, loss = 0.0009999337, step = 880 (10.303 sec)
INFO:tensorflow:global_step/sec: 0.329935
2021-11-27 22:11:46,264 [INFO] tensorflow: global_step/sec: 0.329935
2021-11-27 22:11:46,265 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 40/120: loss: 0.00100 learning rate: 0.00050 Time taken: 0:00:07.381091 ETA: 0:09:50.487289
INFO:tensorflow:global_step/sec: 15.1789
2021-11-27 22:11:46,395 [INFO] tensorflow: global_step/sec: 15.1789
INFO:tensorflow:global_step/sec: 15.2989
2021-11-27 22:11:46,526 [INFO] tensorflow: global_step/sec: 15.2989
INFO:tensorflow:global_step/sec: 15.0682
2021-11-27 22:11:46,659 [INFO] tensorflow: global_step/sec: 15.0682
INFO:tensorflow:global_step/sec: 15.0943
2021-11-27 22:11:46,791 [INFO] tensorflow: global_step/sec: 15.0943
INFO:tensorflow:global_step/sec: 15.1207
2021-11-27 22:11:46,924 [INFO] tensorflow: global_step/sec: 15.1207
INFO:tensorflow:global_step/sec: 14.9446
2021-11-27 22:11:47,057 [INFO] tensorflow: global_step/sec: 14.9446
INFO:tensorflow:global_step/sec: 15.088
2021-11-27 22:11:47,190 [INFO] tensorflow: global_step/sec: 15.088
INFO:tensorflow:global_step/sec: 15.0426
2021-11-27 22:11:47,323 [INFO] tensorflow: global_step/sec: 15.0426
INFO:tensorflow:global_step/sec: 14.9005
2021-11-27 22:11:47,457 [INFO] tensorflow: global_step/sec: 14.9005
2021-11-27 22:11:47,524 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 13.179
INFO:tensorflow:global_step/sec: 15.1584
2021-11-27 22:11:47,589 [INFO] tensorflow: global_step/sec: 15.1584
INFO:tensorflow:global_step/sec: 14.6073
2021-11-27 22:11:47,726 [INFO] tensorflow: global_step/sec: 14.6073
2021-11-27 22:11:47,727 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 41/120: loss: 0.00084 learning rate: 0.00050 Time taken: 0:00:01.464972 ETA: 0:01:55.732808
INFO:tensorflow:global_step/sec: 15.282
2021-11-27 22:11:47,857 [INFO] tensorflow: global_step/sec: 15.282
INFO:tensorflow:global_step/sec: 15.168
2021-11-27 22:11:47,989 [INFO] tensorflow: global_step/sec: 15.168
INFO:tensorflow:global_step/sec: 15.1081
2021-11-27 22:11:48,121 [INFO] tensorflow: global_step/sec: 15.1081
INFO:tensorflow:global_step/sec: 15.0112
2021-11-27 22:11:48,254 [INFO] tensorflow: global_step/sec: 15.0112
INFO:tensorflow:global_step/sec: 14.9168
2021-11-27 22:11:48,388 [INFO] tensorflow: global_step/sec: 14.9168
INFO:tensorflow:global_step/sec: 15.2759
2021-11-27 22:11:48,519 [INFO] tensorflow: global_step/sec: 15.2759
INFO:tensorflow:global_step/sec: 15.4619
2021-11-27 22:11:48,649 [INFO] tensorflow: global_step/sec: 15.4619
INFO:tensorflow:global_step/sec: 15.2158
2021-11-27 22:11:48,780 [INFO] tensorflow: global_step/sec: 15.2158
INFO:tensorflow:global_step/sec: 15.3261
2021-11-27 22:11:48,911 [INFO] tensorflow: global_step/sec: 15.3261
INFO:tensorflow:global_step/sec: 15.0754
2021-11-27 22:11:49,043 [INFO] tensorflow: global_step/sec: 15.0754
INFO:tensorflow:global_step/sec: 14.3537
2021-11-27 22:11:49,183 [INFO] tensorflow: global_step/sec: 14.3537
2021-11-27 22:11:49,184 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 42/120: loss: 0.00100 learning rate: 0.00050 Time taken: 0:00:01.452587 ETA: 0:01:53.301815
2021-11-27 22:11:49,184 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.245
INFO:tensorflow:global_step/sec: 14.9327
2021-11-27 22:11:49,317 [INFO] tensorflow: global_step/sec: 14.9327
INFO:tensorflow:global_step/sec: 15.3756
2021-11-27 22:11:49,447 [INFO] tensorflow: global_step/sec: 15.3756
INFO:tensorflow:global_step/sec: 15.3226
2021-11-27 22:11:49,577 [INFO] tensorflow: global_step/sec: 15.3226
INFO:tensorflow:global_step/sec: 15.5236
2021-11-27 22:11:49,706 [INFO] tensorflow: global_step/sec: 15.5236
INFO:tensorflow:global_step/sec: 15.1194
2021-11-27 22:11:49,838 [INFO] tensorflow: global_step/sec: 15.1194
INFO:tensorflow:global_step/sec: 15.2439
2021-11-27 22:11:49,970 [INFO] tensorflow: global_step/sec: 15.2439
INFO:tensorflow:global_step/sec: 14.6351
2021-11-27 22:11:50,106 [INFO] tensorflow: global_step/sec: 14.6351
INFO:tensorflow:global_step/sec: 14.9455
2021-11-27 22:11:50,240 [INFO] tensorflow: global_step/sec: 14.9455
INFO:tensorflow:global_step/sec: 14.9625
2021-11-27 22:11:50,374 [INFO] tensorflow: global_step/sec: 14.9625
INFO:tensorflow:global_step/sec: 15.0503
2021-11-27 22:11:50,507 [INFO] tensorflow: global_step/sec: 15.0503
INFO:tensorflow:global_step/sec: 14.0792
2021-11-27 22:11:50,649 [INFO] tensorflow: global_step/sec: 14.0792
2021-11-27 22:11:50,649 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 43/120: loss: 0.00087 learning rate: 0.00050 Time taken: 0:00:01.463979 ETA: 0:01:52.726402
INFO:tensorflow:global_step/sec: 15.0479
2021-11-27 22:11:50,782 [INFO] tensorflow: global_step/sec: 15.0479
2021-11-27 22:11:50,848 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.112
INFO:tensorflow:global_step/sec: 15.1267
2021-11-27 22:11:50,914 [INFO] tensorflow: global_step/sec: 15.1267
INFO:tensorflow:global_step/sec: 15.4693
2021-11-27 22:11:51,043 [INFO] tensorflow: global_step/sec: 15.4693
INFO:tensorflow:global_step/sec: 14.9862
2021-11-27 22:11:51,177 [INFO] tensorflow: global_step/sec: 14.9862
INFO:tensorflow:global_step/sec: 14.6079
2021-11-27 22:11:51,313 [INFO] tensorflow: global_step/sec: 14.6079
INFO:tensorflow:epoch = 43.5, learning_rate = 0.00049999997, loss = 0.00081038236, step = 957 (5.117 sec)
2021-11-27 22:11:51,380 [INFO] tensorflow: epoch = 43.5, learning_rate = 0.00049999997, loss = 0.00081038236, step = 957 (5.117 sec)
INFO:tensorflow:global_step/sec: 15.1928
2021-11-27 22:11:51,445 [INFO] tensorflow: global_step/sec: 15.1928
INFO:tensorflow:global_step/sec: 14.8257
2021-11-27 22:11:51,580 [INFO] tensorflow: global_step/sec: 14.8257
INFO:tensorflow:global_step/sec: 15.0792
2021-11-27 22:11:51,713 [INFO] tensorflow: global_step/sec: 15.0792
INFO:tensorflow:global_step/sec: 15.1708
2021-11-27 22:11:51,844 [INFO] tensorflow: global_step/sec: 15.1708
INFO:tensorflow:global_step/sec: 15.0073
2021-11-27 22:11:51,978 [INFO] tensorflow: global_step/sec: 15.0073
INFO:tensorflow:global_step/sec: 13.7614
2021-11-27 22:11:52,123 [INFO] tensorflow: global_step/sec: 13.7614
2021-11-27 22:11:52,124 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 44/120: loss: 0.00098 learning rate: 0.00050 Time taken: 0:00:01.471652 ETA: 0:01:51.845554
INFO:tensorflow:global_step/sec: 15.1739
2021-11-27 22:11:52,255 [INFO] tensorflow: global_step/sec: 15.1739
INFO:tensorflow:global_step/sec: 14.9989
2021-11-27 22:11:52,388 [INFO] tensorflow: global_step/sec: 14.9989
INFO:tensorflow:global_step/sec: 15.459
2021-11-27 22:11:52,518 [INFO] tensorflow: global_step/sec: 15.459
2021-11-27 22:11:52,518 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.867
INFO:tensorflow:global_step/sec: 14.8956
2021-11-27 22:11:52,652 [INFO] tensorflow: global_step/sec: 14.8956
INFO:tensorflow:global_step/sec: 15.1938
2021-11-27 22:11:52,783 [INFO] tensorflow: global_step/sec: 15.1938
INFO:tensorflow:global_step/sec: 15.0278
2021-11-27 22:11:52,917 [INFO] tensorflow: global_step/sec: 15.0278
INFO:tensorflow:global_step/sec: 15.5823
2021-11-27 22:11:53,045 [INFO] tensorflow: global_step/sec: 15.5823
INFO:tensorflow:global_step/sec: 15.2012
2021-11-27 22:11:53,176 [INFO] tensorflow: global_step/sec: 15.2012
INFO:tensorflow:global_step/sec: 15.6249
2021-11-27 22:11:53,304 [INFO] tensorflow: global_step/sec: 15.6249
INFO:tensorflow:global_step/sec: 15.1907
2021-11-27 22:11:53,436 [INFO] tensorflow: global_step/sec: 15.1907
INFO:tensorflow:global_step/sec: 14.448
2021-11-27 22:11:53,575 [INFO] tensorflow: global_step/sec: 14.448
2021-11-27 22:11:53,576 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 45/120: loss: 0.00079 learning rate: 0.00050 Time taken: 0:00:01.451916 ETA: 0:01:48.893681
INFO:tensorflow:global_step/sec: 14.8185
2021-11-27 22:11:53,710 [INFO] tensorflow: global_step/sec: 14.8185
INFO:tensorflow:global_step/sec: 15.1671
2021-11-27 22:11:53,841 [INFO] tensorflow: global_step/sec: 15.1671
INFO:tensorflow:global_step/sec: 14.8818
2021-11-27 22:11:53,976 [INFO] tensorflow: global_step/sec: 14.8818
INFO:tensorflow:global_step/sec: 14.9848
2021-11-27 22:11:54,109 [INFO] tensorflow: global_step/sec: 14.9848
2021-11-27 22:11:54,174 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.394
INFO:tensorflow:global_step/sec: 15.5096
2021-11-27 22:11:54,238 [INFO] tensorflow: global_step/sec: 15.5096
INFO:tensorflow:global_step/sec: 14.907
2021-11-27 22:11:54,372 [INFO] tensorflow: global_step/sec: 14.907
INFO:tensorflow:global_step/sec: 15.0075
2021-11-27 22:11:54,506 [INFO] tensorflow: global_step/sec: 15.0075
INFO:tensorflow:global_step/sec: 14.7377
2021-11-27 22:11:54,641 [INFO] tensorflow: global_step/sec: 14.7377
INFO:tensorflow:global_step/sec: 15.2918
2021-11-27 22:11:54,772 [INFO] tensorflow: global_step/sec: 15.2918
INFO:tensorflow:global_step/sec: 14.9758
2021-11-27 22:11:54,906 [INFO] tensorflow: global_step/sec: 14.9758
INFO:tensorflow:global_step/sec: 14.3312
2021-11-27 22:11:55,045 [INFO] tensorflow: global_step/sec: 14.3312
2021-11-27 22:11:55,046 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 46/120: loss: 0.00084 learning rate: 0.00050 Time taken: 0:00:01.467359 ETA: 0:01:48.584553
INFO:tensorflow:global_step/sec: 15.3426
2021-11-27 22:11:55,176 [INFO] tensorflow: global_step/sec: 15.3426
INFO:tensorflow:global_step/sec: 14.9345
2021-11-27 22:11:55,309 [INFO] tensorflow: global_step/sec: 14.9345
INFO:tensorflow:global_step/sec: 15.1861
2021-11-27 22:11:55,441 [INFO] tensorflow: global_step/sec: 15.1861
INFO:tensorflow:global_step/sec: 15.0804
2021-11-27 22:11:55,574 [INFO] tensorflow: global_step/sec: 15.0804
INFO:tensorflow:global_step/sec: 15.0088
2021-11-27 22:11:55,707 [INFO] tensorflow: global_step/sec: 15.0088
INFO:tensorflow:global_step/sec: 15.1252
2021-11-27 22:11:55,839 [INFO] tensorflow: global_step/sec: 15.1252
2021-11-27 22:11:55,840 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.043
INFO:tensorflow:global_step/sec: 15.0408
2021-11-27 22:11:55,972 [INFO] tensorflow: global_step/sec: 15.0408
INFO:tensorflow:global_step/sec: 15.2532
2021-11-27 22:11:56,103 [INFO] tensorflow: global_step/sec: 15.2532
INFO:tensorflow:global_step/sec: 15.1086
2021-11-27 22:11:56,236 [INFO] tensorflow: global_step/sec: 15.1086
INFO:tensorflow:global_step/sec: 14.5805
2021-11-27 22:11:56,373 [INFO] tensorflow: global_step/sec: 14.5805
INFO:tensorflow:epoch = 47.0, learning_rate = 0.00049999997, loss = 0.0009138873, step = 1034 (5.125 sec)
2021-11-27 22:11:56,504 [INFO] tensorflow: epoch = 47.0, learning_rate = 0.00049999997, loss = 0.0009138873, step = 1034 (5.125 sec)
INFO:tensorflow:global_step/sec: 15.1393
2021-11-27 22:11:56,505 [INFO] tensorflow: global_step/sec: 15.1393
2021-11-27 22:11:56,506 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 47/120: loss: 0.00091 learning rate: 0.00050 Time taken: 0:00:01.462579 ETA: 0:01:46.768250
INFO:tensorflow:global_step/sec: 15.2855
2021-11-27 22:11:56,636 [INFO] tensorflow: global_step/sec: 15.2855
INFO:tensorflow:global_step/sec: 15.0066
2021-11-27 22:11:56,769 [INFO] tensorflow: global_step/sec: 15.0066
INFO:tensorflow:global_step/sec: 14.7333
2021-11-27 22:11:56,905 [INFO] tensorflow: global_step/sec: 14.7333
INFO:tensorflow:global_step/sec: 15.3987
2021-11-27 22:11:57,035 [INFO] tensorflow: global_step/sec: 15.3987
INFO:tensorflow:global_step/sec: 15.3049
2021-11-27 22:11:57,165 [INFO] tensorflow: global_step/sec: 15.3049
INFO:tensorflow:global_step/sec: 15.299
2021-11-27 22:11:57,296 [INFO] tensorflow: global_step/sec: 15.299
INFO:tensorflow:global_step/sec: 14.9759
2021-11-27 22:11:57,430 [INFO] tensorflow: global_step/sec: 14.9759
2021-11-27 22:11:57,496 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.401
INFO:tensorflow:global_step/sec: 14.9869
2021-11-27 22:11:57,563 [INFO] tensorflow: global_step/sec: 14.9869
INFO:tensorflow:global_step/sec: 15.1593
2021-11-27 22:11:57,695 [INFO] tensorflow: global_step/sec: 15.1593
INFO:tensorflow:global_step/sec: 15.1397
2021-11-27 22:11:57,827 [INFO] tensorflow: global_step/sec: 15.1397
INFO:tensorflow:global_step/sec: 14.5672
2021-11-27 22:11:57,965 [INFO] tensorflow: global_step/sec: 14.5672
2021-11-27 22:11:57,965 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 48/120: loss: 0.00092 learning rate: 0.00050 Time taken: 0:00:01.456469 ETA: 0:01:44.865772
INFO:tensorflow:global_step/sec: 15.2014
2021-11-27 22:11:58,096 [INFO] tensorflow: global_step/sec: 15.2014
INFO:tensorflow:global_step/sec: 15.332
2021-11-27 22:11:58,227 [INFO] tensorflow: global_step/sec: 15.332
INFO:tensorflow:global_step/sec: 15.3564
2021-11-27 22:11:58,357 [INFO] tensorflow: global_step/sec: 15.3564
INFO:tensorflow:global_step/sec: 15.179
2021-11-27 22:11:58,489 [INFO] tensorflow: global_step/sec: 15.179
INFO:tensorflow:global_step/sec: 14.712
2021-11-27 22:11:58,624 [INFO] tensorflow: global_step/sec: 14.712
INFO:tensorflow:global_step/sec: 14.6408
2021-11-27 22:11:58,761 [INFO] tensorflow: global_step/sec: 14.6408
INFO:tensorflow:global_step/sec: 15.097
2021-11-27 22:11:58,894 [INFO] tensorflow: global_step/sec: 15.097
INFO:tensorflow:global_step/sec: 15.097
2021-11-27 22:11:59,026 [INFO] tensorflow: global_step/sec: 15.097
INFO:tensorflow:global_step/sec: 15.2985
2021-11-27 22:11:59,157 [INFO] tensorflow: global_step/sec: 15.2985
2021-11-27 22:11:59,158 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.190
INFO:tensorflow:global_step/sec: 14.9426
2021-11-27 22:11:59,291 [INFO] tensorflow: global_step/sec: 14.9426
INFO:tensorflow:global_step/sec: 14.4123
2021-11-27 22:11:59,429 [INFO] tensorflow: global_step/sec: 14.4123
2021-11-27 22:11:59,430 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 49/120: loss: 0.00074 learning rate: 0.00050 Time taken: 0:00:01.462435 ETA: 0:01:43.832852
INFO:tensorflow:global_step/sec: 15.0344
2021-11-27 22:11:59,562 [INFO] tensorflow: global_step/sec: 15.0344
INFO:tensorflow:global_step/sec: 15.1516
2021-11-27 22:11:59,694 [INFO] tensorflow: global_step/sec: 15.1516
INFO:tensorflow:global_step/sec: 15.2192
2021-11-27 22:11:59,826 [INFO] tensorflow: global_step/sec: 15.2192
INFO:tensorflow:global_step/sec: 15.3521
2021-11-27 22:11:59,956 [INFO] tensorflow: global_step/sec: 15.3521
INFO:tensorflow:global_step/sec: 14.5958
2021-11-27 22:12:00,093 [INFO] tensorflow: global_step/sec: 14.5958
INFO:tensorflow:global_step/sec: 15.7292
2021-11-27 22:12:00,220 [INFO] tensorflow: global_step/sec: 15.7292
INFO:tensorflow:global_step/sec: 14.8774
2021-11-27 22:12:00,355 [INFO] tensorflow: global_step/sec: 14.8774
INFO:tensorflow:global_step/sec: 14.8267
2021-11-27 22:12:00,490 [INFO] tensorflow: global_step/sec: 14.8267
INFO:tensorflow:global_step/sec: 15.1096
2021-11-27 22:12:00,622 [INFO] tensorflow: global_step/sec: 15.1096
INFO:tensorflow:global_step/sec: 14.847
2021-11-27 22:12:00,757 [INFO] tensorflow: global_step/sec: 14.847
INFO:tensorflow:Saving checkpoints for step-1100.
2021-11-27 22:12:00,823 [INFO] tensorflow: Saving checkpoints for step-1100.
WARNING:tensorflow:Ignoring: /tmp/tmp0zria95g; No such file or directory
2021-11-27 22:12:00,910 [WARNING] tensorflow: Ignoring: /tmp/tmp0zria95g; No such file or directory
2021-11-27 22:12:03,172 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 801/801 [00:00<00:00, 21408.10it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 90/90 [00:00<00:00, 23497.50it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 239/239 [00:00<00:00, 24605.16it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 1302/1302 [00:00<00:00, 26501.78it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 303/303 [00:00<00:00, 24410.78it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 965/965 [00:00<00:00, 24058.20it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 3685/3685 [00:00<00:00, 36470.23it/s]
Epoch 50/120
=========================
Validation cost: 0.000479
Mean average_precision (in %): 24.4442
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 41.4886
floor 0
palette 4.98866
pillar 53.2444
pushcart 0
rackframe 39.0402
rackshelf 48.8277
wall 32.4083
Median Inference Time: 0.007343
2021-11-27 22:12:06,058 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 14.492
INFO:tensorflow:epoch = 50.0, learning_rate = 0.00049999997, loss = 0.0010649569, step = 1100 (9.622 sec)
2021-11-27 22:12:06,126 [INFO] tensorflow: epoch = 50.0, learning_rate = 0.00049999997, loss = 0.0010649569, step = 1100 (9.622 sec)
INFO:tensorflow:global_step/sec: 0.37245
2021-11-27 22:12:06,127 [INFO] tensorflow: global_step/sec: 0.37245
2021-11-27 22:12:06,127 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 50/120: loss: 0.00106 learning rate: 0.00050 Time taken: 0:00:06.694914 ETA: 0:07:48.643970
INFO:tensorflow:global_step/sec: 15.2352
2021-11-27 22:12:06,258 [INFO] tensorflow: global_step/sec: 15.2352
INFO:tensorflow:global_step/sec: 15.3075
2021-11-27 22:12:06,388 [INFO] tensorflow: global_step/sec: 15.3075
INFO:tensorflow:global_step/sec: 15.6479
2021-11-27 22:12:06,516 [INFO] tensorflow: global_step/sec: 15.6479
INFO:tensorflow:global_step/sec: 14.819
2021-11-27 22:12:06,651 [INFO] tensorflow: global_step/sec: 14.819
INFO:tensorflow:global_step/sec: 14.9812
2021-11-27 22:12:06,785 [INFO] tensorflow: global_step/sec: 14.9812
INFO:tensorflow:global_step/sec: 14.6868
2021-11-27 22:12:06,921 [INFO] tensorflow: global_step/sec: 14.6868
INFO:tensorflow:global_step/sec: 15.2648
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INFO:tensorflow:global_step/sec: 14.7162
2021-11-27 22:12:07,188 [INFO] tensorflow: global_step/sec: 14.7162
INFO:tensorflow:global_step/sec: 15.59
2021-11-27 22:12:07,316 [INFO] tensorflow: global_step/sec: 15.59
INFO:tensorflow:global_step/sec: 15.6763
2021-11-27 22:12:07,444 [INFO] tensorflow: global_step/sec: 15.6763
INFO:tensorflow:global_step/sec: 14.728
2021-11-27 22:12:07,579 [INFO] tensorflow: global_step/sec: 14.728
2021-11-27 22:12:07,580 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 51/120: loss: 0.00083 learning rate: 0.00050 Time taken: 0:00:01.450180 ETA: 0:01:40.062391
INFO:tensorflow:global_step/sec: 14.9589
2021-11-27 22:12:07,713 [INFO] tensorflow: global_step/sec: 14.9589
2021-11-27 22:12:07,714 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.457
INFO:tensorflow:global_step/sec: 15.3706
2021-11-27 22:12:07,843 [INFO] tensorflow: global_step/sec: 15.3706
INFO:tensorflow:global_step/sec: 15.2981
2021-11-27 22:12:07,974 [INFO] tensorflow: global_step/sec: 15.2981
INFO:tensorflow:global_step/sec: 14.7912
2021-11-27 22:12:08,109 [INFO] tensorflow: global_step/sec: 14.7912
INFO:tensorflow:global_step/sec: 14.6076
2021-11-27 22:12:08,246 [INFO] tensorflow: global_step/sec: 14.6076
INFO:tensorflow:global_step/sec: 15.0434
2021-11-27 22:12:08,379 [INFO] tensorflow: global_step/sec: 15.0434
INFO:tensorflow:global_step/sec: 15.4711
2021-11-27 22:12:08,508 [INFO] tensorflow: global_step/sec: 15.4711
INFO:tensorflow:global_step/sec: 15.2914
2021-11-27 22:12:08,639 [INFO] tensorflow: global_step/sec: 15.2914
INFO:tensorflow:global_step/sec: 15.0977
2021-11-27 22:12:08,772 [INFO] tensorflow: global_step/sec: 15.0977
INFO:tensorflow:global_step/sec: 15.1596
2021-11-27 22:12:08,904 [INFO] tensorflow: global_step/sec: 15.1596
INFO:tensorflow:global_step/sec: 13.9233
2021-11-27 22:12:09,047 [INFO] tensorflow: global_step/sec: 13.9233
2021-11-27 22:12:09,048 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 52/120: loss: 0.00088 learning rate: 0.00050 Time taken: 0:00:01.466222 ETA: 0:01:39.703099
INFO:tensorflow:global_step/sec: 15.4908
2021-11-27 22:12:09,176 [INFO] tensorflow: global_step/sec: 15.4908
INFO:tensorflow:global_step/sec: 14.9332
2021-11-27 22:12:09,310 [INFO] tensorflow: global_step/sec: 14.9332
2021-11-27 22:12:09,375 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.220
INFO:tensorflow:global_step/sec: 15.2218
2021-11-27 22:12:09,442 [INFO] tensorflow: global_step/sec: 15.2218
INFO:tensorflow:global_step/sec: 14.9859
2021-11-27 22:12:09,575 [INFO] tensorflow: global_step/sec: 14.9859
INFO:tensorflow:global_step/sec: 15.4823
2021-11-27 22:12:09,704 [INFO] tensorflow: global_step/sec: 15.4823
INFO:tensorflow:global_step/sec: 15.6199
2021-11-27 22:12:09,832 [INFO] tensorflow: global_step/sec: 15.6199
INFO:tensorflow:global_step/sec: 15.9041
2021-11-27 22:12:09,958 [INFO] tensorflow: global_step/sec: 15.9041
INFO:tensorflow:global_step/sec: 14.8429
2021-11-27 22:12:10,093 [INFO] tensorflow: global_step/sec: 14.8429
INFO:tensorflow:global_step/sec: 15.4095
2021-11-27 22:12:10,223 [INFO] tensorflow: global_step/sec: 15.4095
INFO:tensorflow:global_step/sec: 15.2428
2021-11-27 22:12:10,354 [INFO] tensorflow: global_step/sec: 15.2428
INFO:tensorflow:global_step/sec: 14.2094
2021-11-27 22:12:10,495 [INFO] tensorflow: global_step/sec: 14.2094
2021-11-27 22:12:10,496 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 53/120: loss: 0.00078 learning rate: 0.00050 Time taken: 0:00:01.447644 ETA: 0:01:36.992132
INFO:tensorflow:global_step/sec: 15.3816
2021-11-27 22:12:10,625 [INFO] tensorflow: global_step/sec: 15.3816
INFO:tensorflow:global_step/sec: 15.4565
2021-11-27 22:12:10,754 [INFO] tensorflow: global_step/sec: 15.4565
INFO:tensorflow:global_step/sec: 14.9284
2021-11-27 22:12:10,888 [INFO] tensorflow: global_step/sec: 14.9284
INFO:tensorflow:global_step/sec: 14.8126
2021-11-27 22:12:11,023 [INFO] tensorflow: global_step/sec: 14.8126
2021-11-27 22:12:11,024 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.652
INFO:tensorflow:global_step/sec: 15.4312
2021-11-27 22:12:11,153 [INFO] tensorflow: global_step/sec: 15.4312
INFO:tensorflow:epoch = 53.5, learning_rate = 0.00049999997, loss = 0.00094118493, step = 1177 (5.094 sec)
2021-11-27 22:12:11,220 [INFO] tensorflow: epoch = 53.5, learning_rate = 0.00049999997, loss = 0.00094118493, step = 1177 (5.094 sec)
INFO:tensorflow:global_step/sec: 14.9147
2021-11-27 22:12:11,287 [INFO] tensorflow: global_step/sec: 14.9147
INFO:tensorflow:global_step/sec: 15.2435
2021-11-27 22:12:11,418 [INFO] tensorflow: global_step/sec: 15.2435
INFO:tensorflow:global_step/sec: 14.5334
2021-11-27 22:12:11,556 [INFO] tensorflow: global_step/sec: 14.5334
INFO:tensorflow:global_step/sec: 14.7962
2021-11-27 22:12:11,691 [INFO] tensorflow: global_step/sec: 14.7962
INFO:tensorflow:global_step/sec: 15.301
2021-11-27 22:12:11,821 [INFO] tensorflow: global_step/sec: 15.301
INFO:tensorflow:global_step/sec: 14.5375
2021-11-27 22:12:11,959 [INFO] tensorflow: global_step/sec: 14.5375
2021-11-27 22:12:11,960 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 54/120: loss: 0.00087 learning rate: 0.00050 Time taken: 0:00:01.463930 ETA: 0:01:36.619389
INFO:tensorflow:global_step/sec: 15.1491
2021-11-27 22:12:12,091 [INFO] tensorflow: global_step/sec: 15.1491
INFO:tensorflow:global_step/sec: 15.0707
2021-11-27 22:12:12,224 [INFO] tensorflow: global_step/sec: 15.0707
INFO:tensorflow:global_step/sec: 14.9959
2021-11-27 22:12:12,357 [INFO] tensorflow: global_step/sec: 14.9959
INFO:tensorflow:global_step/sec: 15.3094
2021-11-27 22:12:12,488 [INFO] tensorflow: global_step/sec: 15.3094
INFO:tensorflow:global_step/sec: 14.7646
2021-11-27 22:12:12,623 [INFO] tensorflow: global_step/sec: 14.7646
2021-11-27 22:12:12,689 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.081
INFO:tensorflow:global_step/sec: 15.362
2021-11-27 22:12:12,753 [INFO] tensorflow: global_step/sec: 15.362
INFO:tensorflow:global_step/sec: 14.7541
2021-11-27 22:12:12,889 [INFO] tensorflow: global_step/sec: 14.7541
INFO:tensorflow:global_step/sec: 14.8839
2021-11-27 22:12:13,023 [INFO] tensorflow: global_step/sec: 14.8839
INFO:tensorflow:global_step/sec: 15.0809
2021-11-27 22:12:13,156 [INFO] tensorflow: global_step/sec: 15.0809
INFO:tensorflow:global_step/sec: 14.9506
2021-11-27 22:12:13,290 [INFO] tensorflow: global_step/sec: 14.9506
INFO:tensorflow:global_step/sec: 14.6066
2021-11-27 22:12:13,427 [INFO] tensorflow: global_step/sec: 14.6066
2021-11-27 22:12:13,427 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 55/120: loss: 0.00078 learning rate: 0.00050 Time taken: 0:00:01.463731 ETA: 0:01:35.142534
INFO:tensorflow:global_step/sec: 13.25
2021-11-27 22:12:13,578 [INFO] tensorflow: global_step/sec: 13.25
INFO:tensorflow:global_step/sec: 15.171
2021-11-27 22:12:13,709 [INFO] tensorflow: global_step/sec: 15.171
INFO:tensorflow:global_step/sec: 15.0354
2021-11-27 22:12:13,842 [INFO] tensorflow: global_step/sec: 15.0354
INFO:tensorflow:global_step/sec: 15.6589
2021-11-27 22:12:13,970 [INFO] tensorflow: global_step/sec: 15.6589
INFO:tensorflow:global_step/sec: 15.3792
2021-11-27 22:12:14,100 [INFO] tensorflow: global_step/sec: 15.3792
INFO:tensorflow:global_step/sec: 15.1949
2021-11-27 22:12:14,232 [INFO] tensorflow: global_step/sec: 15.1949
INFO:tensorflow:global_step/sec: 15.0252
2021-11-27 22:12:14,365 [INFO] tensorflow: global_step/sec: 15.0252
2021-11-27 22:12:14,366 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.637
INFO:tensorflow:global_step/sec: 15.1619
2021-11-27 22:12:14,497 [INFO] tensorflow: global_step/sec: 15.1619
INFO:tensorflow:global_step/sec: 15.4137
2021-11-27 22:12:14,627 [INFO] tensorflow: global_step/sec: 15.4137
INFO:tensorflow:global_step/sec: 15.2072
2021-11-27 22:12:14,758 [INFO] tensorflow: global_step/sec: 15.2072
INFO:tensorflow:global_step/sec: 14.5832
2021-11-27 22:12:14,895 [INFO] tensorflow: global_step/sec: 14.5832
2021-11-27 22:12:14,896 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 56/120: loss: 0.00092 learning rate: 0.00050 Time taken: 0:00:01.466157 ETA: 0:01:33.834045
INFO:tensorflow:global_step/sec: 14.7921
2021-11-27 22:12:15,030 [INFO] tensorflow: global_step/sec: 14.7921
INFO:tensorflow:global_step/sec: 14.9331
2021-11-27 22:12:15,164 [INFO] tensorflow: global_step/sec: 14.9331
INFO:tensorflow:global_step/sec: 14.9091
2021-11-27 22:12:15,299 [INFO] tensorflow: global_step/sec: 14.9091
INFO:tensorflow:global_step/sec: 14.7242
2021-11-27 22:12:15,434 [INFO] tensorflow: global_step/sec: 14.7242
INFO:tensorflow:global_step/sec: 14.9121
2021-11-27 22:12:15,568 [INFO] tensorflow: global_step/sec: 14.9121
INFO:tensorflow:global_step/sec: 15.0135
2021-11-27 22:12:15,702 [INFO] tensorflow: global_step/sec: 15.0135
INFO:tensorflow:global_step/sec: 15.0289
2021-11-27 22:12:15,835 [INFO] tensorflow: global_step/sec: 15.0289
INFO:tensorflow:global_step/sec: 15.0823
2021-11-27 22:12:15,967 [INFO] tensorflow: global_step/sec: 15.0823
2021-11-27 22:12:16,032 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.020
INFO:tensorflow:global_step/sec: 14.9472
2021-11-27 22:12:16,101 [INFO] tensorflow: global_step/sec: 14.9472
INFO:tensorflow:global_step/sec: 15.1505
2021-11-27 22:12:16,233 [INFO] tensorflow: global_step/sec: 15.1505
INFO:tensorflow:epoch = 56.95454545454545, learning_rate = 0.00049999997, loss = 0.00086893945, step = 1253 (5.081 sec)
2021-11-27 22:12:16,301 [INFO] tensorflow: epoch = 56.95454545454545, learning_rate = 0.00049999997, loss = 0.00086893945, step = 1253 (5.081 sec)
INFO:tensorflow:global_step/sec: 13.8847
2021-11-27 22:12:16,377 [INFO] tensorflow: global_step/sec: 13.8847
2021-11-27 22:12:16,378 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 57/120: loss: 0.00078 learning rate: 0.00050 Time taken: 0:00:01.478455 ETA: 0:01:33.142654
INFO:tensorflow:global_step/sec: 15.0431
2021-11-27 22:12:16,510 [INFO] tensorflow: global_step/sec: 15.0431
INFO:tensorflow:global_step/sec: 15.5716
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INFO:tensorflow:global_step/sec: 15.1448
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INFO:tensorflow:global_step/sec: 15.1011
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INFO:tensorflow:global_step/sec: 15.0432
2021-11-27 22:12:17,036 [INFO] tensorflow: global_step/sec: 15.0432
INFO:tensorflow:global_step/sec: 14.9499
2021-11-27 22:12:17,170 [INFO] tensorflow: global_step/sec: 14.9499
INFO:tensorflow:global_step/sec: 14.955
2021-11-27 22:12:17,304 [INFO] tensorflow: global_step/sec: 14.955
INFO:tensorflow:global_step/sec: 14.5574
2021-11-27 22:12:17,441 [INFO] tensorflow: global_step/sec: 14.5574
INFO:tensorflow:global_step/sec: 15.0822
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INFO:tensorflow:global_step/sec: 15.2021
2021-11-27 22:12:17,705 [INFO] tensorflow: global_step/sec: 15.2021
2021-11-27 22:12:17,706 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.766
INFO:tensorflow:global_step/sec: 14.7023
2021-11-27 22:12:17,841 [INFO] tensorflow: global_step/sec: 14.7023
2021-11-27 22:12:17,842 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 58/120: loss: 0.00093 learning rate: 0.00050 Time taken: 0:00:01.465820 ETA: 0:01:30.880859
INFO:tensorflow:global_step/sec: 15.1699
2021-11-27 22:12:17,973 [INFO] tensorflow: global_step/sec: 15.1699
INFO:tensorflow:global_step/sec: 15.1236
2021-11-27 22:12:18,105 [INFO] tensorflow: global_step/sec: 15.1236
INFO:tensorflow:global_step/sec: 15.2878
2021-11-27 22:12:18,236 [INFO] tensorflow: global_step/sec: 15.2878
INFO:tensorflow:global_step/sec: 15.0469
2021-11-27 22:12:18,369 [INFO] tensorflow: global_step/sec: 15.0469
INFO:tensorflow:global_step/sec: 14.8052
2021-11-27 22:12:18,504 [INFO] tensorflow: global_step/sec: 14.8052
INFO:tensorflow:global_step/sec: 15.0932
2021-11-27 22:12:18,637 [INFO] tensorflow: global_step/sec: 15.0932
INFO:tensorflow:global_step/sec: 14.9378
2021-11-27 22:12:18,770 [INFO] tensorflow: global_step/sec: 14.9378
INFO:tensorflow:global_step/sec: 14.6198
2021-11-27 22:12:18,907 [INFO] tensorflow: global_step/sec: 14.6198
INFO:tensorflow:global_step/sec: 15.4707
2021-11-27 22:12:19,037 [INFO] tensorflow: global_step/sec: 15.4707
INFO:tensorflow:global_step/sec: 14.4054
2021-11-27 22:12:19,175 [INFO] tensorflow: global_step/sec: 14.4054
INFO:tensorflow:global_step/sec: 14.4557
2021-11-27 22:12:19,314 [INFO] tensorflow: global_step/sec: 14.4557
2021-11-27 22:12:19,315 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 59/120: loss: 0.00093 learning rate: 0.00050 Time taken: 0:00:01.470789 ETA: 0:01:29.718141
2021-11-27 22:12:19,381 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.679
INFO:tensorflow:global_step/sec: 14.5913
2021-11-27 22:12:19,451 [INFO] tensorflow: global_step/sec: 14.5913
INFO:tensorflow:global_step/sec: 14.7346
2021-11-27 22:12:19,587 [INFO] tensorflow: global_step/sec: 14.7346
INFO:tensorflow:global_step/sec: 14.8875
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INFO:tensorflow:global_step/sec: 14.859
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INFO:tensorflow:global_step/sec: 15.6333
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INFO:tensorflow:global_step/sec: 15.4073
2021-11-27 22:12:20,113 [INFO] tensorflow: global_step/sec: 15.4073
INFO:tensorflow:global_step/sec: 14.9848
2021-11-27 22:12:20,247 [INFO] tensorflow: global_step/sec: 14.9848
INFO:tensorflow:global_step/sec: 15.2503
2021-11-27 22:12:20,378 [INFO] tensorflow: global_step/sec: 15.2503
INFO:tensorflow:global_step/sec: 14.5828
2021-11-27 22:12:20,515 [INFO] tensorflow: global_step/sec: 14.5828
INFO:tensorflow:global_step/sec: 14.9752
2021-11-27 22:12:20,649 [INFO] tensorflow: global_step/sec: 14.9752
INFO:tensorflow:Saving checkpoints for step-1320.
2021-11-27 22:12:20,713 [INFO] tensorflow: Saving checkpoints for step-1320.
WARNING:tensorflow:Ignoring: /tmp/tmp00e3fall; No such file or directory
2021-11-27 22:12:20,799 [WARNING] tensorflow: Ignoring: /tmp/tmp00e3fall; No such file or directory
2021-11-27 22:12:23,052 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 1126/1126 [00:00<00:00, 24527.07it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 119/119 [00:00<00:00, 23328.92it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 366/366 [00:00<00:00, 24577.18it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 1075/1075 [00:00<00:00, 25359.98it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 363/363 [00:00<00:00, 23733.94it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 1085/1085 [00:00<00:00, 23687.88it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 3902/3902 [00:00<00:00, 35894.43it/s]
Epoch 60/120
=========================
Validation cost: 0.000544
Mean average_precision (in %): 26.8432
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 52.4472
floor 0
palette 7.28369
pillar 50.1653
pushcart 0
rackframe 40.2605
rackshelf 52.1553
wall 39.277
Median Inference Time: 0.007524
INFO:tensorflow:epoch = 60.0, learning_rate = 0.00049999997, loss = 0.00087940047, step = 1320 (9.752 sec)
2021-11-27 22:12:26,053 [INFO] tensorflow: epoch = 60.0, learning_rate = 0.00049999997, loss = 0.00087940047, step = 1320 (9.752 sec)
INFO:tensorflow:global_step/sec: 0.370007
2021-11-27 22:12:26,054 [INFO] tensorflow: global_step/sec: 0.370007
2021-11-27 22:12:26,055 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 60/120: loss: 0.00088 learning rate: 0.00050 Time taken: 0:00:06.734482 ETA: 0:06:44.068937
INFO:tensorflow:global_step/sec: 14.7957
2021-11-27 22:12:26,189 [INFO] tensorflow: global_step/sec: 14.7957
INFO:tensorflow:global_step/sec: 15.1964
2021-11-27 22:12:26,321 [INFO] tensorflow: global_step/sec: 15.1964
2021-11-27 22:12:26,321 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 14.410
INFO:tensorflow:global_step/sec: 15.0273
2021-11-27 22:12:26,454 [INFO] tensorflow: global_step/sec: 15.0273
INFO:tensorflow:global_step/sec: 15.2797
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INFO:tensorflow:global_step/sec: 15.1838
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INFO:tensorflow:global_step/sec: 14.9278
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INFO:tensorflow:global_step/sec: 15.058
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INFO:tensorflow:global_step/sec: 15.3988
2021-11-27 22:12:27,113 [INFO] tensorflow: global_step/sec: 15.3988
INFO:tensorflow:global_step/sec: 14.9069
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INFO:tensorflow:global_step/sec: 14.6136
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INFO:tensorflow:global_step/sec: 14.4648
2021-11-27 22:12:27,522 [INFO] tensorflow: global_step/sec: 14.4648
2021-11-27 22:12:27,523 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 61/120: loss: 0.00089 learning rate: 0.00050 Time taken: 0:00:01.471548 ETA: 0:01:26.821309
INFO:tensorflow:global_step/sec: 15.1275
2021-11-27 22:12:27,655 [INFO] tensorflow: global_step/sec: 15.1275
INFO:tensorflow:global_step/sec: 14.369
2021-11-27 22:12:27,794 [INFO] tensorflow: global_step/sec: 14.369
INFO:tensorflow:global_step/sec: 15.3824
2021-11-27 22:12:27,924 [INFO] tensorflow: global_step/sec: 15.3824
2021-11-27 22:12:27,989 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.972
INFO:tensorflow:global_step/sec: 15.3686
2021-11-27 22:12:28,054 [INFO] tensorflow: global_step/sec: 15.3686
INFO:tensorflow:global_step/sec: 14.5108
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INFO:tensorflow:global_step/sec: 14.9015
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INFO:tensorflow:global_step/sec: 15.707
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INFO:tensorflow:global_step/sec: 15.6036
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2021-11-27 22:12:28,978 [INFO] tensorflow: global_step/sec: 15.2381
2021-11-27 22:12:28,979 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 62/120: loss: 0.00095 learning rate: 0.00050 Time taken: 0:00:01.458882 ETA: 0:01:24.615134
INFO:tensorflow:global_step/sec: 15.0636
2021-11-27 22:12:29,110 [INFO] tensorflow: global_step/sec: 15.0636
INFO:tensorflow:global_step/sec: 14.9533
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INFO:tensorflow:global_step/sec: 14.7151
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INFO:tensorflow:global_step/sec: 15.2775
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INFO:tensorflow:global_step/sec: 14.775
2021-11-27 22:12:29,646 [INFO] tensorflow: global_step/sec: 14.775
2021-11-27 22:12:29,647 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.337
INFO:tensorflow:global_step/sec: 15.0148
2021-11-27 22:12:29,780 [INFO] tensorflow: global_step/sec: 15.0148
INFO:tensorflow:global_step/sec: 14.2722
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INFO:tensorflow:global_step/sec: 14.6775
2021-11-27 22:12:30,449 [INFO] tensorflow: global_step/sec: 14.6775
2021-11-27 22:12:30,450 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 63/120: loss: 0.00100 learning rate: 0.00050 Time taken: 0:00:01.466209 ETA: 0:01:23.573936
INFO:tensorflow:global_step/sec: 14.7514
2021-11-27 22:12:30,585 [INFO] tensorflow: global_step/sec: 14.7514
INFO:tensorflow:global_step/sec: 14.8264
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INFO:tensorflow:global_step/sec: 15.134
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INFO:tensorflow:global_step/sec: 14.8385
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INFO:tensorflow:global_step/sec: 15.2822
2021-11-27 22:12:31,117 [INFO] tensorflow: global_step/sec: 15.2822
INFO:tensorflow:epoch = 63.5, learning_rate = 0.00049999997, loss = 0.00069937564, step = 1397 (5.130 sec)
2021-11-27 22:12:31,184 [INFO] tensorflow: epoch = 63.5, learning_rate = 0.00049999997, loss = 0.00069937564, step = 1397 (5.130 sec)
INFO:tensorflow:global_step/sec: 15.0908
2021-11-27 22:12:31,250 [INFO] tensorflow: global_step/sec: 15.0908
2021-11-27 22:12:31,318 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.845
INFO:tensorflow:global_step/sec: 14.6565
2021-11-27 22:12:31,386 [INFO] tensorflow: global_step/sec: 14.6565
INFO:tensorflow:global_step/sec: 15.3194
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INFO:tensorflow:global_step/sec: 15.3984
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INFO:tensorflow:global_step/sec: 14.3433
2021-11-27 22:12:31,917 [INFO] tensorflow: global_step/sec: 14.3433
2021-11-27 22:12:31,918 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 64/120: loss: 0.00082 learning rate: 0.00050 Time taken: 0:00:01.468210 ETA: 0:01:22.219732
INFO:tensorflow:global_step/sec: 15.3212
2021-11-27 22:12:32,047 [INFO] tensorflow: global_step/sec: 15.3212
INFO:tensorflow:global_step/sec: 14.91
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INFO:tensorflow:global_step/sec: 15.1005
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INFO:tensorflow:global_step/sec: 14.7625
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INFO:tensorflow:global_step/sec: 15.3502
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INFO:tensorflow:global_step/sec: 14.9473
2021-11-27 22:12:32,981 [INFO] tensorflow: global_step/sec: 14.9473
2021-11-27 22:12:32,982 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.132
INFO:tensorflow:global_step/sec: 14.8914
2021-11-27 22:12:33,115 [INFO] tensorflow: global_step/sec: 14.8914
INFO:tensorflow:global_step/sec: 15.3056
2021-11-27 22:12:33,246 [INFO] tensorflow: global_step/sec: 15.3056
INFO:tensorflow:global_step/sec: 14.1316
2021-11-27 22:12:33,387 [INFO] tensorflow: global_step/sec: 14.1316
2021-11-27 22:12:33,389 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 65/120: loss: 0.00073 learning rate: 0.00050 Time taken: 0:00:01.467547 ETA: 0:01:20.715108
INFO:tensorflow:global_step/sec: 15.1364
2021-11-27 22:12:33,520 [INFO] tensorflow: global_step/sec: 15.1364
INFO:tensorflow:global_step/sec: 15.2039
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INFO:tensorflow:global_step/sec: 14.9706
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INFO:tensorflow:global_step/sec: 15.3865
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INFO:tensorflow:global_step/sec: 14.5854
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INFO:tensorflow:global_step/sec: 15.3522
2021-11-27 22:12:34,182 [INFO] tensorflow: global_step/sec: 15.3522
INFO:tensorflow:global_step/sec: 14.9313
2021-11-27 22:12:34,316 [INFO] tensorflow: global_step/sec: 14.9313
INFO:tensorflow:global_step/sec: 14.3697
2021-11-27 22:12:34,455 [INFO] tensorflow: global_step/sec: 14.3697
INFO:tensorflow:global_step/sec: 15.0508
2021-11-27 22:12:34,588 [INFO] tensorflow: global_step/sec: 15.0508
2021-11-27 22:12:34,654 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.797
INFO:tensorflow:global_step/sec: 14.5865
2021-11-27 22:12:34,725 [INFO] tensorflow: global_step/sec: 14.5865
INFO:tensorflow:global_step/sec: 13.3584
2021-11-27 22:12:34,875 [INFO] tensorflow: global_step/sec: 13.3584
2021-11-27 22:12:34,876 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 66/120: loss: 0.00079 learning rate: 0.00050 Time taken: 0:00:01.478570 ETA: 0:01:19.842766
INFO:tensorflow:global_step/sec: 13.9818
2021-11-27 22:12:35,018 [INFO] tensorflow: global_step/sec: 13.9818
INFO:tensorflow:global_step/sec: 14.2815
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INFO:tensorflow:global_step/sec: 15.5514
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INFO:tensorflow:global_step/sec: 14.9359
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INFO:tensorflow:global_step/sec: 14.7137
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INFO:tensorflow:global_step/sec: 13.9985
2021-11-27 22:12:36,116 [INFO] tensorflow: global_step/sec: 13.9985
INFO:tensorflow:global_step/sec: 14.7891
2021-11-27 22:12:36,251 [INFO] tensorflow: global_step/sec: 14.7891
INFO:tensorflow:epoch = 66.95454545454545, learning_rate = 0.00049999997, loss = 0.00080842694, step = 1473 (5.140 sec)
2021-11-27 22:12:36,324 [INFO] tensorflow: epoch = 66.95454545454545, learning_rate = 0.00049999997, loss = 0.00080842694, step = 1473 (5.140 sec)
INFO:tensorflow:global_step/sec: 13.1274
2021-11-27 22:12:36,403 [INFO] tensorflow: global_step/sec: 13.1274
2021-11-27 22:12:36,404 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 67/120: loss: 0.00080 learning rate: 0.00050 Time taken: 0:00:01.529250 ETA: 0:01:21.050270
2021-11-27 22:12:36,404 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.154
INFO:tensorflow:global_step/sec: 14.5124
2021-11-27 22:12:36,541 [INFO] tensorflow: global_step/sec: 14.5124
INFO:tensorflow:global_step/sec: 14.2461
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INFO:tensorflow:global_step/sec: 14.9067
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INFO:tensorflow:global_step/sec: 15.1283
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INFO:tensorflow:global_step/sec: 15.0433
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INFO:tensorflow:global_step/sec: 14.5256
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INFO:tensorflow:global_step/sec: 15.3974
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INFO:tensorflow:global_step/sec: 14.207
2021-11-27 22:12:37,893 [INFO] tensorflow: global_step/sec: 14.207
2021-11-27 22:12:37,894 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 68/120: loss: 0.00086 learning rate: 0.00050 Time taken: 0:00:01.492450 ETA: 0:01:17.607400
INFO:tensorflow:global_step/sec: 15.0805
2021-11-27 22:12:38,026 [INFO] tensorflow: global_step/sec: 15.0805
2021-11-27 22:12:38,091 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.274
INFO:tensorflow:global_step/sec: 15.1857
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INFO:tensorflow:global_step/sec: 15.3878
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INFO:tensorflow:global_step/sec: 14.888
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INFO:tensorflow:global_step/sec: 15.1366
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INFO:tensorflow:global_step/sec: 15.2033
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INFO:tensorflow:global_step/sec: 14.7444
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INFO:tensorflow:global_step/sec: 14.6964
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INFO:tensorflow:global_step/sec: 15.021
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INFO:tensorflow:global_step/sec: 14.5311
2021-11-27 22:12:39,359 [INFO] tensorflow: global_step/sec: 14.5311
2021-11-27 22:12:39,360 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 69/120: loss: 0.00078 learning rate: 0.00050 Time taken: 0:00:01.466060 ETA: 0:01:14.769044
INFO:tensorflow:global_step/sec: 14.9926
2021-11-27 22:12:39,493 [INFO] tensorflow: global_step/sec: 14.9926
INFO:tensorflow:global_step/sec: 14.228
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INFO:tensorflow:global_step/sec: 14.8496
2021-11-27 22:12:39,768 [INFO] tensorflow: global_step/sec: 14.8496
2021-11-27 22:12:39,768 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.638
INFO:tensorflow:global_step/sec: 14.7667
2021-11-27 22:12:39,903 [INFO] tensorflow: global_step/sec: 14.7667
INFO:tensorflow:global_step/sec: 14.8912
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INFO:tensorflow:global_step/sec: 14.6907
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INFO:tensorflow:global_step/sec: 15.0516
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INFO:tensorflow:global_step/sec: 15.2418
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INFO:tensorflow:global_step/sec: 14.1835
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INFO:tensorflow:global_step/sec: 14.4201
2021-11-27 22:12:40,718 [INFO] tensorflow: global_step/sec: 14.4201
INFO:tensorflow:Saving checkpoints for step-1540.
2021-11-27 22:12:40,786 [INFO] tensorflow: Saving checkpoints for step-1540.
WARNING:tensorflow:Ignoring: /tmp/tmpl5e3bt52; No such file or directory
2021-11-27 22:12:40,875 [WARNING] tensorflow: Ignoring: /tmp/tmpl5e3bt52; No such file or directory
2021-11-27 22:12:43,090 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 1109/1109 [00:00<00:00, 24772.77it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 132/132 [00:00<00:00, 24423.14it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 358/358 [00:00<00:00, 25020.59it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 1027/1027 [00:00<00:00, 25286.32it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 372/372 [00:00<00:00, 24498.05it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 920/920 [00:00<00:00, 24068.96it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 2308/2308 [00:00<00:00, 35560.36it/s]
Epoch 70/120
=========================
Validation cost: 0.000533
Mean average_precision (in %): 27.0035
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 53.7311
floor 0
palette 8.71212
pillar 54.5732
pushcart 0
rackframe 38.1974
rackshelf 49.1223
wall 38.6951
Median Inference Time: 0.007034
INFO:tensorflow:epoch = 70.0, learning_rate = 0.00049999997, loss = 0.0007588954, step = 1540 (9.764 sec)
2021-11-27 22:12:46,088 [INFO] tensorflow: epoch = 70.0, learning_rate = 0.00049999997, loss = 0.0007588954, step = 1540 (9.764 sec)
INFO:tensorflow:global_step/sec: 0.372372
2021-11-27 22:12:46,089 [INFO] tensorflow: global_step/sec: 0.372372
2021-11-27 22:12:46,090 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 70/120: loss: 0.00076 learning rate: 0.00050 Time taken: 0:00:06.722126 ETA: 0:05:36.106277
INFO:tensorflow:global_step/sec: 13.6125
2021-11-27 22:12:46,236 [INFO] tensorflow: global_step/sec: 13.6125
INFO:tensorflow:global_step/sec: 14.2295
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INFO:tensorflow:global_step/sec: 13.8296
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INFO:tensorflow:global_step/sec: 14.6712
2021-11-27 22:12:46,657 [INFO] tensorflow: global_step/sec: 14.6712
2021-11-27 22:12:46,721 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 14.384
INFO:tensorflow:global_step/sec: 15.1416
2021-11-27 22:12:46,789 [INFO] tensorflow: global_step/sec: 15.1416
INFO:tensorflow:global_step/sec: 15.2101
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2021-11-27 22:12:47,582 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 71/120: loss: 0.00079 learning rate: 0.00050 Time taken: 0:00:01.495772 ETA: 0:01:13.292846
INFO:tensorflow:global_step/sec: 14.8002
2021-11-27 22:12:47,716 [INFO] tensorflow: global_step/sec: 14.8002
INFO:tensorflow:global_step/sec: 15.1268
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INFO:tensorflow:global_step/sec: 14.8205
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INFO:tensorflow:global_step/sec: 14.7806
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INFO:tensorflow:global_step/sec: 15.1353
2021-11-27 22:12:48,383 [INFO] tensorflow: global_step/sec: 15.1353
2021-11-27 22:12:48,383 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.158
INFO:tensorflow:global_step/sec: 14.6156
2021-11-27 22:12:48,520 [INFO] tensorflow: global_step/sec: 14.6156
INFO:tensorflow:global_step/sec: 14.6246
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INFO:tensorflow:global_step/sec: 15.1029
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INFO:tensorflow:global_step/sec: 13.8264
2021-11-27 22:12:49,068 [INFO] tensorflow: global_step/sec: 13.8264
2021-11-27 22:12:49,069 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 72/120: loss: 0.00075 learning rate: 0.00050 Time taken: 0:00:01.483009 ETA: 0:01:11.184437
INFO:tensorflow:global_step/sec: 15.0983
2021-11-27 22:12:49,201 [INFO] tensorflow: global_step/sec: 15.0983
INFO:tensorflow:global_step/sec: 14.7319
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INFO:tensorflow:global_step/sec: 15.3224
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INFO:tensorflow:global_step/sec: 15.118
2021-11-27 22:12:49,875 [INFO] tensorflow: global_step/sec: 15.118
INFO:tensorflow:global_step/sec: 15.4484
2021-11-27 22:12:50,004 [INFO] tensorflow: global_step/sec: 15.4484
2021-11-27 22:12:50,069 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.328
INFO:tensorflow:global_step/sec: 15.4375
2021-11-27 22:12:50,134 [INFO] tensorflow: global_step/sec: 15.4375
INFO:tensorflow:global_step/sec: 14.5934
2021-11-27 22:12:50,271 [INFO] tensorflow: global_step/sec: 14.5934
INFO:tensorflow:global_step/sec: 15.2868
2021-11-27 22:12:50,402 [INFO] tensorflow: global_step/sec: 15.2868
INFO:tensorflow:global_step/sec: 13.9608
2021-11-27 22:12:50,545 [INFO] tensorflow: global_step/sec: 13.9608
2021-11-27 22:12:50,546 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 73/120: loss: 0.00071 learning rate: 0.00050 Time taken: 0:00:01.473545 ETA: 0:01:09.256630
INFO:tensorflow:global_step/sec: 15.1236
2021-11-27 22:12:50,677 [INFO] tensorflow: global_step/sec: 15.1236
INFO:tensorflow:global_step/sec: 15.2885
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INFO:tensorflow:global_step/sec: 15.0971
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INFO:tensorflow:global_step/sec: 15.0934
2021-11-27 22:12:51,073 [INFO] tensorflow: global_step/sec: 15.0934
INFO:tensorflow:epoch = 73.45454545454545, learning_rate = 0.00049999997, loss = 0.0007004625, step = 1616 (5.115 sec)
2021-11-27 22:12:51,203 [INFO] tensorflow: epoch = 73.45454545454545, learning_rate = 0.00049999997, loss = 0.0007004625, step = 1616 (5.115 sec)
INFO:tensorflow:global_step/sec: 15.3594
2021-11-27 22:12:51,203 [INFO] tensorflow: global_step/sec: 15.3594
INFO:tensorflow:global_step/sec: 15.0263
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INFO:tensorflow:global_step/sec: 15.0121
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INFO:tensorflow:global_step/sec: 15.2726
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INFO:tensorflow:global_step/sec: 15.1035
2021-11-27 22:12:51,733 [INFO] tensorflow: global_step/sec: 15.1035
2021-11-27 22:12:51,734 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.099
INFO:tensorflow:global_step/sec: 15.029
2021-11-27 22:12:51,866 [INFO] tensorflow: global_step/sec: 15.029
INFO:tensorflow:global_step/sec: 14.0965
2021-11-27 22:12:52,008 [INFO] tensorflow: global_step/sec: 14.0965
2021-11-27 22:12:52,009 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 74/120: loss: 0.00074 learning rate: 0.00050 Time taken: 0:00:01.464094 ETA: 0:01:07.348342
INFO:tensorflow:global_step/sec: 15.0669
2021-11-27 22:12:52,141 [INFO] tensorflow: global_step/sec: 15.0669
INFO:tensorflow:global_step/sec: 15.1088
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INFO:tensorflow:global_step/sec: 15.037
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INFO:tensorflow:global_step/sec: 14.7934
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INFO:tensorflow:global_step/sec: 15.13
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INFO:tensorflow:global_step/sec: 14.7019
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INFO:tensorflow:global_step/sec: 15.2613
2021-11-27 22:12:52,941 [INFO] tensorflow: global_step/sec: 15.2613
INFO:tensorflow:global_step/sec: 15.0271
2021-11-27 22:12:53,074 [INFO] tensorflow: global_step/sec: 15.0271
INFO:tensorflow:global_step/sec: 14.9261
2021-11-27 22:12:53,208 [INFO] tensorflow: global_step/sec: 14.9261
INFO:tensorflow:global_step/sec: 14.6805
2021-11-27 22:12:53,344 [INFO] tensorflow: global_step/sec: 14.6805
2021-11-27 22:12:53,414 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.513
INFO:tensorflow:global_step/sec: 14.3085
2021-11-27 22:12:53,484 [INFO] tensorflow: global_step/sec: 14.3085
2021-11-27 22:12:53,485 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 75/120: loss: 0.00078 learning rate: 0.00050 Time taken: 0:00:01.473139 ETA: 0:01:06.291268
INFO:tensorflow:global_step/sec: 14.863
2021-11-27 22:12:53,618 [INFO] tensorflow: global_step/sec: 14.863
INFO:tensorflow:global_step/sec: 14.9176
2021-11-27 22:12:53,752 [INFO] tensorflow: global_step/sec: 14.9176
INFO:tensorflow:global_step/sec: 14.5529
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INFO:tensorflow:global_step/sec: 14.3515
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INFO:tensorflow:global_step/sec: 15.4043
2021-11-27 22:12:54,159 [INFO] tensorflow: global_step/sec: 15.4043
INFO:tensorflow:global_step/sec: 15.8303
2021-11-27 22:12:54,285 [INFO] tensorflow: global_step/sec: 15.8303
INFO:tensorflow:global_step/sec: 14.8735
2021-11-27 22:12:54,420 [INFO] tensorflow: global_step/sec: 14.8735
INFO:tensorflow:global_step/sec: 14.9424
2021-11-27 22:12:54,554 [INFO] tensorflow: global_step/sec: 14.9424
INFO:tensorflow:global_step/sec: 14.9376
2021-11-27 22:12:54,688 [INFO] tensorflow: global_step/sec: 14.9376
INFO:tensorflow:global_step/sec: 15.5001
2021-11-27 22:12:54,817 [INFO] tensorflow: global_step/sec: 15.5001
INFO:tensorflow:global_step/sec: 14.1045
2021-11-27 22:12:54,958 [INFO] tensorflow: global_step/sec: 14.1045
2021-11-27 22:12:54,959 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 76/120: loss: 0.00081 learning rate: 0.00050 Time taken: 0:00:01.476994 ETA: 0:01:04.987717
INFO:tensorflow:global_step/sec: 15.2177
2021-11-27 22:12:55,090 [INFO] tensorflow: global_step/sec: 15.2177
2021-11-27 22:12:55,091 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.710
INFO:tensorflow:global_step/sec: 14.9719
2021-11-27 22:12:55,223 [INFO] tensorflow: global_step/sec: 14.9719
INFO:tensorflow:global_step/sec: 15.692
2021-11-27 22:12:55,351 [INFO] tensorflow: global_step/sec: 15.692
INFO:tensorflow:global_step/sec: 15.4475
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INFO:tensorflow:global_step/sec: 15.1329
2021-11-27 22:12:55,612 [INFO] tensorflow: global_step/sec: 15.1329
INFO:tensorflow:global_step/sec: 15.5349
2021-11-27 22:12:55,741 [INFO] tensorflow: global_step/sec: 15.5349
INFO:tensorflow:global_step/sec: 14.9617
2021-11-27 22:12:55,875 [INFO] tensorflow: global_step/sec: 14.9617
INFO:tensorflow:global_step/sec: 14.9667
2021-11-27 22:12:56,009 [INFO] tensorflow: global_step/sec: 14.9667
INFO:tensorflow:global_step/sec: 15.0135
2021-11-27 22:12:56,142 [INFO] tensorflow: global_step/sec: 15.0135
INFO:tensorflow:epoch = 76.9090909090909, learning_rate = 0.00049999997, loss = 0.00073854055, step = 1692 (5.075 sec)
2021-11-27 22:12:56,278 [INFO] tensorflow: epoch = 76.9090909090909, learning_rate = 0.00049999997, loss = 0.00073854055, step = 1692 (5.075 sec)
INFO:tensorflow:global_step/sec: 14.5652
2021-11-27 22:12:56,279 [INFO] tensorflow: global_step/sec: 14.5652
INFO:tensorflow:global_step/sec: 13.5652
2021-11-27 22:12:56,426 [INFO] tensorflow: global_step/sec: 13.5652
2021-11-27 22:12:56,427 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 77/120: loss: 0.00073 learning rate: 0.00050 Time taken: 0:00:01.463050 ETA: 0:01:02.911166
INFO:tensorflow:global_step/sec: 14.4322
2021-11-27 22:12:56,565 [INFO] tensorflow: global_step/sec: 14.4322
INFO:tensorflow:global_step/sec: 14.93
2021-11-27 22:12:56,699 [INFO] tensorflow: global_step/sec: 14.93
2021-11-27 22:12:56,767 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.648
INFO:tensorflow:global_step/sec: 14.4709
2021-11-27 22:12:56,837 [INFO] tensorflow: global_step/sec: 14.4709
INFO:tensorflow:global_step/sec: 14.4396
2021-11-27 22:12:56,976 [INFO] tensorflow: global_step/sec: 14.4396
INFO:tensorflow:global_step/sec: 13.8835
2021-11-27 22:12:57,120 [INFO] tensorflow: global_step/sec: 13.8835
INFO:tensorflow:global_step/sec: 14.6914
2021-11-27 22:12:57,256 [INFO] tensorflow: global_step/sec: 14.6914
INFO:tensorflow:global_step/sec: 15.1329
2021-11-27 22:12:57,388 [INFO] tensorflow: global_step/sec: 15.1329
INFO:tensorflow:global_step/sec: 14.889
2021-11-27 22:12:57,522 [INFO] tensorflow: global_step/sec: 14.889
INFO:tensorflow:global_step/sec: 14.6504
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INFO:tensorflow:global_step/sec: 14.7089
2021-11-27 22:12:57,795 [INFO] tensorflow: global_step/sec: 14.7089
INFO:tensorflow:global_step/sec: 13.3885
2021-11-27 22:12:57,944 [INFO] tensorflow: global_step/sec: 13.3885
2021-11-27 22:12:57,946 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 78/120: loss: 0.00071 learning rate: 0.00050 Time taken: 0:00:01.512005 ETA: 0:01:03.504214
INFO:tensorflow:global_step/sec: 14.6969
2021-11-27 22:12:58,080 [INFO] tensorflow: global_step/sec: 14.6969
INFO:tensorflow:global_step/sec: 14.5369
2021-11-27 22:12:58,218 [INFO] tensorflow: global_step/sec: 14.5369
INFO:tensorflow:global_step/sec: 15.6171
2021-11-27 22:12:58,346 [INFO] tensorflow: global_step/sec: 15.6171
INFO:tensorflow:global_step/sec: 15.2686
2021-11-27 22:12:58,477 [INFO] tensorflow: global_step/sec: 15.2686
2021-11-27 22:12:58,477 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.488
INFO:tensorflow:global_step/sec: 15.3921
2021-11-27 22:12:58,607 [INFO] tensorflow: global_step/sec: 15.3921
INFO:tensorflow:global_step/sec: 14.4972
2021-11-27 22:12:58,745 [INFO] tensorflow: global_step/sec: 14.4972
INFO:tensorflow:global_step/sec: 15.0587
2021-11-27 22:12:58,878 [INFO] tensorflow: global_step/sec: 15.0587
INFO:tensorflow:global_step/sec: 15.1277
2021-11-27 22:12:59,010 [INFO] tensorflow: global_step/sec: 15.1277
INFO:tensorflow:global_step/sec: 14.8894
2021-11-27 22:12:59,144 [INFO] tensorflow: global_step/sec: 14.8894
INFO:tensorflow:global_step/sec: 14.5121
2021-11-27 22:12:59,282 [INFO] tensorflow: global_step/sec: 14.5121
INFO:tensorflow:global_step/sec: 13.2763
2021-11-27 22:12:59,433 [INFO] tensorflow: global_step/sec: 13.2763
2021-11-27 22:12:59,434 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 79/120: loss: 0.00065 learning rate: 0.00050 Time taken: 0:00:01.486251 ETA: 0:01:00.936286
INFO:tensorflow:global_step/sec: 14.3228
2021-11-27 22:12:59,572 [INFO] tensorflow: global_step/sec: 14.3228
INFO:tensorflow:global_step/sec: 14.1395
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INFO:tensorflow:global_step/sec: 14.7495
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INFO:tensorflow:global_step/sec: 15.0211
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INFO:tensorflow:global_step/sec: 15.1254
2021-11-27 22:13:00,115 [INFO] tensorflow: global_step/sec: 15.1254
2021-11-27 22:13:00,181 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.716
INFO:tensorflow:global_step/sec: 15.3276
2021-11-27 22:13:00,245 [INFO] tensorflow: global_step/sec: 15.3276
INFO:tensorflow:global_step/sec: 14.6185
2021-11-27 22:13:00,382 [INFO] tensorflow: global_step/sec: 14.6185
INFO:tensorflow:global_step/sec: 14.8032
2021-11-27 22:13:00,517 [INFO] tensorflow: global_step/sec: 14.8032
INFO:tensorflow:global_step/sec: 14.9164
2021-11-27 22:13:00,651 [INFO] tensorflow: global_step/sec: 14.9164
INFO:tensorflow:global_step/sec: 15.7042
2021-11-27 22:13:00,779 [INFO] tensorflow: global_step/sec: 15.7042
INFO:tensorflow:Saving checkpoints for step-1760.
2021-11-27 22:13:00,845 [INFO] tensorflow: Saving checkpoints for step-1760.
WARNING:tensorflow:Ignoring: /tmp/tmpw88zljs7; No such file or directory
2021-11-27 22:13:00,934 [WARNING] tensorflow: Ignoring: /tmp/tmpw88zljs7; No such file or directory
2021-11-27 22:13:03,176 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 825/825 [00:00<00:00, 24141.18it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 51/51 [00:00<00:00, 22834.06it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 169/169 [00:00<00:00, 24357.00it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 891/891 [00:00<00:00, 25336.44it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 492/492 [00:00<00:00, 23677.60it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 839/839 [00:00<00:00, 23788.74it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 2452/2452 [00:00<00:00, 36299.84it/s]
Epoch 80/120
=========================
Validation cost: 0.000479
Mean average_precision (in %): 28.1822
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 60.6922
floor 0
palette 10.7372
pillar 44.2346
pushcart 0
rackframe 46.2873
rackshelf 58.7035
wall 32.9852
Median Inference Time: 0.007864
INFO:tensorflow:epoch = 80.0, learning_rate = 0.00049999997, loss = 0.0006499792, step = 1760 (9.147 sec)
2021-11-27 22:13:05,426 [INFO] tensorflow: epoch = 80.0, learning_rate = 0.00049999997, loss = 0.0006499792, step = 1760 (9.147 sec)
INFO:tensorflow:global_step/sec: 0.430287
2021-11-27 22:13:05,427 [INFO] tensorflow: global_step/sec: 0.430287
2021-11-27 22:13:05,428 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 80/120: loss: 0.00065 learning rate: 0.00050 Time taken: 0:00:05.998800 ETA: 0:03:59.952011
INFO:tensorflow:global_step/sec: 13.6292
2021-11-27 22:13:05,573 [INFO] tensorflow: global_step/sec: 13.6292
INFO:tensorflow:global_step/sec: 14.7563
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INFO:tensorflow:global_step/sec: 15.0554
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INFO:tensorflow:global_step/sec: 15.3417
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INFO:tensorflow:global_step/sec: 14.3697
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INFO:tensorflow:global_step/sec: 14.4241
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INFO:tensorflow:global_step/sec: 14.628
2021-11-27 22:13:06,387 [INFO] tensorflow: global_step/sec: 14.628
2021-11-27 22:13:06,387 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 16.113
INFO:tensorflow:global_step/sec: 15.359
2021-11-27 22:13:06,517 [INFO] tensorflow: global_step/sec: 15.359
INFO:tensorflow:global_step/sec: 15.3121
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INFO:tensorflow:global_step/sec: 15.4831
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INFO:tensorflow:global_step/sec: 14.493
2021-11-27 22:13:06,915 [INFO] tensorflow: global_step/sec: 14.493
2021-11-27 22:13:06,916 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 81/120: loss: 0.00074 learning rate: 0.00050 Time taken: 0:00:01.486891 ETA: 0:00:57.988750
INFO:tensorflow:global_step/sec: 14.831
2021-11-27 22:13:07,050 [INFO] tensorflow: global_step/sec: 14.831
INFO:tensorflow:global_step/sec: 15.5973
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INFO:tensorflow:global_step/sec: 14.683
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INFO:tensorflow:global_step/sec: 15.1998
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INFO:tensorflow:global_step/sec: 14.3385
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INFO:tensorflow:global_step/sec: 15.29
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INFO:tensorflow:global_step/sec: 15.4708
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INFO:tensorflow:global_step/sec: 14.6313
2021-11-27 22:13:07,982 [INFO] tensorflow: global_step/sec: 14.6313
2021-11-27 22:13:08,047 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 60.265
INFO:tensorflow:global_step/sec: 15.5324
2021-11-27 22:13:08,111 [INFO] tensorflow: global_step/sec: 15.5324
INFO:tensorflow:global_step/sec: 14.8359
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INFO:tensorflow:global_step/sec: 14.3576
2021-11-27 22:13:08,385 [INFO] tensorflow: global_step/sec: 14.3576
2021-11-27 22:13:08,386 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 82/120: loss: 0.00061 learning rate: 0.00050 Time taken: 0:00:01.465412 ETA: 0:00:55.685661
INFO:tensorflow:global_step/sec: 14.5825
2021-11-27 22:13:08,522 [INFO] tensorflow: global_step/sec: 14.5825
INFO:tensorflow:global_step/sec: 14.6026
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INFO:tensorflow:global_step/sec: 14.7293
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INFO:tensorflow:global_step/sec: 15.1709
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INFO:tensorflow:global_step/sec: 15.4105
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INFO:tensorflow:global_step/sec: 14.616
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INFO:tensorflow:global_step/sec: 14.1376
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INFO:tensorflow:global_step/sec: 13.8033
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INFO:tensorflow:global_step/sec: 13.8202
2021-11-27 22:13:09,759 [INFO] tensorflow: global_step/sec: 13.8202
2021-11-27 22:13:09,760 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.383
INFO:tensorflow:global_step/sec: 13.5034
2021-11-27 22:13:09,908 [INFO] tensorflow: global_step/sec: 13.5034
2021-11-27 22:13:09,909 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 83/120: loss: 0.00073 learning rate: 0.00050 Time taken: 0:00:01.522144 ETA: 0:00:56.319331
INFO:tensorflow:global_step/sec: 14.5834
2021-11-27 22:13:10,045 [INFO] tensorflow: global_step/sec: 14.5834
INFO:tensorflow:global_step/sec: 14.8498
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INFO:tensorflow:global_step/sec: 14.8563
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INFO:tensorflow:global_step/sec: 14.479
2021-11-27 22:13:10,452 [INFO] tensorflow: global_step/sec: 14.479
INFO:tensorflow:epoch = 83.4090909090909, learning_rate = 0.00049999997, loss = 0.0007822754, step = 1835 (5.093 sec)
2021-11-27 22:13:10,518 [INFO] tensorflow: epoch = 83.4090909090909, learning_rate = 0.00049999997, loss = 0.0007822754, step = 1835 (5.093 sec)
INFO:tensorflow:global_step/sec: 15.0943
2021-11-27 22:13:10,585 [INFO] tensorflow: global_step/sec: 15.0943
INFO:tensorflow:global_step/sec: 15.1703
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INFO:tensorflow:global_step/sec: 14.9898
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INFO:tensorflow:global_step/sec: 15.4098
2021-11-27 22:13:10,980 [INFO] tensorflow: global_step/sec: 15.4098
INFO:tensorflow:global_step/sec: 15.1817
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INFO:tensorflow:global_step/sec: 15.337
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INFO:tensorflow:global_step/sec: 14.1729
2021-11-27 22:13:11,383 [INFO] tensorflow: global_step/sec: 14.1729
2021-11-27 22:13:11,384 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 84/120: loss: 0.00072 learning rate: 0.00050 Time taken: 0:00:01.473306 ETA: 0:00:53.039022
2021-11-27 22:13:11,449 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.239
INFO:tensorflow:global_step/sec: 15.1327
2021-11-27 22:13:11,515 [INFO] tensorflow: global_step/sec: 15.1327
INFO:tensorflow:global_step/sec: 14.8292
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INFO:tensorflow:global_step/sec: 14.8591
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INFO:tensorflow:global_step/sec: 15.2282
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INFO:tensorflow:global_step/sec: 14.8331
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INFO:tensorflow:global_step/sec: 15.0929
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INFO:tensorflow:global_step/sec: 14.6942
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INFO:tensorflow:global_step/sec: 14.8106
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INFO:tensorflow:global_step/sec: 15.3081
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INFO:tensorflow:global_step/sec: 14.281
2021-11-27 22:13:12,856 [INFO] tensorflow: global_step/sec: 14.281
2021-11-27 22:13:12,857 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 85/120: loss: 0.00067 learning rate: 0.00044 Time taken: 0:00:01.474650 ETA: 0:00:51.612738
INFO:tensorflow:global_step/sec: 15.2563
2021-11-27 22:13:12,987 [INFO] tensorflow: global_step/sec: 15.2563
INFO:tensorflow:global_step/sec: 14.6811
2021-11-27 22:13:13,124 [INFO] tensorflow: global_step/sec: 14.6811
2021-11-27 22:13:13,124 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.688
INFO:tensorflow:global_step/sec: 15.064
2021-11-27 22:13:13,256 [INFO] tensorflow: global_step/sec: 15.064
INFO:tensorflow:global_step/sec: 14.7387
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INFO:tensorflow:global_step/sec: 14.9827
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INFO:tensorflow:global_step/sec: 14.8412
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INFO:tensorflow:global_step/sec: 15.2277
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INFO:tensorflow:global_step/sec: 14.9006
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INFO:tensorflow:global_step/sec: 15.5387
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INFO:tensorflow:global_step/sec: 15.5275
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INFO:tensorflow:global_step/sec: 14.1983
2021-11-27 22:13:14,324 [INFO] tensorflow: global_step/sec: 14.1983
2021-11-27 22:13:14,325 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 86/120: loss: 0.00070 learning rate: 0.00039 Time taken: 0:00:01.463946 ETA: 0:00:49.774151
INFO:tensorflow:global_step/sec: 14.7477
2021-11-27 22:13:14,460 [INFO] tensorflow: global_step/sec: 14.7477
INFO:tensorflow:global_step/sec: 14.7541
2021-11-27 22:13:14,595 [INFO] tensorflow: global_step/sec: 14.7541
INFO:tensorflow:global_step/sec: 15.3032
2021-11-27 22:13:14,726 [INFO] tensorflow: global_step/sec: 15.3032
2021-11-27 22:13:14,802 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.611
INFO:tensorflow:global_step/sec: 13.8856
2021-11-27 22:13:14,870 [INFO] tensorflow: global_step/sec: 13.8856
INFO:tensorflow:global_step/sec: 15.2284
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INFO:tensorflow:global_step/sec: 14.9008
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INFO:tensorflow:global_step/sec: 15.0425
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INFO:tensorflow:global_step/sec: 14.4612
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INFO:tensorflow:global_step/sec: 14.4209
2021-11-27 22:13:15,546 [INFO] tensorflow: global_step/sec: 14.4209
INFO:tensorflow:epoch = 86.86363636363636, learning_rate = 0.0003466404, loss = 0.00072251324, step = 1911 (5.096 sec)
2021-11-27 22:13:15,614 [INFO] tensorflow: epoch = 86.86363636363636, learning_rate = 0.0003466404, loss = 0.00072251324, step = 1911 (5.096 sec)
INFO:tensorflow:global_step/sec: 14.8664
2021-11-27 22:13:15,680 [INFO] tensorflow: global_step/sec: 14.8664
INFO:tensorflow:global_step/sec: 14.5591
2021-11-27 22:13:15,818 [INFO] tensorflow: global_step/sec: 14.5591
2021-11-27 22:13:15,818 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 87/120: loss: 0.00060 learning rate: 0.00034 Time taken: 0:00:01.495117 ETA: 0:00:49.338851
INFO:tensorflow:global_step/sec: 15.1702
2021-11-27 22:13:15,949 [INFO] tensorflow: global_step/sec: 15.1702
INFO:tensorflow:global_step/sec: 15.3082
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INFO:tensorflow:global_step/sec: 15.122
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INFO:tensorflow:global_step/sec: 14.8722
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INFO:tensorflow:global_step/sec: 14.4974
2021-11-27 22:13:16,485 [INFO] tensorflow: global_step/sec: 14.4974
2021-11-27 22:13:16,485 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.415
INFO:tensorflow:global_step/sec: 15.5415
2021-11-27 22:13:16,613 [INFO] tensorflow: global_step/sec: 15.5415
INFO:tensorflow:global_step/sec: 14.7761
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INFO:tensorflow:global_step/sec: 14.9693
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INFO:tensorflow:global_step/sec: 14.4355
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INFO:tensorflow:global_step/sec: 13.9816
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INFO:tensorflow:global_step/sec: 13.7595
2021-11-27 22:13:17,309 [INFO] tensorflow: global_step/sec: 13.7595
2021-11-27 22:13:17,310 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 88/120: loss: 0.00058 learning rate: 0.00030 Time taken: 0:00:01.484386 ETA: 0:00:47.500343
INFO:tensorflow:global_step/sec: 14.8488
2021-11-27 22:13:17,444 [INFO] tensorflow: global_step/sec: 14.8488
INFO:tensorflow:global_step/sec: 14.5991
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INFO:tensorflow:global_step/sec: 14.7755
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INFO:tensorflow:global_step/sec: 13.9732
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INFO:tensorflow:global_step/sec: 14.8747
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INFO:tensorflow:global_step/sec: 13.8057
2021-11-27 22:13:18,139 [INFO] tensorflow: global_step/sec: 13.8057
2021-11-27 22:13:18,210 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.990
INFO:tensorflow:global_step/sec: 14.0308
2021-11-27 22:13:18,281 [INFO] tensorflow: global_step/sec: 14.0308
INFO:tensorflow:global_step/sec: 15.0172
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INFO:tensorflow:global_step/sec: 15.2718
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INFO:tensorflow:global_step/sec: 15.2321
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INFO:tensorflow:global_step/sec: 14.558
2021-11-27 22:13:18,814 [INFO] tensorflow: global_step/sec: 14.558
2021-11-27 22:13:18,815 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 89/120: loss: 0.00062 learning rate: 0.00026 Time taken: 0:00:01.507442 ETA: 0:00:46.730717
INFO:tensorflow:global_step/sec: 14.9583
2021-11-27 22:13:18,948 [INFO] tensorflow: global_step/sec: 14.9583
INFO:tensorflow:global_step/sec: 14.9255
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INFO:tensorflow:global_step/sec: 15.2949
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INFO:tensorflow:global_step/sec: 14.7123
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INFO:tensorflow:global_step/sec: 14.8202
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INFO:tensorflow:global_step/sec: 14.734
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INFO:tensorflow:global_step/sec: 14.7792
2021-11-27 22:13:19,887 [INFO] tensorflow: global_step/sec: 14.7792
2021-11-27 22:13:19,888 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.611
INFO:tensorflow:global_step/sec: 15.0663
2021-11-27 22:13:20,020 [INFO] tensorflow: global_step/sec: 15.0663
INFO:tensorflow:global_step/sec: 14.6455
2021-11-27 22:13:20,157 [INFO] tensorflow: global_step/sec: 14.6455
INFO:tensorflow:Saving checkpoints for step-1980.
2021-11-27 22:13:20,224 [INFO] tensorflow: Saving checkpoints for step-1980.
WARNING:tensorflow:Ignoring: /tmp/tmp24snkaxz; No such file or directory
2021-11-27 22:13:20,313 [WARNING] tensorflow: Ignoring: /tmp/tmp24snkaxz; No such file or directory
2021-11-27 22:13:22,554 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 1036/1036 [00:00<00:00, 24695.37it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 54/54 [00:00<00:00, 23373.83it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 196/196 [00:00<00:00, 24721.34it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 718/718 [00:00<00:00, 25645.81it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 241/241 [00:00<00:00, 24213.17it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 736/736 [00:00<00:00, 23490.53it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 1605/1605 [00:00<00:00, 36985.59it/s]
Epoch 90/120
=========================
Validation cost: 0.000422
Mean average_precision (in %): 28.8910
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 74.7346
floor 0
palette 7.65957
pillar 49.2648
pushcart 0
rackframe 44.7523
rackshelf 48.4322
wall 35.1759
Median Inference Time: 0.007415
INFO:tensorflow:epoch = 90.0, learning_rate = 0.00023207937, loss = 0.00057127076, step = 1980 (9.215 sec)
2021-11-27 22:13:24,830 [INFO] tensorflow: epoch = 90.0, learning_rate = 0.00023207937, loss = 0.00057127076, step = 1980 (9.215 sec)
INFO:tensorflow:global_step/sec: 0.42791
2021-11-27 22:13:24,831 [INFO] tensorflow: global_step/sec: 0.42791
2021-11-27 22:13:24,831 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 90/120: loss: 0.00057 learning rate: 0.00023 Time taken: 0:00:06.009696 ETA: 0:03:00.290895
INFO:tensorflow:global_step/sec: 14.9932
2021-11-27 22:13:24,964 [INFO] tensorflow: global_step/sec: 14.9932
INFO:tensorflow:global_step/sec: 15.0883
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INFO:tensorflow:global_step/sec: 14.7956
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INFO:tensorflow:global_step/sec: 15.2936
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INFO:tensorflow:global_step/sec: 15.1085
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INFO:tensorflow:global_step/sec: 15.1568
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INFO:tensorflow:global_step/sec: 14.877
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INFO:tensorflow:global_step/sec: 15.1688
2021-11-27 22:13:26,024 [INFO] tensorflow: global_step/sec: 15.1688
2021-11-27 22:13:26,090 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 16.126
INFO:tensorflow:global_step/sec: 15.3013
2021-11-27 22:13:26,155 [INFO] tensorflow: global_step/sec: 15.3013
INFO:tensorflow:global_step/sec: 14.3635
2021-11-27 22:13:26,294 [INFO] tensorflow: global_step/sec: 14.3635
2021-11-27 22:13:26,295 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 91/120: loss: 0.00055 learning rate: 0.00020 Time taken: 0:00:01.468175 ETA: 0:00:42.577087
INFO:tensorflow:global_step/sec: 14.735
2021-11-27 22:13:26,430 [INFO] tensorflow: global_step/sec: 14.735
INFO:tensorflow:global_step/sec: 15.2105
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INFO:tensorflow:global_step/sec: 14.5592
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INFO:tensorflow:global_step/sec: 15.1098
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INFO:tensorflow:global_step/sec: 14.5534
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INFO:tensorflow:global_step/sec: 15.0356
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INFO:tensorflow:global_step/sec: 14.7363
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INFO:tensorflow:global_step/sec: 15.3127
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INFO:tensorflow:global_step/sec: 15.0626
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INFO:tensorflow:global_step/sec: 14.9401
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INFO:tensorflow:global_step/sec: 13.7332
2021-11-27 22:13:27,780 [INFO] tensorflow: global_step/sec: 13.7332
2021-11-27 22:13:27,781 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 92/120: loss: 0.00068 learning rate: 0.00018 Time taken: 0:00:01.481202 ETA: 0:00:41.473666
2021-11-27 22:13:27,781 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.136
INFO:tensorflow:global_step/sec: 14.8315
2021-11-27 22:13:27,915 [INFO] tensorflow: global_step/sec: 14.8315
INFO:tensorflow:global_step/sec: 15.0609
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INFO:tensorflow:global_step/sec: 14.6548
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INFO:tensorflow:global_step/sec: 15.0389
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INFO:tensorflow:global_step/sec: 14.84
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INFO:tensorflow:global_step/sec: 14.8077
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INFO:tensorflow:global_step/sec: 14.7013
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INFO:tensorflow:global_step/sec: 13.8526
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INFO:tensorflow:global_step/sec: 14.5947
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INFO:tensorflow:global_step/sec: 15.115
2021-11-27 22:13:29,137 [INFO] tensorflow: global_step/sec: 15.115
INFO:tensorflow:global_step/sec: 14.7715
2021-11-27 22:13:29,272 [INFO] tensorflow: global_step/sec: 14.7715
2021-11-27 22:13:29,273 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 93/120: loss: 0.00057 learning rate: 0.00016 Time taken: 0:00:01.496615 ETA: 0:00:40.408597
INFO:tensorflow:global_step/sec: 15.0622
2021-11-27 22:13:29,405 [INFO] tensorflow: global_step/sec: 15.0622
2021-11-27 22:13:29,470 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.223
INFO:tensorflow:global_step/sec: 15.4088
2021-11-27 22:13:29,535 [INFO] tensorflow: global_step/sec: 15.4088
INFO:tensorflow:global_step/sec: 14.9831
2021-11-27 22:13:29,668 [INFO] tensorflow: global_step/sec: 14.9831
INFO:tensorflow:global_step/sec: 14.4544
2021-11-27 22:13:29,806 [INFO] tensorflow: global_step/sec: 14.4544
INFO:tensorflow:epoch = 93.45454545454545, learning_rate = 0.0001491824, loss = 0.000626393, step = 2056 (5.117 sec)
2021-11-27 22:13:29,946 [INFO] tensorflow: epoch = 93.45454545454545, learning_rate = 0.0001491824, loss = 0.000626393, step = 2056 (5.117 sec)
INFO:tensorflow:global_step/sec: 14.2034
2021-11-27 22:13:29,947 [INFO] tensorflow: global_step/sec: 14.2034
INFO:tensorflow:global_step/sec: 14.5378
2021-11-27 22:13:30,085 [INFO] tensorflow: global_step/sec: 14.5378
INFO:tensorflow:global_step/sec: 15.1569
2021-11-27 22:13:30,217 [INFO] tensorflow: global_step/sec: 15.1569
INFO:tensorflow:global_step/sec: 14.9863
2021-11-27 22:13:30,350 [INFO] tensorflow: global_step/sec: 14.9863
INFO:tensorflow:global_step/sec: 14.8413
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INFO:tensorflow:global_step/sec: 14.9437
2021-11-27 22:13:30,619 [INFO] tensorflow: global_step/sec: 14.9437
INFO:tensorflow:global_step/sec: 13.8728
2021-11-27 22:13:30,763 [INFO] tensorflow: global_step/sec: 13.8728
2021-11-27 22:13:30,764 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 94/120: loss: 0.00062 learning rate: 0.00014 Time taken: 0:00:01.484202 ETA: 0:00:38.589250
INFO:tensorflow:global_step/sec: 14.9684
2021-11-27 22:13:30,897 [INFO] tensorflow: global_step/sec: 14.9684
INFO:tensorflow:global_step/sec: 14.8754
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INFO:tensorflow:global_step/sec: 14.8074
2021-11-27 22:13:31,166 [INFO] tensorflow: global_step/sec: 14.8074
2021-11-27 22:13:31,167 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.931
INFO:tensorflow:global_step/sec: 14.8315
2021-11-27 22:13:31,301 [INFO] tensorflow: global_step/sec: 14.8315
INFO:tensorflow:global_step/sec: 15.0223
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INFO:tensorflow:global_step/sec: 14.7531
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INFO:tensorflow:global_step/sec: 15.318
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INFO:tensorflow:global_step/sec: 14.4051
2021-11-27 22:13:32,240 [INFO] tensorflow: global_step/sec: 14.4051
2021-11-27 22:13:32,241 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 95/120: loss: 0.00062 learning rate: 0.00012 Time taken: 0:00:01.478175 ETA: 0:00:36.954379
INFO:tensorflow:global_step/sec: 14.7962
2021-11-27 22:13:32,375 [INFO] tensorflow: global_step/sec: 14.7962
INFO:tensorflow:global_step/sec: 15.0096
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INFO:tensorflow:global_step/sec: 14.8786
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INFO:tensorflow:global_step/sec: 15.0628
2021-11-27 22:13:32,776 [INFO] tensorflow: global_step/sec: 15.0628
2021-11-27 22:13:32,840 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.771
INFO:tensorflow:global_step/sec: 15.1816
2021-11-27 22:13:32,908 [INFO] tensorflow: global_step/sec: 15.1816
INFO:tensorflow:global_step/sec: 14.8557
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INFO:tensorflow:global_step/sec: 15.4076
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INFO:tensorflow:global_step/sec: 14.6008
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INFO:tensorflow:global_step/sec: 15.1131
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INFO:tensorflow:global_step/sec: 14.3264
2021-11-27 22:13:33,713 [INFO] tensorflow: global_step/sec: 14.3264
2021-11-27 22:13:33,714 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 96/120: loss: 0.00058 learning rate: 0.00011 Time taken: 0:00:01.468922 ETA: 0:00:35.254131
INFO:tensorflow:global_step/sec: 15.2513
2021-11-27 22:13:33,844 [INFO] tensorflow: global_step/sec: 15.2513
INFO:tensorflow:global_step/sec: 15.003
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INFO:tensorflow:global_step/sec: 15.0827
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INFO:tensorflow:global_step/sec: 15.1125
2021-11-27 22:13:34,242 [INFO] tensorflow: global_step/sec: 15.1125
INFO:tensorflow:global_step/sec: 13.9267
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INFO:tensorflow:global_step/sec: 14.2696
2021-11-27 22:13:34,526 [INFO] tensorflow: global_step/sec: 14.2696
2021-11-27 22:13:34,527 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.309
INFO:tensorflow:global_step/sec: 13.3772
2021-11-27 22:13:34,675 [INFO] tensorflow: global_step/sec: 13.3772
INFO:tensorflow:global_step/sec: 14.9418
2021-11-27 22:13:34,809 [INFO] tensorflow: global_step/sec: 14.9418
INFO:tensorflow:global_step/sec: 14.7551
2021-11-27 22:13:34,945 [INFO] tensorflow: global_step/sec: 14.7551
INFO:tensorflow:epoch = 96.9090909090909, learning_rate = 9.589558e-05, loss = 0.0005523006, step = 2132 (5.134 sec)
2021-11-27 22:13:35,080 [INFO] tensorflow: epoch = 96.9090909090909, learning_rate = 9.589558e-05, loss = 0.0005523006, step = 2132 (5.134 sec)
INFO:tensorflow:global_step/sec: 14.711
2021-11-27 22:13:35,081 [INFO] tensorflow: global_step/sec: 14.711
INFO:tensorflow:global_step/sec: 12.8561
2021-11-27 22:13:35,236 [INFO] tensorflow: global_step/sec: 12.8561
2021-11-27 22:13:35,237 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 97/120: loss: 0.00057 learning rate: 0.00009 Time taken: 0:00:01.510840 ETA: 0:00:34.749319
INFO:tensorflow:global_step/sec: 13.9675
2021-11-27 22:13:35,380 [INFO] tensorflow: global_step/sec: 13.9675
INFO:tensorflow:global_step/sec: 14.9383
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INFO:tensorflow:global_step/sec: 15.0593
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INFO:tensorflow:global_step/sec: 14.9271
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INFO:tensorflow:global_step/sec: 15.5292
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INFO:tensorflow:global_step/sec: 15.0751
2021-11-27 22:13:36,175 [INFO] tensorflow: global_step/sec: 15.0751
2021-11-27 22:13:36,240 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.370
INFO:tensorflow:global_step/sec: 15.2464
2021-11-27 22:13:36,306 [INFO] tensorflow: global_step/sec: 15.2464
INFO:tensorflow:global_step/sec: 14.931
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INFO:tensorflow:global_step/sec: 14.4101
2021-11-27 22:13:36,712 [INFO] tensorflow: global_step/sec: 14.4101
2021-11-27 22:13:36,713 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 98/120: loss: 0.00051 learning rate: 0.00008 Time taken: 0:00:01.484409 ETA: 0:00:32.657000
INFO:tensorflow:global_step/sec: 15.0223
2021-11-27 22:13:36,845 [INFO] tensorflow: global_step/sec: 15.0223
INFO:tensorflow:global_step/sec: 15.3027
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INFO:tensorflow:global_step/sec: 15.1061
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INFO:tensorflow:global_step/sec: 14.9271
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INFO:tensorflow:global_step/sec: 14.4789
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INFO:tensorflow:global_step/sec: 14.8067
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INFO:tensorflow:global_step/sec: 14.9415
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INFO:tensorflow:global_step/sec: 14.6001
2021-11-27 22:13:37,917 [INFO] tensorflow: global_step/sec: 14.6001
2021-11-27 22:13:37,918 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.608
INFO:tensorflow:global_step/sec: 15.2626
2021-11-27 22:13:38,048 [INFO] tensorflow: global_step/sec: 15.2626
INFO:tensorflow:global_step/sec: 14.2748
2021-11-27 22:13:38,189 [INFO] tensorflow: global_step/sec: 14.2748
2021-11-27 22:13:38,189 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 99/120: loss: 0.00053 learning rate: 0.00007 Time taken: 0:00:01.477549 ETA: 0:00:31.028531
INFO:tensorflow:global_step/sec: 14.8238
2021-11-27 22:13:38,323 [INFO] tensorflow: global_step/sec: 14.8238
INFO:tensorflow:global_step/sec: 14.8193
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INFO:tensorflow:global_step/sec: 15.6166
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INFO:tensorflow:global_step/sec: 15.198
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INFO:tensorflow:global_step/sec: 14.6753
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INFO:tensorflow:global_step/sec: 14.7144
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INFO:tensorflow:global_step/sec: 15.1402
2021-11-27 22:13:39,122 [INFO] tensorflow: global_step/sec: 15.1402
INFO:tensorflow:global_step/sec: 15.1915
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INFO:tensorflow:global_step/sec: 15.2127
2021-11-27 22:13:39,386 [INFO] tensorflow: global_step/sec: 15.2127
INFO:tensorflow:global_step/sec: 14.866
2021-11-27 22:13:39,520 [INFO] tensorflow: global_step/sec: 14.866
INFO:tensorflow:Saving checkpoints for step-2200.
2021-11-27 22:13:39,584 [INFO] tensorflow: Saving checkpoints for step-2200.
WARNING:tensorflow:Ignoring: /tmp/tmpsujycxfe; No such file or directory
2021-11-27 22:13:39,675 [WARNING] tensorflow: Ignoring: /tmp/tmpsujycxfe; No such file or directory
2021-11-27 22:13:41,958 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 803/803 [00:00<00:00, 24276.16it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 55/55 [00:00<00:00, 23198.58it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 183/183 [00:00<00:00, 24072.69it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 602/602 [00:00<00:00, 25071.95it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 257/257 [00:00<00:00, 23842.34it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 716/716 [00:00<00:00, 23360.05it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 1187/1187 [00:00<00:00, 32942.54it/s]
Epoch 100/120
=========================
Validation cost: 0.000361
Mean average_precision (in %): 30.8107
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 80.0994
floor 0
palette 6.77966
pillar 54.2219
pushcart 0
rackframe 46.9401
rackshelf 49.1903
wall 40.0651
Median Inference Time: 0.006997
2021-11-27 22:13:43,963 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 16.545
INFO:tensorflow:epoch = 100.0, learning_rate = 6.457747e-05, loss = 0.00055886863, step = 2200 (8.954 sec)
2021-11-27 22:13:44,034 [INFO] tensorflow: epoch = 100.0, learning_rate = 6.457747e-05, loss = 0.00055886863, step = 2200 (8.954 sec)
INFO:tensorflow:global_step/sec: 0.442994
2021-11-27 22:13:44,035 [INFO] tensorflow: global_step/sec: 0.442994
2021-11-27 22:13:44,036 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 100/120: loss: 0.00056 learning rate: 0.00006 Time taken: 0:00:05.839059 ETA: 0:01:56.781173
INFO:tensorflow:global_step/sec: 14.5727
2021-11-27 22:13:44,172 [INFO] tensorflow: global_step/sec: 14.5727
INFO:tensorflow:global_step/sec: 14.8189
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INFO:tensorflow:global_step/sec: 14.8315
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INFO:tensorflow:global_step/sec: 14.7101
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INFO:tensorflow:global_step/sec: 15.037
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INFO:tensorflow:global_step/sec: 15.341
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INFO:tensorflow:global_step/sec: 15.1629
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INFO:tensorflow:global_step/sec: 14.6894
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2021-11-27 22:13:45,518 [INFO] tensorflow: global_step/sec: 14.1061
2021-11-27 22:13:45,519 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 101/120: loss: 0.00058 learning rate: 0.00006 Time taken: 0:00:01.487553 ETA: 0:00:28.263500
INFO:tensorflow:global_step/sec: 15.2236
2021-11-27 22:13:45,649 [INFO] tensorflow: global_step/sec: 15.2236
2021-11-27 22:13:45,650 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.314
INFO:tensorflow:global_step/sec: 14.2657
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INFO:tensorflow:global_step/sec: 14.6146
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INFO:tensorflow:global_step/sec: 15.0145
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INFO:tensorflow:global_step/sec: 14.7514
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INFO:tensorflow:global_step/sec: 14.6666
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INFO:tensorflow:global_step/sec: 15.27
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INFO:tensorflow:global_step/sec: 14.7994
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INFO:tensorflow:global_step/sec: 14.7466
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INFO:tensorflow:global_step/sec: 13.3923
2021-11-27 22:13:47,016 [INFO] tensorflow: global_step/sec: 13.3923
2021-11-27 22:13:47,017 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 102/120: loss: 0.00057 learning rate: 0.00005 Time taken: 0:00:01.490161 ETA: 0:00:26.822906
INFO:tensorflow:global_step/sec: 14.4915
2021-11-27 22:13:47,154 [INFO] tensorflow: global_step/sec: 14.4915
INFO:tensorflow:global_step/sec: 14.3181
2021-11-27 22:13:47,294 [INFO] tensorflow: global_step/sec: 14.3181
2021-11-27 22:13:47,363 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.375
INFO:tensorflow:global_step/sec: 14.3946
2021-11-27 22:13:47,433 [INFO] tensorflow: global_step/sec: 14.3946
INFO:tensorflow:global_step/sec: 14.6103
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INFO:tensorflow:global_step/sec: 15.0284
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INFO:tensorflow:global_step/sec: 15.2751
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INFO:tensorflow:global_step/sec: 14.5911
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INFO:tensorflow:global_step/sec: 14.3818
2021-11-27 22:13:48,528 [INFO] tensorflow: global_step/sec: 14.3818
2021-11-27 22:13:48,529 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 103/120: loss: 0.00059 learning rate: 0.00004 Time taken: 0:00:01.513487 ETA: 0:00:25.729281
INFO:tensorflow:global_step/sec: 14.4868
2021-11-27 22:13:48,666 [INFO] tensorflow: global_step/sec: 14.4868
INFO:tensorflow:global_step/sec: 14.7924
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INFO:tensorflow:global_step/sec: 14.829
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INFO:tensorflow:global_step/sec: 15.2678
2021-11-27 22:13:49,067 [INFO] tensorflow: global_step/sec: 15.2678
2021-11-27 22:13:49,068 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.675
INFO:tensorflow:epoch = 103.4090909090909, learning_rate = 4.175296e-05, loss = 0.0005593177, step = 2275 (5.102 sec)
2021-11-27 22:13:49,136 [INFO] tensorflow: epoch = 103.4090909090909, learning_rate = 4.175296e-05, loss = 0.0005593177, step = 2275 (5.102 sec)
INFO:tensorflow:global_step/sec: 14.4317
2021-11-27 22:13:49,206 [INFO] tensorflow: global_step/sec: 14.4317
INFO:tensorflow:global_step/sec: 14.6899
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INFO:tensorflow:global_step/sec: 14.9752
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INFO:tensorflow:global_step/sec: 15.0527
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INFO:tensorflow:global_step/sec: 14.3406
2021-11-27 22:13:50,017 [INFO] tensorflow: global_step/sec: 14.3406
2021-11-27 22:13:50,018 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 104/120: loss: 0.00057 learning rate: 0.00004 Time taken: 0:00:01.488014 ETA: 0:00:23.808220
INFO:tensorflow:global_step/sec: 14.797
2021-11-27 22:13:50,153 [INFO] tensorflow: global_step/sec: 14.797
INFO:tensorflow:global_step/sec: 14.9948
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2021-11-27 22:13:50,692 [INFO] tensorflow: global_step/sec: 14.8354
2021-11-27 22:13:50,759 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.137
INFO:tensorflow:global_step/sec: 15.1909
2021-11-27 22:13:50,824 [INFO] tensorflow: global_step/sec: 15.1909
INFO:tensorflow:global_step/sec: 15.036
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INFO:tensorflow:global_step/sec: 14.9644
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INFO:tensorflow:global_step/sec: 14.9499
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INFO:tensorflow:global_step/sec: 14.759
2021-11-27 22:13:51,492 [INFO] tensorflow: global_step/sec: 14.759
2021-11-27 22:13:51,493 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 105/120: loss: 0.00054 learning rate: 0.00003 Time taken: 0:00:01.475093 ETA: 0:00:22.126400
INFO:tensorflow:global_step/sec: 14.9596
2021-11-27 22:13:51,625 [INFO] tensorflow: global_step/sec: 14.9596
INFO:tensorflow:global_step/sec: 15.1018
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INFO:tensorflow:global_step/sec: 15.1254
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INFO:tensorflow:global_step/sec: 14.7954
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INFO:tensorflow:global_step/sec: 15.0259
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INFO:tensorflow:global_step/sec: 14.978
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INFO:tensorflow:global_step/sec: 14.4577
2021-11-27 22:13:52,430 [INFO] tensorflow: global_step/sec: 14.4577
2021-11-27 22:13:52,431 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.832
INFO:tensorflow:global_step/sec: 15.4703
2021-11-27 22:13:52,559 [INFO] tensorflow: global_step/sec: 15.4703
INFO:tensorflow:global_step/sec: 14.93
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INFO:tensorflow:global_step/sec: 14.0773
2021-11-27 22:13:52,971 [INFO] tensorflow: global_step/sec: 14.0773
2021-11-27 22:13:52,972 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 106/120: loss: 0.00052 learning rate: 0.00003 Time taken: 0:00:01.476597 ETA: 0:00:20.672352
INFO:tensorflow:global_step/sec: 15.3114
2021-11-27 22:13:53,102 [INFO] tensorflow: global_step/sec: 15.3114
INFO:tensorflow:global_step/sec: 15.1175
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INFO:tensorflow:global_step/sec: 15.5868
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INFO:tensorflow:global_step/sec: 15.1488
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INFO:tensorflow:global_step/sec: 15.0376
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INFO:tensorflow:global_step/sec: 14.8196
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INFO:tensorflow:global_step/sec: 15.1396
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INFO:tensorflow:global_step/sec: 14.8561
2021-11-27 22:13:54,029 [INFO] tensorflow: global_step/sec: 14.8561
2021-11-27 22:13:54,098 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.997
INFO:tensorflow:global_step/sec: 14.7577
2021-11-27 22:13:54,165 [INFO] tensorflow: global_step/sec: 14.7577
INFO:tensorflow:epoch = 106.86363636363636, learning_rate = 2.6839094e-05, loss = 0.0005783711, step = 2351 (5.097 sec)
2021-11-27 22:13:54,233 [INFO] tensorflow: epoch = 106.86363636363636, learning_rate = 2.6839094e-05, loss = 0.0005783711, step = 2351 (5.097 sec)
INFO:tensorflow:global_step/sec: 14.5509
2021-11-27 22:13:54,302 [INFO] tensorflow: global_step/sec: 14.5509
INFO:tensorflow:global_step/sec: 13.7995
2021-11-27 22:13:54,447 [INFO] tensorflow: global_step/sec: 13.7995
2021-11-27 22:13:54,448 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 107/120: loss: 0.00055 learning rate: 0.00003 Time taken: 0:00:01.473645 ETA: 0:00:19.157388
INFO:tensorflow:global_step/sec: 14.205
2021-11-27 22:13:54,588 [INFO] tensorflow: global_step/sec: 14.205
INFO:tensorflow:global_step/sec: 15.021
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INFO:tensorflow:global_step/sec: 15.1786
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INFO:tensorflow:global_step/sec: 15.4445
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INFO:tensorflow:global_step/sec: 14.3361
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INFO:tensorflow:global_step/sec: 15.227
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INFO:tensorflow:global_step/sec: 14.7772
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INFO:tensorflow:global_step/sec: 14.7789
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INFO:tensorflow:global_step/sec: 15.0687
2021-11-27 22:13:55,788 [INFO] tensorflow: global_step/sec: 15.0687
2021-11-27 22:13:55,789 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.138
INFO:tensorflow:global_step/sec: 14.2253
2021-11-27 22:13:55,929 [INFO] tensorflow: global_step/sec: 14.2253
2021-11-27 22:13:55,930 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 108/120: loss: 0.00061 learning rate: 0.00002 Time taken: 0:00:01.481451 ETA: 0:00:17.777407
INFO:tensorflow:global_step/sec: 15.1751
2021-11-27 22:13:56,061 [INFO] tensorflow: global_step/sec: 15.1751
INFO:tensorflow:global_step/sec: 15.0851
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INFO:tensorflow:global_step/sec: 14.9349
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INFO:tensorflow:global_step/sec: 14.8667
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INFO:tensorflow:global_step/sec: 14.6712
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INFO:tensorflow:global_step/sec: 15.0774
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INFO:tensorflow:global_step/sec: 14.7904
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INFO:tensorflow:global_step/sec: 14.8893
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INFO:tensorflow:global_step/sec: 14.6063
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INFO:tensorflow:global_step/sec: 14.5439
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INFO:tensorflow:global_step/sec: 13.9451
2021-11-27 22:13:57,418 [INFO] tensorflow: global_step/sec: 13.9451
2021-11-27 22:13:57,419 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 109/120: loss: 0.00052 learning rate: 0.00002 Time taken: 0:00:01.486024 ETA: 0:00:16.346268
2021-11-27 22:13:57,481 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 59.117
INFO:tensorflow:global_step/sec: 15.4105
2021-11-27 22:13:57,548 [INFO] tensorflow: global_step/sec: 15.4105
INFO:tensorflow:global_step/sec: 14.9786
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INFO:tensorflow:global_step/sec: 14.7983
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INFO:tensorflow:global_step/sec: 14.8149
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INFO:tensorflow:global_step/sec: 14.5381
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INFO:tensorflow:global_step/sec: 14.6208
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INFO:tensorflow:global_step/sec: 14.9362
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INFO:tensorflow:global_step/sec: 15.4475
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INFO:tensorflow:global_step/sec: 15.3136
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INFO:tensorflow:global_step/sec: 15.0841
2021-11-27 22:13:58,753 [INFO] tensorflow: global_step/sec: 15.0841
INFO:tensorflow:Saving checkpoints for step-2420.
2021-11-27 22:13:58,819 [INFO] tensorflow: Saving checkpoints for step-2420.
WARNING:tensorflow:Ignoring: /tmp/tmp085v6unk; No such file or directory
2021-11-27 22:13:58,906 [WARNING] tensorflow: Ignoring: /tmp/tmp085v6unk; No such file or directory
2021-11-27 22:14:01,162 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 811/811 [00:00<00:00, 23914.88it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 57/57 [00:00<00:00, 23921.89it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 177/177 [00:00<00:00, 24374.28it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 572/572 [00:00<00:00, 25186.52it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 286/286 [00:00<00:00, 23310.29it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 719/719 [00:00<00:00, 23982.13it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 1021/1021 [00:00<00:00, 33398.72it/s]
Epoch 110/120
=========================
Validation cost: 0.000356
Mean average_precision (in %): 32.1409
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 83.3622
floor 0
palette 9.60187
pillar 57.2921
pushcart 0
rackframe 46.9219
rackshelf 51.9863
wall 40.1041
Median Inference Time: 0.007966
INFO:tensorflow:epoch = 110.0, learning_rate = 1.7969083e-05, loss = 0.0005546734, step = 2420 (8.912 sec)
2021-11-27 22:14:03,145 [INFO] tensorflow: epoch = 110.0, learning_rate = 1.7969083e-05, loss = 0.0005546734, step = 2420 (8.912 sec)
INFO:tensorflow:global_step/sec: 0.455199
2021-11-27 22:14:03,146 [INFO] tensorflow: global_step/sec: 0.455199
2021-11-27 22:14:03,147 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 110/120: loss: 0.00055 learning rate: 0.00002 Time taken: 0:00:05.721983 ETA: 0:00:57.219834
INFO:tensorflow:global_step/sec: 13.6625
2021-11-27 22:14:03,293 [INFO] tensorflow: global_step/sec: 13.6625
INFO:tensorflow:global_step/sec: 14.7438
2021-11-27 22:14:03,428 [INFO] tensorflow: global_step/sec: 14.7438
2021-11-27 22:14:03,429 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 16.813
INFO:tensorflow:global_step/sec: 13.9278
2021-11-27 22:14:03,572 [INFO] tensorflow: global_step/sec: 13.9278
INFO:tensorflow:global_step/sec: 14.1084
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INFO:tensorflow:global_step/sec: 14.4681
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INFO:tensorflow:global_step/sec: 14.7191
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INFO:tensorflow:global_step/sec: 14.1071
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INFO:tensorflow:global_step/sec: 14.9028
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INFO:tensorflow:global_step/sec: 14.7381
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INFO:tensorflow:global_step/sec: 14.0034
2021-11-27 22:14:04,678 [INFO] tensorflow: global_step/sec: 14.0034
2021-11-27 22:14:04,678 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 111/120: loss: 0.00055 learning rate: 0.00002 Time taken: 0:00:01.532775 ETA: 0:00:13.794974
INFO:tensorflow:global_step/sec: 14.7861
2021-11-27 22:14:04,813 [INFO] tensorflow: global_step/sec: 14.7861
INFO:tensorflow:global_step/sec: 13.8382
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INFO:tensorflow:global_step/sec: 14.5552
2021-11-27 22:14:05,095 [INFO] tensorflow: global_step/sec: 14.5552
2021-11-27 22:14:05,163 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.669
INFO:tensorflow:global_step/sec: 14.5795
2021-11-27 22:14:05,232 [INFO] tensorflow: global_step/sec: 14.5795
INFO:tensorflow:global_step/sec: 14.9513
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INFO:tensorflow:global_step/sec: 15.0493
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INFO:tensorflow:global_step/sec: 14.5385
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INFO:tensorflow:global_step/sec: 14.8733
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INFO:tensorflow:global_step/sec: 14.433
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INFO:tensorflow:global_step/sec: 15.3317
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INFO:tensorflow:global_step/sec: 13.509
2021-11-27 22:14:06,188 [INFO] tensorflow: global_step/sec: 13.509
2021-11-27 22:14:06,188 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 112/120: loss: 0.00057 learning rate: 0.00001 Time taken: 0:00:01.506736 ETA: 0:00:12.053888
INFO:tensorflow:global_step/sec: 14.458
2021-11-27 22:14:06,326 [INFO] tensorflow: global_step/sec: 14.458
INFO:tensorflow:global_step/sec: 14.5047
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INFO:tensorflow:global_step/sec: 14.5484
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INFO:tensorflow:global_step/sec: 14.8116
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INFO:tensorflow:global_step/sec: 14.9014
2021-11-27 22:14:06,871 [INFO] tensorflow: global_step/sec: 14.9014
2021-11-27 22:14:06,871 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.560
INFO:tensorflow:global_step/sec: 14.3655
2021-11-27 22:14:07,010 [INFO] tensorflow: global_step/sec: 14.3655
INFO:tensorflow:global_step/sec: 14.6463
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INFO:tensorflow:global_step/sec: 14.5217
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INFO:tensorflow:global_step/sec: 15.0949
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INFO:tensorflow:global_step/sec: 14.7148
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INFO:tensorflow:global_step/sec: 13.6502
2021-11-27 22:14:07,699 [INFO] tensorflow: global_step/sec: 13.6502
2021-11-27 22:14:07,700 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 113/120: loss: 0.00049 learning rate: 0.00001 Time taken: 0:00:01.511716 ETA: 0:00:10.582013
INFO:tensorflow:global_step/sec: 13.9831
2021-11-27 22:14:07,842 [INFO] tensorflow: global_step/sec: 13.9831
INFO:tensorflow:global_step/sec: 14.1898
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INFO:tensorflow:global_step/sec: 14.6837
2021-11-27 22:14:08,119 [INFO] tensorflow: global_step/sec: 14.6837
INFO:tensorflow:epoch = 113.36363636363636, learning_rate = 1.168576e-05, loss = 0.0005457344, step = 2494 (5.107 sec)
2021-11-27 22:14:08,252 [INFO] tensorflow: epoch = 113.36363636363636, learning_rate = 1.168576e-05, loss = 0.0005457344, step = 2494 (5.107 sec)
INFO:tensorflow:global_step/sec: 14.9502
2021-11-27 22:14:08,253 [INFO] tensorflow: global_step/sec: 14.9502
INFO:tensorflow:global_step/sec: 14.4158
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INFO:tensorflow:global_step/sec: 14.4871
2021-11-27 22:14:08,530 [INFO] tensorflow: global_step/sec: 14.4871
2021-11-27 22:14:08,596 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 57.990
INFO:tensorflow:global_step/sec: 14.9496
2021-11-27 22:14:08,664 [INFO] tensorflow: global_step/sec: 14.9496
INFO:tensorflow:global_step/sec: 14.7773
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INFO:tensorflow:global_step/sec: 14.8251
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INFO:tensorflow:global_step/sec: 14.0095
2021-11-27 22:14:09,211 [INFO] tensorflow: global_step/sec: 14.0095
2021-11-27 22:14:09,212 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 114/120: loss: 0.00051 learning rate: 0.00001 Time taken: 0:00:01.507674 ETA: 0:00:09.046042
INFO:tensorflow:global_step/sec: 14.265
2021-11-27 22:14:09,351 [INFO] tensorflow: global_step/sec: 14.265
INFO:tensorflow:global_step/sec: 14.7811
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INFO:tensorflow:global_step/sec: 15.0106
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INFO:tensorflow:global_step/sec: 14.6874
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INFO:tensorflow:global_step/sec: 14.5284
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INFO:tensorflow:global_step/sec: 14.6142
2021-11-27 22:14:10,305 [INFO] tensorflow: global_step/sec: 14.6142
2021-11-27 22:14:10,306 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.506
INFO:tensorflow:global_step/sec: 14.4073
2021-11-27 22:14:10,444 [INFO] tensorflow: global_step/sec: 14.4073
INFO:tensorflow:global_step/sec: 14.6873
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INFO:tensorflow:global_step/sec: 13.3242
2021-11-27 22:14:10,730 [INFO] tensorflow: global_step/sec: 13.3242
2021-11-27 22:14:10,731 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 115/120: loss: 0.00054 learning rate: 0.00001 Time taken: 0:00:01.519587 ETA: 0:00:07.597936
INFO:tensorflow:global_step/sec: 14.6239
2021-11-27 22:14:10,867 [INFO] tensorflow: global_step/sec: 14.6239
INFO:tensorflow:global_step/sec: 14.5794
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INFO:tensorflow:global_step/sec: 14.8667
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INFO:tensorflow:global_step/sec: 14.5006
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INFO:tensorflow:global_step/sec: 15.0917
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INFO:tensorflow:global_step/sec: 14.9849
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INFO:tensorflow:global_step/sec: 15.0553
2021-11-27 22:14:11,953 [INFO] tensorflow: global_step/sec: 15.0553
2021-11-27 22:14:12,021 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.301
INFO:tensorflow:global_step/sec: 14.6977
2021-11-27 22:14:12,089 [INFO] tensorflow: global_step/sec: 14.6977
INFO:tensorflow:global_step/sec: 13.9754
2021-11-27 22:14:12,232 [INFO] tensorflow: global_step/sec: 13.9754
2021-11-27 22:14:12,233 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 116/120: loss: 0.00057 learning rate: 0.00001 Time taken: 0:00:01.501678 ETA: 0:00:06.006714
INFO:tensorflow:global_step/sec: 15.1511
2021-11-27 22:14:12,364 [INFO] tensorflow: global_step/sec: 15.1511
INFO:tensorflow:global_step/sec: 14.4551
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INFO:tensorflow:global_step/sec: 14.612
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INFO:tensorflow:global_step/sec: 14.7892
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INFO:tensorflow:global_step/sec: 14.5904
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INFO:tensorflow:global_step/sec: 14.6879
2021-11-27 22:14:13,048 [INFO] tensorflow: global_step/sec: 14.6879
INFO:tensorflow:global_step/sec: 14.8979
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INFO:tensorflow:global_step/sec: 15.0688
2021-11-27 22:14:13,314 [INFO] tensorflow: global_step/sec: 15.0688
INFO:tensorflow:epoch = 116.77272727272728, learning_rate = 7.5555e-06, loss = 0.00049362035, step = 2569 (5.129 sec)
2021-11-27 22:14:13,382 [INFO] tensorflow: epoch = 116.77272727272728, learning_rate = 7.5555e-06, loss = 0.00049362035, step = 2569 (5.129 sec)
INFO:tensorflow:global_step/sec: 14.7136
2021-11-27 22:14:13,450 [INFO] tensorflow: global_step/sec: 14.7136
INFO:tensorflow:global_step/sec: 14.9746
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INFO:tensorflow:global_step/sec: 13.7404
2021-11-27 22:14:13,730 [INFO] tensorflow: global_step/sec: 13.7404
2021-11-27 22:14:13,730 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 117/120: loss: 0.00058 learning rate: 0.00001 Time taken: 0:00:01.496253 ETA: 0:00:04.488758
2021-11-27 22:14:13,731 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.507
INFO:tensorflow:global_step/sec: 14.8639
2021-11-27 22:14:13,864 [INFO] tensorflow: global_step/sec: 14.8639
INFO:tensorflow:global_step/sec: 14.7895
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2021-11-27 22:14:14,138 [INFO] tensorflow: global_step/sec: 14.3918
INFO:tensorflow:global_step/sec: 14.2683
2021-11-27 22:14:14,278 [INFO] tensorflow: global_step/sec: 14.2683
INFO:tensorflow:global_step/sec: 14.4947
2021-11-27 22:14:14,416 [INFO] tensorflow: global_step/sec: 14.4947
INFO:tensorflow:global_step/sec: 14.8349
2021-11-27 22:14:14,551 [INFO] tensorflow: global_step/sec: 14.8349
INFO:tensorflow:global_step/sec: 14.7231
2021-11-27 22:14:14,687 [INFO] tensorflow: global_step/sec: 14.7231
INFO:tensorflow:global_step/sec: 14.0777
2021-11-27 22:14:14,829 [INFO] tensorflow: global_step/sec: 14.0777
INFO:tensorflow:global_step/sec: 14.6964
2021-11-27 22:14:14,965 [INFO] tensorflow: global_step/sec: 14.6964
INFO:tensorflow:global_step/sec: 15.074
2021-11-27 22:14:15,098 [INFO] tensorflow: global_step/sec: 15.074
INFO:tensorflow:global_step/sec: 13.9061
2021-11-27 22:14:15,242 [INFO] tensorflow: global_step/sec: 13.9061
2021-11-27 22:14:15,243 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 118/120: loss: 0.00056 learning rate: 0.00001 Time taken: 0:00:01.511011 ETA: 0:00:03.022022
INFO:tensorflow:global_step/sec: 14.5515
2021-11-27 22:14:15,379 [INFO] tensorflow: global_step/sec: 14.5515
2021-11-27 22:14:15,448 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.233
INFO:tensorflow:global_step/sec: 14.5891
2021-11-27 22:14:15,516 [INFO] tensorflow: global_step/sec: 14.5891
INFO:tensorflow:global_step/sec: 14.9013
2021-11-27 22:14:15,651 [INFO] tensorflow: global_step/sec: 14.9013
INFO:tensorflow:global_step/sec: 15.0269
2021-11-27 22:14:15,784 [INFO] tensorflow: global_step/sec: 15.0269
INFO:tensorflow:global_step/sec: 14.5289
2021-11-27 22:14:15,921 [INFO] tensorflow: global_step/sec: 14.5289
INFO:tensorflow:global_step/sec: 14.851
2021-11-27 22:14:16,056 [INFO] tensorflow: global_step/sec: 14.851
INFO:tensorflow:global_step/sec: 14.6678
2021-11-27 22:14:16,192 [INFO] tensorflow: global_step/sec: 14.6678
INFO:tensorflow:global_step/sec: 14.872
2021-11-27 22:14:16,327 [INFO] tensorflow: global_step/sec: 14.872
INFO:tensorflow:global_step/sec: 14.5707
2021-11-27 22:14:16,464 [INFO] tensorflow: global_step/sec: 14.5707
INFO:tensorflow:global_step/sec: 14.3698
2021-11-27 22:14:16,603 [INFO] tensorflow: global_step/sec: 14.3698
INFO:tensorflow:global_step/sec: 14.2
2021-11-27 22:14:16,744 [INFO] tensorflow: global_step/sec: 14.2
2021-11-27 22:14:16,745 [INFO] iva.detectnet_v2.tfhooks.task_progress_monitor_hook: Epoch 119/120: loss: 0.00056 learning rate: 0.00001 Time taken: 0:00:01.503073 ETA: 0:00:01.503073
INFO:tensorflow:global_step/sec: 14.925
2021-11-27 22:14:16,878 [INFO] tensorflow: global_step/sec: 14.925
INFO:tensorflow:global_step/sec: 14.7784
2021-11-27 22:14:17,013 [INFO] tensorflow: global_step/sec: 14.7784
INFO:tensorflow:global_step/sec: 14.4469
2021-11-27 22:14:17,152 [INFO] tensorflow: global_step/sec: 14.4469
2021-11-27 22:14:17,152 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.685
INFO:tensorflow:global_step/sec: 14.4737
2021-11-27 22:14:17,290 [INFO] tensorflow: global_step/sec: 14.4737
INFO:tensorflow:global_step/sec: 14.8276
2021-11-27 22:14:17,425 [INFO] tensorflow: global_step/sec: 14.8276
INFO:tensorflow:global_step/sec: 14.8145
2021-11-27 22:14:17,560 [INFO] tensorflow: global_step/sec: 14.8145
INFO:tensorflow:global_step/sec: 14.9416
2021-11-27 22:14:17,694 [INFO] tensorflow: global_step/sec: 14.9416
INFO:tensorflow:global_step/sec: 14.4597
2021-11-27 22:14:17,832 [INFO] tensorflow: global_step/sec: 14.4597
INFO:tensorflow:global_step/sec: 14.7073
2021-11-27 22:14:17,968 [INFO] tensorflow: global_step/sec: 14.7073
INFO:tensorflow:global_step/sec: 14.5652
2021-11-27 22:14:18,105 [INFO] tensorflow: global_step/sec: 14.5652
INFO:tensorflow:Saving checkpoints for step-2640.
2021-11-27 22:14:18,174 [INFO] tensorflow: Saving checkpoints for step-2640.
WARNING:tensorflow:Ignoring: /tmp/tmpst265022; No such file or directory
2021-11-27 22:14:18,265 [WARNING] tensorflow: Ignoring: /tmp/tmpst265022; No such file or directory
2021-11-27 22:14:20,584 [INFO] iva.detectnet_v2.evaluation.evaluation: step 0 / 3, 0.00s/step
Matching predictions to ground truth, class 1/9.: 100%|█| 671/671 [00:00<00:00, 24039.72it/s]
Matching predictions to ground truth, class 3/9.: 100%|█| 33/33 [00:00<00:00, 22572.09it/s]
Matching predictions to ground truth, class 4/9.: 100%|█| 134/134 [00:00<00:00, 24012.51it/s]
Matching predictions to ground truth, class 6/9.: 100%|█| 532/532 [00:00<00:00, 23845.53it/s]
Matching predictions to ground truth, class 7/9.: 100%|█| 198/198 [00:00<00:00, 24022.22it/s]
Matching predictions to ground truth, class 8/9.: 100%|█| 702/702 [00:00<00:00, 23627.23it/s]
Matching predictions to ground truth, class 9/9.: 100%|█| 954/954 [00:00<00:00, 30982.08it/s]
Epoch 120/120
=========================
Validation cost: 0.000278
Mean average_precision (in %): 30.6785
class name average precision (in %)
------------ --------------------------
cardbox 0
ceiling 80.6844
floor 0
palette 10.2041
pillar 53.995
pushcart 0
rackframe 43.0036
rackshelf 48.4257
wall 39.7941
Median Inference Time: 0.007785
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:95: The name tf.reset_default_graph is deprecated. Please use tf.compat.v1.reset_default_graph instead.
2021-11-27 22:14:22,764 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:95: The name tf.reset_default_graph is deprecated. Please use tf.compat.v1.reset_default_graph instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:98: The name tf.placeholder_with_default is deprecated. Please use tf.compat.v1.placeholder_with_default instead.
2021-11-27 22:14:22,764 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:98: The name tf.placeholder_with_default is deprecated. Please use tf.compat.v1.placeholder_with_default instead.
2021-11-27 22:14:22,766 [INFO] modulus.hooks.sample_counter_hook: Train Samples / sec: 58.685
Time taken to run __main__:main: 0:04:24.418081.
2021-11-27 17:14:24,569 [INFO] tlt.components.docker_handler.docker_handler: Stopping container.
|
pantelis-classes/omniverse-ai/Wikipages/Editing Synthetic Data Generation (Python API).md | # Synthetic Data in Omniverse from Isaac Sim
Omniverse comes with synthetic data generation samples in Python. These can be found in (home/.local/share/ov/pkg/isaac_sim-2021.2.0/python_samples)
## Offline Dataset Generation
This example will demonstrate how to generate synthetic dataset offline which can be used for training deep neural networks using default values.
From the package root folder (home/.local/share/ov/pkg/isaac_sim-2021.2.0/) run this command to generate synthetic data:
./python.sh standalone_examples/replicator/offline_generation.py
These are the arguments we can use:
1. --scenario: Specify the USD stage to load from omniverse server for dataset generation.
1. --num_frames: Number of frames to record.
1. --max_queue_size: Maximum size of queue to store and process synthetic data. If value of this field is less than or equal to zero, the queue size is infinite.
1. --data_dir: Location where data will be output. Default is ./output
1. --writer_mode: Specify output format - npy or kitti. Default is npy.
When KittiWriter is used with the --writer_mode kitti argument, two more arguments become available.
6. --classes: Which classes to write labels for. Defaults to all classes.
7. --train_size: Number of frames for training set. Defaults to 8.
queue size is infinite.
With arguments, the above command looks like:
./python.sh standalone_examples/replicator/offline_generation.py --scenario omniverse://<server-name>/Isaac/Samples/Synthetic_Data/Stage/warehouse_with_sensors.usd --num_frames 10 --max_queue_size 500
All output data is stored within (home/.local/share/ov/pkg/isaac_sim-2021.1.1/output)
## Offline Training with TLT
To leverage TLT, we need to have a dataset in the Kitti format. NVIDIA Transfer Learning Toolkit (TLT) is a Python-based AI toolkit for taking purpose-built pretrained AI models and customizing them with your own data.
### Offline Kitti Dataset Generation
for this we add the argument --writer_mode kitti and specify the classes like in this example (not specifying an argument makes it use the default):
./python.sh standalone_examples/replicator/offline_generation.py --writer_mode kitti --classes ceiling floor --num_frames 500 --train_size 100
![image](https://user-images.githubusercontent.com/589439/143666365-9cbab570-213f-403b-bdc9-d891025fabac.png)
![image](https://user-images.githubusercontent.com/589439/143666538-47885861-2340-4fca-9507-8a1a66d82fe9.png)
![image](https://user-images.githubusercontent.com/589439/143666560-4a7dd70c-abde-4af8-a1c7-16eab5d99bf3.png)
![omniverse data gen](https://user-images.githubusercontent.com/589439/143667012-183800ff-f197-44a7-9677-d19940a06179.gif)
The python scripts can be extensively modified to generate more customized datasets (code deep dive to come).
- The output of the synthetic data generation can be found in: `~/.local/share/ov/pkg/isaac_sim-2021.2.0/output`
![image](https://user-images.githubusercontent.com/589439/143666727-f7a06dbc-aba6-410f-8bd5-0aa24ecf38d3.png)
- The dataset is divided into two folders; A Training and Test Dataset. The training dataset contains **images** and **labels** of the warehouse.
![image](https://user-images.githubusercontent.com/589439/143666820-b12aafdd-f1e1-4c46-889c-34af1c9ca929.png)
![image](https://user-images.githubusercontent.com/589439/143666829-813f9715-3a2d-49f1-9124-5a690681accc.png)
![image](https://user-images.githubusercontent.com/589439/143666852-90d659de-01a0-4685-bf36-42868e1c77d9.png)
![image](https://user-images.githubusercontent.com/589439/143666866-5896317b-1255-4e67-abe7-5f3ff03be288.png)
- The test dataset contains only **images**.
![image](https://user-images.githubusercontent.com/589439/143666874-a453b635-63e6-44e0-94c1-7127e1c7f729.png)
![omniversepicgen](https://user-images.githubusercontent.com/589439/143667064-d0136cd5-9b3e-4b5d-987f-c013ff08d401.gif)
|
pantelis-classes/omniverse-ai/Wikipages/Isaac Sim SDK Omniverse Installation.md | ## Prerequisites
Ubuntu 18.04 LTS required
Nvidia drivers 470 or higher
### Installing Nvidia Drivers on Ubuntu 18.04 LTS
sudo apt-add-repository -r ppa:graphics-drivers/ppa
![image](https://user-images.githubusercontent.com/589439/143662835-6d5624b2-b78d-4ff2-acc3-efadc64d58a2.png)
sudo apt update
![image](https://user-images.githubusercontent.com/589439/143662852-f99e89cc-1c28-4039-8c25-95c470de171f.png)
sudo apt remove nvidia*
![image](https://user-images.githubusercontent.com/589439/143662863-5dbc78c5-c175-495e-bd36-5b214557774c.png)
![image](https://user-images.githubusercontent.com/589439/143662877-cd6abe58-973f-4da1-ac1c-9fe5d28a5853.png)
sudo apt autoremove
![image](https://user-images.githubusercontent.com/589439/143662895-53e3155b-e8bf-498b-9bb3-4cbe39e1354a.png)
![image](https://user-images.githubusercontent.com/589439/143662915-70024577-3531-46da-8f6e-ea2d8d230e8a.png)
sudo ubuntu-drivers autoinstall
![image](https://user-images.githubusercontent.com/589439/143662959-6b21b9f4-5462-4b9d-9a29-083fad49eafe.png)
sudo apt install nvidia-driver-470
![image](https://user-images.githubusercontent.com/589439/143662965-5e05ee0d-a48f-4161-a086-ab03bf6854bf.png)
- Restart your PC.
- Run nvidia-smi to make sure you are on the latest nvidia drivers for Isaac.
nvidia-smi
![image](https://user-images.githubusercontent.com/589439/143663079-a9503fd4-75f1-4bb0-bfd8-ada3bd9fa2ec.png)
## Omniverse and Isaac Sim installation (executable)
### 1. Create nvidia developer account. This is required to access some of the downloads as well as obtaining API keys for Nvidia NGC
- Go to this <a href="https://developer.nvidia.com/developer-program">link</a> and create an account.
![image](https://user-images.githubusercontent.com/589439/143655734-92f93f94-723b-4a03-aee3-9004ebdfa931.png)
- Fill out your NVIDIA profile.
![image](https://user-images.githubusercontent.com/589439/143655803-423dddd8-398e-49e0-839f-d96a5e655441.png)
### 2. Go to this <a href="https://www.nvidia.com/en-us/omniverse/">omniverse link</a> and download Omniverse and install.
![image](https://user-images.githubusercontent.com/589439/143158851-a4f7a00b-4f25-40e0-ae2e-2fba3edef08e.png)
- Fill out the form.
![image](https://user-images.githubusercontent.com/589439/143158880-17506781-abc2-4188-aca3-4546dcb475f9.png)
- Click the download link for Linux.
![image](https://user-images.githubusercontent.com/589439/143158912-97fb24ad-8b49-432e-a3d7-4badb0977714.png)
- Download and save the AppImage file to your ~/Downloads folder.
![image](https://user-images.githubusercontent.com/589439/143158967-afad1831-822f-4440-9a4b-9248c909007d.png)
- Run these commands to execute the AppImage.
cd ~/Downloads
ls
chmod +x omniverse-launcher-linux.AppImage
./omniverse-launcher-linux.AppImage
![image](https://user-images.githubusercontent.com/589439/143656306-85f1aefd-a6a8-4f07-a2e9-b7153ff175ce.png)
### 3. Login to Omniverse to install Isaac Sim 2021.
- Login with your NVIDIA credentials.
![image](https://user-images.githubusercontent.com/589439/143160948-90380e23-e8cc-42b3-8933-4d88c5c9bc90.png)
- Accept the terms of agreement.
![image](https://user-images.githubusercontent.com/589439/143161008-59913f3c-cfde-4c9f-93d4-609dc0346469.png)
- Click continue. (default paths)
![image](https://user-images.githubusercontent.com/589439/143161046-21afc550-6bf7-450c-b023-3296de59d7b4.png)
- Install cache.
![image](https://user-images.githubusercontent.com/589439/143161192-9936a489-e81d-4ccc-a2e0-caf120ce92c4.png)
### 4. Installing Isaac through Omniverse.
- Click the Exchange tab in Omniverse.
![image](https://user-images.githubusercontent.com/589439/143165080-9daa5e96-99c0-4e60-9a40-ff4f77944311.png)
- Search for Isaac and Click Isaac Sim.
![image](https://user-images.githubusercontent.com/589439/143165387-659a75bf-ba62-49e4-9bab-320b0da9eeb1.png)
- Click install.
![image](https://user-images.githubusercontent.com/589439/143165778-75f9cbea-b93b-4c0a-9661-269ec0e643f5.png)
### 5. Go to the nucleus tab and create a nucleus local server to run the Omniverse Isaac Sim Samples.
- Create your local nucleus account by clicking the Nucleus tab in Omniverse.
- Click Add Local Nucleus Service.
![image](https://user-images.githubusercontent.com/589439/143163402-c38ef3e5-64a8-437f-8a4c-7f978b37e40b.png)
- Click Next. (Default Path)
![image](https://user-images.githubusercontent.com/589439/143163446-5fa6c2bc-6437-4239-bcd7-5be8f9159de7.png)
- Create Administrator Account.
- Go to this <a href="https://developer.nvidia.com/nvidia-isaac-sim-assets-20211">link</a> and download the Isaac Sim Assets.
![image](https://user-images.githubusercontent.com/589439/143163494-95fba91c-12b3-4228-ae21-39ce639d66b4.png)
- Unzip the by going to your downloads folder and right clicking isaac-sim-assets-2021.1.1.zip and choosing "extract here".
![image](https://user-images.githubusercontent.com/589439/143657912-d33c71f8-1965-4ca2-b06c-3d0790ffd1e4.png)
- Log into the Nucleus Service with the credentials you created.
![image](https://user-images.githubusercontent.com/589439/143163725-d7b1a5ae-2391-4da0-9a70-f58ce063eb38.png)
- Create an Isaac Folder. (Right click localhost)
![image](https://user-images.githubusercontent.com/589439/143164075-7cfacb0b-a2e2-4e29-a63f-85316f585a5e.png)
![image](https://user-images.githubusercontent.com/589439/143164125-851ba73c-0cc8-4555-b5d8-769d54625d8d.png)
![image](https://user-images.githubusercontent.com/589439/143657335-7499d95b-d4e0-44bd-88f9-87f4d73a9de9.png)
- Drag and drop the the files in the isaac-sim-assets-2021.1.1. folder into the Isaac folder in Omniverse. (NOT THE .ZIP; THE FILES IN THE FOLDER THAT WAS CREATED WHEN YOU EXTRACTED IT).
![image](https://user-images.githubusercontent.com/589439/143666284-5ff41514-5c89-4cc7-afa0-b17ed9003b61.png)
- Click upload.
![image](https://user-images.githubusercontent.com/589439/143657451-f9792fd1-e085-4850-a5b5-1ccbe9d4d4e5.png)
![image](https://user-images.githubusercontent.com/589439/143666323-eb172e58-d0cb-4228-af31-f9f7daf43d19.png)
### 6. Now launch Isaac Sim from the Library Omniverse tab within Omniverse.
- Click Launch in the Library Tab of Omniverse.
![image](https://user-images.githubusercontent.com/589439/143657605-6b09b104-698d-4eba-b5f7-e027eee033eb.png)
- Click Start with the default settings with "Issac Sim" selected.
![image](https://user-images.githubusercontent.com/589439/143657653-c3d31131-1da7-4919-b7dd-8a9555c4aba6.png)
- Once Isaac Sim has finished loading, login to localhost with the browser window that opened.
![image](https://user-images.githubusercontent.com/589439/143658289-5d6ed582-e15f-4ca7-b3dd-b7cd1d37a2fb.png)
![image](https://user-images.githubusercontent.com/589439/143658399-7538b399-a050-4468-842f-32cfe782bf80.png)
From here we can launch the Isaac Sim application. Currently there is no way to generate KITTI formated output synthetic data (which is required for Nvidia's transfer learning) from the domain randomizer within the application itself.
For this we need to use Omniverse's built in python environment.
## Python API Installation
1. Using the Linux command line interface (terminal), go to the packages root folder (home/.local/share/ov/pkg/isaac_sim-2021.2.0/).
cd ~/.local/share/ov/pkg/isaac_sim-2021.2.0/
ls
![image](https://user-images.githubusercontent.com/589439/143659975-91da9c57-e9c0-4c41-a208-c02010656a83.png)
2. Run the following command to get all the required dependencies:
./python.sh -m pip install -r requirements.txt
![image](https://user-images.githubusercontent.com/589439/143660049-8e2288b8-14c4-4503-a4d4-56fb45574849.png)
|
pantelis-classes/omniverse-ai/Wikipages/TAO (NVIDIA Train, Adapt, and Optimize).md | All instructions stem from this <a href="https://docs.nvidia.com/tao/tao-toolkit/text/tao_toolkit_quick_start_guide.html">Nvidia Doc</a>.
# Requirements
### Hardware Requirements (Recommended)
32 GB system RAM
32 GB of GPU RAM
8 core CPU
1 NVIDIA GPU
100 GB of SSD space
### Hardware Requirements (REQUIRED)
- TAO Toolkit is supported on **A100**, **V100** and **RTX 30x0 GPUs**.
# Login to the NGC docker registry.
Login to the NGC docker registry:
Use the command
docker login nvcr.io
and enter the following credentials:
a. Username: "$oauthtoken"
b. Password: "YOUR_NGC_API_KEY"
- Where YOUR_NGC_API_KEY corresponds to the key you generated from step 3.
![image](https://user-images.githubusercontent.com/589439/143663405-5323b62f-74a8-409f-80a8-c2c6ad961497.png)
# Installing TAO Toolkit
- TAO Toolkit is a Python pip package that is hosted on the NVIDIA PyIndex. The package uses the docker restAPI under the hood to interact with the NGC Docker registry to pull and instantiate the underlying docker containers. You must have an NGC account and an API key associated with your account. See the Installation Prerequisites section for details on creating an NGC account and obtaining an API key.
## 1. Create a new virtualenv using virtualenvwrapper
- Click this <a href="https://python-guide-cn.readthedocs.io/en/latest/dev/virtualenvs.html"> link</a> to understand how virtual enviroments in python work.
- Make sure you have virtualenv installed by checking it's version. (Instructions are in this <a href="https://github.com/pantelis-classes/omniverse-ai/wiki/NVIDIA-Transfer-Learning-Toolkit-(TLT)-Installation#1-create-new-python-virtual-environment">page</a> of the)
virtualenv --version
![image](https://user-images.githubusercontent.com/589439/143723668-73111ae8-0ac5-4729-b89b-481d29b25d16.png)
## 2. Define the environment variable called VIRTUALENVWRAPPER_PYTHON.
- Run this command to see where your python is located.
which python3
![image](https://user-images.githubusercontent.com/589439/143723824-968874c9-5f8e-44cc-a535-d0d336a72b78.png)
- Define the environment variable of your Python location.
export VIRTUALENVWRAPPER_PYTHON=/usr/bin/python3
![image](https://user-images.githubusercontent.com/589439/143723906-baf552bc-e9d1-435b-8d43-553f6f0a6707.png)
- Run this command to make sure the enviroment variable was created. (There should be red output with the variable name.)
env | grep 'VIRTUALENVWRAPPER_PYTHON'
![image](https://user-images.githubusercontent.com/589439/143723930-c9c8658f-339d-4693-894a-daf70dea28ae.png)
- Run this command.
source `which virtualenvwrapper.sh`
- Run this command to create a virtualenv named "TAO".
mkvirtualenv TAO -p $VIRTUALENVWRAPPER_PYTHON
![image](https://user-images.githubusercontent.com/589439/143724459-afaf363f-dd92-494b-9707-5400f409d05a.png)
- You should now see a (TAO) prepending your username in the CLI.
![image](https://user-images.githubusercontent.com/589439/143724476-77609fc2-e5a7-4773-94d9-799f2b78be6f.png)
## Intructions on how to activate/deactive the vitualenv.
- When you are done with you session, you may deactivate your virtualenv using the deactivate command:
deactivate
![image](https://user-images.githubusercontent.com/589439/143724159-ae6c0578-14e4-463b-8287-ef4147ff0f34.png)
- You may re-instantiate this created virtualenv env using the workon command.
workon TAO
![image](https://user-images.githubusercontent.com/589439/143724492-3036d310-3569-4820-9087-daca2bf9869f.png)
## 3. Download Jupyter Notebook.
- TAO Toolkit provides samples notebooks to walk through and prescrible TAO workflow. These samples are hosted on NGC as a resource and can be downloaded from NGC by executing the command mentioned below.
- Run these commands to set up your notebook.
workon TAO
![image](https://user-images.githubusercontent.com/589439/143725152-cbbd609d-6d94-452c-8a48-a2bcf66dc4ab.png)
- Copy the command belown and keep pressing enter until you are in ~/cv_samples_v1.2.0.
wget --content-disposition https://api.ngc.nvidia.com/v2/resources/nvidia/tao/cv_samples/versions/v1.2.0/zip -O cv_samples_v1.2.0.zip
unzip -u cv_samples_v1.2.0.zip -d ./cv_samples_v1.2.0 && rm -rf cv_samples_v1.2.0.zip && cd ./cv_samples_v1.2.0
![image](https://user-images.githubusercontent.com/589439/143725176-02cc805c-4a98-4afe-9d49-ff17b48e171c.png)
![image](https://user-images.githubusercontent.com/589439/143725173-3c7d7cf0-c3b7-487a-9ed9-818aa5615e84.png)
![image](https://user-images.githubusercontent.com/589439/143725183-3d1caa61-125e-43fe-be67-683429c272ab.png)
## 4. Start Jupyter Notebook
- Once the notebook samples are downloaded, you may start the notebook using the below commands:
jupyter notebook --ip 0.0.0.0 --port 8888 --allow-root
![image](https://user-images.githubusercontent.com/589439/143725216-d67fe159-5f1f-47b1-8dbe-5c14a4e6a7aa.png)
- Open an internet browser on localhost and navigate to the following URL:
http://0.0.0.0:8888
![image](https://user-images.githubusercontent.com/589439/143725228-4696d70e-ec0b-485c-985b-3bffb83be6ac.png)
- Navigate to ./detectnet_v2/detectnet_v2.ipynb
![image](https://user-images.githubusercontent.com/589439/143725266-806cf049-c46f-4e22-9940-ac4e9d952117.png)
![image](https://user-images.githubusercontent.com/589439/143725290-0778740c-3b39-45b4-8d83-a254f545844c.png)
![image](https://user-images.githubusercontent.com/589439/143725306-14110acd-9a61-460a-be5d-df45a55c5b65.png)
|
pantelis-classes/omniverse-ai/Wikipages/_Sidebar.md | # Isaac Sim in Omniverse
* [Home][home]
* [Isaac-Sim-SDK-Omniverse-Installation][Omniverse]
* [Synthetic-Data-Generation][SDG]
* [NVIDIA Transfer Learning Toolkit (TLT) Installation][TLT]
* [NVIDIA TAO][TAO]
* [detectnet_v2 Installation][detectnet_v2]
* [Jupyter Notebook][Jupyter-Notebook]
[home]: https://github.com/pantelis-classes/omniverse-ai/wiki
[Omniverse]: https://github.com/pantelis-classes/omniverse-ai/wiki/Isaac-Sim-SDK-Omniverse-Installation
[SDG]: https://github.com/pantelis-classes/omniverse-ai/wiki/Synthetic-Data-Generation-(Python-API)
[TLT]: https://github.com/pantelis-classes/omniverse-ai/wiki/NVIDIA-Transfer-Learning-Toolkit-(TLT)-Installation
[NTLTSD]: https://github.com/pantelis-classes/omniverse-ai/wiki/Using-NVIDIA-TLT-with-Synthetic-Data
[TAO]: https://github.com/pantelis-classes/omniverse-ai/wiki/TAO-(NVIDIA-Train,-Adapt,-and-Optimize)
[detectnet_v2]: https://github.com/pantelis-classes/omniverse-ai/wiki/detectnet_v2-Installation
[Jupyter-Notebook]: https://github.com/pantelis-classes/omniverse-ai/wiki/Jupyter-Notebook
|
pantelis-classes/omniverse-ai/Wikipages/home.md | # Learning in Simulated Worlds in Omniverse.
## Wiki Navigation
* [Home][home]
* [Isaac-Sim-SDK-Omniverse-Installation][Omniverse]
* [Synthetic-Data-Generation][SDG]
* [NVIDIA Transfer Learning Toolkit (TLT) Installation][TLT]
* [NVIDIA TAO][TAO]
* [detectnet_v2 Installation][detectnet_v2]
* [Jupyter Notebook][Jupyter-Notebook]
[home]: https://github.com/pantelis-classes/omniverse-ai/wiki
[Omniverse]: https://github.com/pantelis-classes/omniverse-ai/wiki/Isaac-Sim-SDK-Omniverse-Installation
[SDG]: https://github.com/pantelis-classes/omniverse-ai/wiki/Synthetic-Data-Generation-(Python-API)
[TLT]: https://github.com/pantelis-classes/omniverse-ai/wiki/NVIDIA-Transfer-Learning-Toolkit-(TLT)-Installation
[NTLTSD]: https://github.com/pantelis-classes/omniverse-ai/wiki/Using-NVIDIA-TLT-with-Synthetic-Data
[TAO]: https://github.com/pantelis-classes/omniverse-ai/wiki/TAO-(NVIDIA-Train,-Adapt,-and-Optimize)
[detectnet_v2]: https://github.com/pantelis-classes/omniverse-ai/wiki/detectnet_v2-Installation
[Jupyter-Notebook]: https://github.com/pantelis-classes/omniverse-ai/wiki/Jupyter-Notebook
<hr />
## Reports
<a href="https://docs.google.com/document/d/1jVXxrNgtOosZw_vAORzomSnmy45G3qK_mmk2B4oJtPg/edit?usp=sharing">Domain Randomization Paper</a><br>
This report provides an indepth understanding on how Domain Randomization helps perception machine learning tasks such as object detection and/or segmentation.
<a href="https://docs.google.com/document/d/1WAzdqlWE0RUns41-0P951mnsqMR7I2XV/edit?usp=sharing&ouid=112712585131518554614&rtpof=true&sd=true">Final Report</a><br>
This final report contains an indepth explanation on the hardware/software used, the methods used to collect the data, an explanation on the data collected, trained and pruned, and the overall conclusions made from the trained and pruned datasets. |
pantelis-classes/omniverse-ai/Wikipages/NVIDIA Transfer Learning Toolkit (TLT) Installation.md | # Installing the Pre-requisites
## 1. Install docker-ce:
### * Set up repository:
Update apt package index and install packages.
sudo apt-get update
![image](https://user-images.githubusercontent.com/589439/143660967-37eb6626-62c0-4afa-af3a-c43a3c172e85.png)
sudo apt-get install \
ca-certificates \
curl \
gnupg \
lsb-release
- The following image has these dependencies already installed.
![image](https://user-images.githubusercontent.com/589439/143660985-4ae4366b-8d28-4514-b1df-bd7fe03e581d.png)
Add Docker's official GPG key:
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg
![image](https://user-images.githubusercontent.com/589439/143661077-2d0ce142-be2f-4ab6-ad99-a685fa709182.png)
### * Install Docker Engine:
Update the apt package index, and install the latest version of Docker Engine.
sudo apt-get update
![image](https://user-images.githubusercontent.com/589439/143661094-a2b86161-c37f-42fd-9110-34523343f65a.png)
sudo apt-get install docker-ce docker-ce-cli containerd.io
![image](https://user-images.githubusercontent.com/589439/143661447-8fa25b3b-1c79-470d-b962-88c21bd56f63.png)
Verify that Docker Engine is installed correctly by running the hello-world image.
sudo docker run hello-world
![image](https://user-images.githubusercontent.com/589439/143661433-d67e18ac-c098-4665-b7ba-127e397b0df6.png)
### * Manage Docker as a non-root user:
Create the docker group.
sudo groupadd docker
![image](https://user-images.githubusercontent.com/589439/143661491-c43c3f94-90d7-47d4-8bd4-dee974f67838.png)
Add your user to the docker group.
sudo usermod -aG docker $USER
![image](https://user-images.githubusercontent.com/589439/143661478-cff5282c-e864-4821-a084-7f1f8360b4bc.png)
Log out and log back in so that your group membership is re-evaluated.
![image](https://user-images.githubusercontent.com/589439/143661541-098c52b5-0c54-46c9-9d14-fd0250f27a1e.png)
Verify that you can run docker commands without sudo.
docker run hello-world
![image](https://user-images.githubusercontent.com/589439/143661708-6baceb75-a047-4f75-8b51-9496e6908d15.png)
- If you get the WARNING error in the above image, run these two commands. Otherwise Skip to #2.
sudo chown "$USER":"$USER" /home/"$USER"/.docker -R
sudo chmod g+rwx "/home/$USER/.docker" -R
- Run docker run hello-world to double check it works now.
docker run hello-world
![image](https://user-images.githubusercontent.com/589439/143661749-52f2103f-19c5-47bb-85b3-0b5069957b87.png)
## 2. Install NVIDIA Container Toolkit:
Setup the stable repository and the GPG key:
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
&& curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
&& curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
![image](https://user-images.githubusercontent.com/589439/143662010-9b31cc9d-bbbe-4aa7-af69-ade75e18ccc6.png)
Install the nvidia-docker2 package (and dependencies) after updating the package listing:
sudo apt-get update
sudo apt-get install -y nvidia-docker2
![image](https://user-images.githubusercontent.com/589439/143662034-8e020c83-780b-40d0-a17b-ad0cdfd4210f.png)
Restart the Docker daemon to complete the installation after setting the default runtime:
sudo systemctl restart docker
![image](https://user-images.githubusercontent.com/589439/143662068-dfcad334-8466-4c9a-9cd0-e08a23f31b66.png)
At this point, a working setup can be tested by running a base CUDA container:
sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi
- This should result in a console output shown below:
![image](https://user-images.githubusercontent.com/589439/143663183-0bdb6ee0-84be-4788-bdc7-0ab23e9e5d41.png)
## 3. Get an NVIDIA NGC account and API key:
- Go to <a href="https://ngc.nvidia.com/signin">NGC</a> and click the Transfer Learning Toolkit container in the Catalog tab. This message is displayed: “Sign in to access the PULL feature of this repository”.
![image](https://user-images.githubusercontent.com/589439/143662546-8e8053f4-9aa9-40bb-bb8c-432d652db64b.png)
- Enter your Email address and click Next, or click Create an Account.
- Choose your organization when prompted for Organization/Team.
- Click Sign In.
- Once redirected to this <a href="https://catalog.ngc.nvidia.com/">page</a> with your account made, click the top right corner to click your profile and click "Setup"
![image](https://user-images.githubusercontent.com/589439/143662652-a6595488-44e6-494e-8e11-17056209a3fd.png)
- Click Get API Key.
![image](https://user-images.githubusercontent.com/589439/143662747-cda7d160-6f1f-41dc-815f-65bf13ba7bc7.png)
- Click Generate API Key.
![image](https://user-images.githubusercontent.com/589439/143662782-9bebeb67-26ec-4980-9624-1a91f0d1a6cc.png)
- Your API key and username will be shown under the DOCKER tm section. Copy the text with your username and API password and save it in a file somewhere.
![image](https://user-images.githubusercontent.com/589439/143663255-907bff87-ae02-4c4d-8400-ef6a914c3aae.png)
![image](https://user-images.githubusercontent.com/589439/143663347-4ec70e43-da4d-4b97-bd26-b336586bc9d7.png)
## 4. Login to the NGC docker registry:
Use the command
docker login nvcr.io
and enter the following credentials:
a. Username: "$oauthtoken"
b. Password: "YOUR_NGC_API_KEY"
- Where YOUR_NGC_API_KEY corresponds to the key you generated from step 3.
![image](https://user-images.githubusercontent.com/589439/143663405-5323b62f-74a8-409f-80a8-c2c6ad961497.png)
# Installing TLT
The Transfer Learning Toolkit (TLT) is a Python pip package that is hosted on the NVIDIA PyIndex. The package uses the docker restAPI under the hood to interact with the NGC Docker registry to pull and instantiate the underlying docker containers.
## 1. Create new Python virtual environment.
### Python virtualenv setup using virtualenvwrapper
Install via pip:
pip3 install virtualenv
![image](https://user-images.githubusercontent.com/589439/143667101-35f5e890-f96d-4a24-8f85-4db1ff95ab8f.png)
pip3 install virtualenvwrapper
![image](https://user-images.githubusercontent.com/589439/143667117-cef7ead6-5ca1-4f93-b759-4caa9c8dca76.png)
|
pantelis-classes/omniverse-ai/Wikipages/_Footer.md | ## Authors
### <a href="https://github.com/dfsanchez999">Diego Sanchez</a> | <a href="https://harp.njit.edu/~jga26/">Jibran Absarulislam</a> | <a href="https://github.com/markkcruz">Mark Cruz</a> | <a href="https://github.com/sppatel2112">Sapan Patel</a>
## Supervisor
### <a href="https://pantelis.github.io/">Dr. Pantelis Monogioudis</a>
## Credits
### <a href="https://developer.nvidia.com/nvidia-omniverse-platform">NVIDIA Omniverse</a> |
pantelis-classes/omniverse-ai/Wikipages/detectnet_v2 Installation.md | # Installing running detectnet_v2 in a jupyter notebook
## Setup File Structures.
- Run these commands to create the correct file structure.
cd ~
mkdir tao
mv cv_samples_v1.2.0/ tao
cd tao/cv_samples_v1.2.0/
rm -r detectnet_v2
![image](https://user-images.githubusercontent.com/589439/143797815-904b6033-f5db-43ac-a736-d653d4d19cfe.png)
![image](https://user-images.githubusercontent.com/589439/143797903-cd33e342-e45d-44ca-a8ac-6efb6d2cd18f.png)
- Download the detectnet_v2.zip from this <a href="https://github.com/pantelis-classes/omniverse-ai/raw/main/detectnet_v2.zip">link</a>.
![image](https://user-images.githubusercontent.com/589439/143727479-6828fc05-4672-4c60-8a21-f1fe6e97d0ea.png)
- Run this command to move the .zip from your downloads folder to your detectnet_v2 folder.
mv ~/Downloads/detectnet_v2.zip ~/tao/cv_samples_v1.2.0/
![image](https://user-images.githubusercontent.com/589439/143798005-a702ed00-5971-4ece-b60a-d05e14fa09b9.png)
- Run this command to unzip the folder.
unzip ~/tao/cv_samples_v1.2.0/detectnet_v2.zip -d detectnet_v2
![image](https://user-images.githubusercontent.com/589439/143798404-ae066e4a-d573-4144-a1ec-b5410db9efb7.png)
![image](https://user-images.githubusercontent.com/589439/143798434-9d14756d-2bdb-4f68-88cb-0e5610562034.png)
- Run this command to copy your dataset to the TAO folder. (You generated this dataset in this <a href="https://github.com/pantelis-classes/omniverse-ai/wiki/Synthetic-Data-Generation-(Python-API)#offline-training-with-tlt">wiki page</a>.)
cp -r ~/.local/share/ov/pkg/isaac_sim-2021.2.0/output/testing/ ~/tao/cv_samples_v1.2.0/detectnet_v2/workspace/tao-experiment/data/
cp -r ~/.local/share/ov/pkg/isaac_sim-2021.2.0/output/training/ ~/tao/cv_samples_v1.2.0/detectnet_v2/workspace/tao-experiment/data/
![image](https://user-images.githubusercontent.com/589439/143798514-be064b8e-18e9-4f21-97b2-ef72820190a8.png)
![image](https://user-images.githubusercontent.com/589439/143798539-d7555c9c-87c3-4037-819a-ee32aca9fa44.png)
- Navigate to Home -> cv_samples_v1.2.0 -> detectnet_v2
- Open the detectnet_v2.ipynb file.
![image](https://user-images.githubusercontent.com/589439/143729232-16e479b2-527e-4b0f-94b0-e43bd08cfba8.png)
- Scroll down to section "0. Set up env variables and map drives" (Ctrl + F)
![image](https://user-images.githubusercontent.com/589439/143729413-dffdd2dc-d0cb-40aa-8b0f-fd567b2a527c.png)
- Replace "diego" with your username. (TIP: whoami in BASH)
![image](https://user-images.githubusercontent.com/589439/143729441-e43fde75-76ed-489d-acef-56fea5ddf539.png)
![image](https://user-images.githubusercontent.com/589439/143729521-c7b0fc38-baf0-4701-9032-dba324497f5e.png) |
pantelis-classes/omniverse-ai/Wikipages/Jupyter Notebook.md | # Object Detection using TAO DetectNet_v2
- Transfer learning is the process of transferring learned features from one application to another. It is a commonly used training technique where you use a model trained on one task and re-train to use it on a different task.
- Train Adapt Optimize (TAO) Toolkit is a simple and easy-to-use Python based AI toolkit for taking purpose-built AI models and customizing them with users' own data.
## How to use the notebook.
- Please refer to the actual jupyter notebook to have more in-depth explanations of the code.
- Each Cell will run some lines of code. Start from the top of the notebook and run each cell by click the play button or using **shift + enter**.
![image](https://user-images.githubusercontent.com/589439/143809035-2ae69802-7929-47a6-a445-12b571cacd14.png)
- Some of the cells may take a long time to complete. Please do not skip cells and wait for the output to finish.
## 0. Set up env variables and map drives
![image](https://user-images.githubusercontent.com/589439/143808844-e4244060-5842-41e2-868d-7a75c57a3c21.png)
![image](https://user-images.githubusercontent.com/589439/143809423-cea91ff5-916f-4c03-b7c3-e4eb625756a4.png)
- We set up the env variables by linking paths, setting number of GPUs, and choosing an encoding style.
## 1. Install the TAO launcher
- This step should have been already completed in the previous wiki pages. Please refer to this <a href="https://github.com/pantelis-classes/omniverse-ai/wiki/TAO-(NVIDIA-Train,-Adapt,-and-Optimize)#login-to-the-ngc-docker-registry">link</a>.
![image](https://user-images.githubusercontent.com/589439/143809877-6e766d73-ff1c-405f-bd6f-600a58736b25.png)
## 2. Prepare dataset and pre-trained model
![image](https://user-images.githubusercontent.com/589439/143809929-1e119a3b-0239-4144-bece-a1d9aa7d51bf.png)
![image](https://user-images.githubusercontent.com/589439/143809965-7997fd22-e172-4360-af13-8c0d65b83f4e.png)
![image](https://user-images.githubusercontent.com/589439/143809992-3a41471a-dd02-4a3e-acea-96b7a7c3a674.png)
![image](https://user-images.githubusercontent.com/589439/143810068-5f175928-4e4d-4820-8b14-067a31b35cd6.png)
![image](https://user-images.githubusercontent.com/589439/143810077-6bfb77d3-4643-4129-a8c4-0b4fbf196b43.png)
![image](https://user-images.githubusercontent.com/589439/143810093-f8508bb1-5728-4010-b87b-21f4aed74e73.png)
![image](https://user-images.githubusercontent.com/589439/143810115-c88787cb-3cae-433a-93c8-712a25db0c78.png)
## 3. Provide training specification
![image](https://user-images.githubusercontent.com/589439/143810872-231209ca-eb71-4bd2-930d-3527fbaaace0.png)
## 4. Run TAO training
![image](https://user-images.githubusercontent.com/589439/143810896-a9875ab8-b9ab-4ced-ad49-c47ea321a052.png)
## 5. Evaluate the trained model
![image](https://user-images.githubusercontent.com/589439/143811275-488e15be-15bd-4341-8392-834cd68bbcad.png)
## 6. Prune the trained model
![image](https://user-images.githubusercontent.com/589439/143810915-c9428405-1f00-462d-8a80-2d1467c95e7b.png)
## 7. Retrain the pruned model
![image](https://user-images.githubusercontent.com/589439/143810942-972f34b4-b7a4-4532-9e8d-6f6bcc01ac9f.png)
![image](https://user-images.githubusercontent.com/589439/143810970-69367200-b71e-481f-b813-3d447e154bb3.png)
## 8. Evaluate the retrained model
![image](https://user-images.githubusercontent.com/589439/143811255-0b946589-2679-4747-b514-3b91ac2259cd.png)
## 9. Visualize inferences
![image](https://user-images.githubusercontent.com/589439/143811032-4adc40ef-fa0e-4596-88b5-2a24610cdaf3.png)
![image](https://user-images.githubusercontent.com/589439/143811081-edaa58f5-d3e6-40c6-9dab-f19e547d090e.png) |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/CODE_OF_CONDUCT.md | ## Code of Conduct
This project has adopted the [Amazon Open Source Code of Conduct](https://aws.github.io/code-of-conduct).
For more information see the [Code of Conduct FAQ](https://aws.github.io/code-of-conduct-faq) or contact
[email protected] with any additional questions or comments.
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/package.json | {
"name": "omni-app",
"version": "0.1.0",
"bin": {
"omni-app": "bin/omni-app.js"
},
"scripts": {
"build": "tsc",
"watch": "tsc -w",
"test": "jest",
"cdk": "cdk"
},
"devDependencies": {
"@types/jest": "^26.0.10",
"@types/node": "10.17.27",
"aws-cdk": "2.20.0",
"jest": "^26.4.2",
"ts-jest": "^26.2.0",
"ts-node": "^9.0.0",
"typescript": "~3.9.7"
},
"dependencies": {
"@aws-cdk/aws-lambda-python-alpha": "2.88.0-alpha.0",
"aws-cdk-lib": "2.88.0",
"cdk-nag": "^2.14.13",
"constructs": "^10.0.0",
"dotenv": "^16.0.3",
"envalid": "^7.2.1",
"source-map-support": "^0.5.16"
}
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/package-lock.json | {
"name": "omni-app",
"version": "0.1.0",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "omni-app",
"version": "0.1.0",
"dependencies": {
"@aws-cdk/aws-lambda-python-alpha": "2.88.0-alpha.0",
"aws-cdk-lib": "2.88.0",
"cdk-nag": "^2.14.13",
"constructs": "^10.0.0",
"dotenv": "^16.0.3",
"envalid": "^7.2.1",
"source-map-support": "^0.5.16"
},
"bin": {
"omni-app": "bin/omni-app.js"
},
"devDependencies": {
"@types/jest": "^26.0.10",
"@types/node": "10.17.27",
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|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/CONTRIBUTING.md | # Contributing Guidelines
Thank you for your interest in contributing to our project. Whether it's a bug report, new feature, correction, or additional
documentation, we greatly value feedback and contributions from our community.
Please read through this document before submitting any issues or pull requests to ensure we have all the necessary
information to effectively respond to your bug report or contribution.
## Reporting Bugs/Feature Requests
We welcome you to use the GitHub issue tracker to report bugs or suggest features.
When filing an issue, please check existing open, or recently closed, issues to make sure somebody else hasn't already
reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:
* A reproducible test case or series of steps
* The version of our code being used
* Any modifications you've made relevant to the bug
* Anything unusual about your environment or deployment
## Contributing via Pull Requests
Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that:
1. You are working against the latest source on the *main* branch.
2. You check existing open, and recently merged, pull requests to make sure someone else hasn't addressed the problem already.
3. You open an issue to discuss any significant work - we would hate for your time to be wasted.
To send us a pull request, please:
1. Fork the repository.
2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change.
3. Ensure local tests pass.
4. Commit to your fork using clear commit messages.
5. Send us a pull request, answering any default questions in the pull request interface.
6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation.
GitHub provides additional document on [forking a repository](https://help.github.com/articles/fork-a-repo/) and
[creating a pull request](https://help.github.com/articles/creating-a-pull-request/).
## Finding contributions to work on
Looking at the existing issues is a great way to find something to contribute on. As our projects, by default, use the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any 'help wanted' issues is a great place to start.
## Code of Conduct
This project has adopted the [Amazon Open Source Code of Conduct](https://aws.github.io/code-of-conduct).
For more information see the [Code of Conduct FAQ](https://aws.github.io/code-of-conduct-faq) or contact
[email protected] with any additional questions or comments.
## Security issue notifications
If you discover a potential security issue in this project we ask that you notify AWS/Amazon Security via our [vulnerability reporting page](http://aws.amazon.com/security/vulnerability-reporting/). Please do **not** create a public github issue.
## Licensing
See the [LICENSE](LICENSE) file for our project's licensing. We will ask you to confirm the licensing of your contribution.
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/cdk.json | {
"app": "npx ts-node --prefer-ts-exts bin/omni-app.ts",
"watch": {
"include": [
"**"
],
"exclude": [
"README.md",
"cdk*.json",
"**/*.d.ts",
"**/*.js",
"tsconfig.json",
"package*.json",
"yarn.lock",
"node_modules",
"test"
]
},
"context": {
"@aws-cdk/aws-apigateway:usagePlanKeyOrderInsensitiveId": true,
"@aws-cdk/core:stackRelativeExports": true,
"@aws-cdk/aws-rds:lowercaseDbIdentifier": true,
"@aws-cdk/aws-lambda:recognizeVersionProps": true,
"@aws-cdk/aws-cloudfront:defaultSecurityPolicyTLSv1.2_2021": true,
"@aws-cdk-containers/ecs-service-extensions:enableDefaultLogDriver": true,
"@aws-cdk/aws-ec2:uniqueImdsv2TemplateName": true,
"@aws-cdk/core:target-partitions": [
"aws",
"aws-cn"
]
}
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/jest.config.js | /*
Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
Licensed under the Amazon Software License http://aws.amazon.com/asl/
*/
module.exports = {
testEnvironment: 'node',
roots: ['<rootDir>/test'],
testMatch: ['**/*.test.ts'],
transform: {
'^.+\\.tsx?$': 'ts-jest'
}
};
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/deploy.sh | #!/bin/bash -e
# Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
printf "BUILDING STACK...\n"
ACCOUNT_ID=$(aws sts get-caller-identity | grep -Eo '"Account"[^,]*' | grep -Eo '[^:]*$')
if [ -z "$ACCOUNT_ID" ]; then
printf "\n[ERROR] Failed to get AWS Account ID. Verify your shell is configured with AWS and try again."
exit 1
fi
printf "\nUsing AWS Account: %s\n" "$ACCOUNT_ID"
if test -f ".env"; then
printf "\nSourcing environment from '.env'.\n"
printf "%s\n" "$(cat .env)"
else
printf "\n[WARNING] No .env found. Creating default .env file.\n"
DEFAULT_STACK_NAME="omni-app"
DEFAULT_REGION="us-west-2"
touch .env
echo "export APP_STACK_NAME=${DEFAULT_STACK_NAME}" >> .env
echo "export AWS_DEFAULT_REGION=${DEFAULT_REGION}" >> .env
fi
source .env
if [[ -z "${APP_STACK_NAME}" ]]; then
printf "\n[ERROR] Missing Required ENV variable APP_STACK_NAME"
exit 1
fi
printf "\nDEPLOYING STACK...\n"
cdk bootstrap && \
cdk synth && \
cdk deploy --require-approval never
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/README.md | # NVIDIA Omniverse Nucleus on Amazon EC2
NVIDIA Omniverse is a scalable, multi-GPU, real-time platform for building and operating metaverse applications, based on Pixar's Universal Scene Description (USD) and NVIDIA RTX technology. USD is a powerful, extensible 3D framework and ecosystem that enables 3D designers and developers to connect and collaborate between industry-leading 3D content creation, rendering, and simulation applications. Omniverse helps individual creators to connect and enhance their 3D artistic process, and enterprises to build and simulate large scale virtual worlds for industrial applications.
With Omniverse, everyone involved in the lifecycle of 3D data has access to high-quality visualizations, authoring, and review tools. Teams do not need additional overhead to manage complex 3D data pipelines. Instead, they can focus on their unique contributions to bring value to the market. Non-technical stakeholders do not need to subject themselves to applications with steep learning curves, nor do results need to be compromised for the sake of iteration reviews.
To support distributed Omniverse users, Nucleus should be deployed in a secure environment. With on-demand compute, storage, and networking resources, AWS infrastructure is well suited to all spatial computing workloads, including Omniverse Nucleus. This repository provides the steps and infrastructure for an Omniverse Enterprise Nucleus Server deployment on Amazon EC2.
## Contents
* [Prerequisites](#prerequisites)
* [Deployment](#deployment)
* [Architecture](#architecture)
* [Troubleshooting](#troubleshooting)
* [Getting Help](#getting-help)
* [Changelog](#changelog)
* [Security](#security)
* [License](#license)
* [References](#references)
## Prerequisites
- AWS CLI - https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html
- AWS CDK - https://docs.aws.amazon.com/cdk/v2/guide/getting_started.html#getting_started_install
- Docker - https://www.docker.com/products/docker-desktop/
- Python 3.9 or greater - https://www.python.org
- Access to NVIDIA Enterprise Omniverse Nucleus packages - https://docs.omniverse.nvidia.com/prod_nucleus/prod_nucleus/enterprise/installation/quick_start_tips.html
- A Route53 Public Hosted Zone - https://docs.aws.amazon.com/Route53/latest/DeveloperGuide/CreatingHostedZone.html
**To learn more, reference the official documentation from NVIDIA:** https://docs.omniverse.nvidia.com/prod_nucleus/prod_nucleus/enterprise/cloud_aws_ec2.html
## Architecture
![architecture](/diagrams/architecture.png)
## Deployment
### 1. Download Nucleus Deployment Artifacts from NVIDIA
Place them in `./src/tools/nucleusServer/stack`
For example: `./src/tools/nucleusServer/stack/nucleus-stack-2022.1.0+tag-2022.1.0.gitlab.3983146.613004ac.tar.gz`
Consult NVIDIA documentation to find the appropriate packages.
> Note This deployment has a templated copy of `nucleus-stack.env` located at `./src/tools/nucleusServer/templates/nucleus-stack.env` this may need to be updated if NVIDIA makes changes to the `nucleus-stack.env` file packaged with their archive.
>
> The same applies to NVIDIA's reverse proxy `nginx.conf` located at `./src/tools/reverseProxy/templates/nginx.conf`
### 2. configure .env file
create ./.env
Set the following variables
```
export APP_STACK_NAME=omni-app
export AWS_DEFAULT_REGION=us-west-2
# STACK INPUTS
export OMNIVERSE_ARTIFACTS_BUCKETNAME=example-bucket-name
export ROOT_DOMAIN=example-domain.com
export NUCLEUS_SERVER_PREFIX=nucleus
export NUCLEUS_BUILD=nucleus-stack-2022.1.0+tag-2022.1.0.gitlab.3983146.613004ac # from Step 1
export ALLOWED_CIDR_RANGE_01=cidr-range-with-public-access
export DEV_MODE=true
```
> NOTE: This deployment assumes you have a public hosted zone in Route53 for the ROOT_DOMAIN, this deployment will add a CNAME record to that hosted zone
### 3. Run the deployment
The following script will run cdk deploy. The calling process must be authenticated with sufficient permissions to deploy AWS resources.
```
chmod +x ./deploy.sh
./deploy.sh
```
> NOTE: deployment requires a running docker session for building Python Lambda functions
> NOTE: It can take a few minutes for the instances to get up and running. After the deployment script finishes, review your EC2 instances and check that they are in a running state.
### 4. Test the connection
Test a connection to `<NUCLEUS_SERVER_PREFIX>.<ROOT_DOMAIN>` from within the ALLOWED_CIDR_RANGE set in the `.env` file. Do so by browsing to `https://<NUCLUES_SERVER_PREFIX>.<ROOT_DOMAIN>` in your web browser.
The default admin username for the Nucleus server is 'omniverse'. You can find the password in a Secrets Manager resource via the AWS Secrets Manager Console. Alternatively, from the Omniverse WebUI, you can create a new username and password.
## Troubleshooting
### Unable to connect to the Nucleus Server
If you are not able to connect to to the Nucleus server, review the status of the Nginx service, and the Nucleus docker stack. To do so, connect to your instances from the EC2 Console via Session Manager - https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/session-manager.html.
- On the Nginx Server, run `sudo journalctl -u nginx.service`, if this is produces no output the Nginx service is not running.
- On the Nucleus server, run `sudo docker ps`, you should see a list of Nucleus containers up.
If there are issues with either of these, it is likely there was an issue with the Lambda and/or SSM run commands that configure the instances. Browse to the Lambda Console (https://us-west-2.console.aws.amazon.com/lambda/home?region=us-west-2#/functions) and search for the respective Lambda Functions:
- STACK_NAME-ReverseProxyConfig-CustomResource
- STACK_NAME-NucleusServerConfig-CustomResource
Review the function CloudWatch Logs.
### No service log entries, or unable to restart nitro-enclave service
If there are issues with either of these, it is likely there was an issue with the Lambda and/or SSM run commands that configure the instances. Browse to the Lambda Console and search for the `STACK_NAME-ReverseProxyConfig-CustomResource` Lambda Function, then review the CloudWatch Logs.
At times the Reverse Proxy custom resource Lambda function does not trigger on a initial stack deployment. If the reverse proxy instance is in a running state, but there are now invocations/logs, terminate the instance and give the auto scaling group a few minutes to create another one, and then try again. Afterwards, check the CloudWatch Logs for the Lambda function: `ReverseProxyAutoScalingLifecycleLambdaFunction`
### Additional Nginx Commands
View Nitro Enclaves Service Logs:
`sudo journalctl -u nginx.service`
Viewing Nginx Logs
`sudo cat /var/log/nginx/error.log`
`sudo cat /var/log/nginx/access.log`
Restart Nginx
`systemctl restart nginx.service`
### Additional Nucleus server notes
Review NVIDIA's Documentation - https://docs.omniverse.nvidia.com/prod_nucleus/prod_nucleus/enterprise/installation/quick_start_tips.html
default base stack and config location: `/opt/ove/`
default omniverse data dir: `/var/lib/omni/nucleus-data`
Interacting with the Nucleus Server docker compose stack:
`sudo docker-compose --env-file ./nucleus-stack.env -f ./nucleus-stack-ssl.yml pull`
`sudo docker-compose --env-file ./nucleus-stack.env -f ./nucleus-stack-ssl.yml up -d`
`sudo docker-compose --env-file ./nucleus-stack.env -f ./nucleus-stack-ssl.yml down`
`sudo docker-compose --env-file ./nucleus-stack.env -f ./nucleus-stack-ssl.yml ps`
Generate new secrets
`sudo rm -fr secrets && sudo ./generate-sample-insecure-secrets.sh`
## Getting Help
If you have questions as you explore this sample project, post them to the Issues section of this repository. To report bugs, request new features, or contribute to this open source project, see [CONTRIBUTING.md](./CONTRIBUTING.md).
## Changelog
To view the history and recent changes to this repository, see [CHANGELOG.md](./CHANGELOG.md)
## Security
See [CONTRIBUTING](./CONTRIBUTING.md) for more information.
## License
This sample code is licensed under the MIT-0 License. See the [LICENSE](./LICENSE) file.
## References
### NVIDIA Omniverse
[Learn more about the NVIDIA Omniverse Platform](https://www.nvidia.com/en-us/omniverse/)
### Omniverse Nucleus
[Learn more about the NVIDIA Omniverse Nucleus](https://docs.omniverse.nvidia.com/prod_nucleus/prod_nucleus/overview.html)
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/tsconfig.json | {
"compilerOptions": {
"target": "ES2018",
"module": "commonjs",
"lib": [
"es2018"
],
"declaration": true,
"strict": true,
"noImplicitAny": true,
"strictNullChecks": true,
"noImplicitThis": true,
"alwaysStrict": true,
"noUnusedLocals": false,
"noUnusedParameters": false,
"noImplicitReturns": true,
"noFallthroughCasesInSwitch": false,
"inlineSourceMap": true,
"inlineSources": true,
"experimentalDecorators": true,
"strictPropertyInitialization": false,
"typeRoots": [
"./node_modules/@types"
]
},
"exclude": [
"node_modules",
"cdk.out"
]
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/test/omni-app.test.ts | // import * as cdk from 'aws-cdk-lib';
// import { Template } from 'aws-cdk-lib/assertions';
// import * as OmniApp from '../lib/omni-app-stack';
// example test. To run these tests, uncomment this file along with the
// example resource in lib/omni-app-stack.ts
test('SQS Queue Created', () => {
// const app = new cdk.App();
// // WHEN
// const stack = new OmniApp.OmniAppStack(app, 'MyTestStack');
// // THEN
// const template = Template.fromStack(stack);
// template.hasResourceProperties('AWS::SQS::Queue', {
// VisibilityTimeout: 300
// });
});
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/nucleusServer/setup.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
from setuptools import setup
with open("README.md", "r") as fh:
long_description = fh.read()
setup(
name="Nucleus Server Tools",
version="1.0",
py_modules=[
'nst'
],
install_requires=[
"boto3",
"python-dotenv",
"Click"
],
entry_points='''
[console_scripts]
nst=nst_cli:main
'''
)
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/nucleusServer/nst_cli.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
# Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
"""
helper tools for omniverse nucleus deployment configuration
"""
# std lib modules
import os
import logging
from pathlib import Path
# 3rd party modules
import click
import nst.logger as logger
pass_config = click.make_pass_decorator(object, ensure=True)
@click.group()
@pass_config
def main(config):
pass
@main.command()
@pass_config
@click.option("--my_opt_arg")
def hello_world(config, my_opt_arg):
logger.info(f"Hello World: {my_opt_arg=}")
@main.command()
@pass_config
@click.option("--server-ip", required=True)
@click.option("--reverse-proxy-domain", required=True)
@click.option("--instance-name", required=True)
@click.option("--master-password", required=True)
@click.option("--service-password", required=True)
@click.option("--data-root", required=True)
def generate_nucleus_stack_env(
config,
server_ip,
reverse_proxy_domain,
instance_name,
master_password,
service_password,
data_root,
):
logger.info(
f"generate_nucleus_stack_env:{server_ip=},{reverse_proxy_domain=},{instance_name=},{master_password=},{service_password=},{data_root=}"
)
tools_path = "/".join(list(Path(__file__).parts[:-1]))
cur_dir_path = "."
template_name = "nucleus-stack.env"
template_path = f"{tools_path}/templates/{template_name}"
output_path = f"{cur_dir_path}/{template_name}"
if not Path(template_path).is_file():
raise Exception("File not found: {template_path}")
data = ""
with open(template_path, "r") as file:
data = file.read()
data = data.format(
SERVER_IP_OR_HOST=server_ip,
REVERSE_PROXY_DOMAIN=reverse_proxy_domain,
INSTANCE_NAME=instance_name,
MASTER_PASSWORD=master_password,
SERVICE_PASSWORD=service_password,
DATA_ROOT=data_root,
ACCEPT_EULA="1",
SECURITY_REVIEWED="1",
)
with open(f"{output_path}", "w") as file:
file.write(data)
logger.info(output_path)
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/nucleusServer/requirements.txt | -e . |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/nucleusServer/README.md | # Tools for configuring Nuclues Server
The contents of this directory are zipped and then deployed to the nuclues server |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/nucleusServer/nst/__init__.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/nucleusServer/nst/logger.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
import os
import logging
LOG_LEVEL = os.getenv('LOG_LEVEL', 'DEBUG')
logger = logging.getLogger()
logger.setLevel(LOG_LEVEL)
def info(*args):
print(*args)
def debug(*args):
print(*args)
def warning(*args):
print(*args)
def error(*args):
print(*args) |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/reverseProxy/rpt_cli.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
"""
helper tools for reverse proxy nginx configuration
"""
# std lib modules
import os
import logging
from pathlib import Path
# 3rd party modules
import click
import rpt.logger as logger
pass_config = click.make_pass_decorator(object, ensure=True)
@click.group()
@pass_config
def main(config):
pass
@main.command()
@pass_config
def hello_world(config):
logger.info(f'Hello World')
@main.command()
@pass_config
@click.option("--cert-arn", required=True)
def generate_acm_yaml(config, cert_arn):
logger.info(f'generate_acm_yaml: {cert_arn=}')
tools_path = '/'.join(list(Path(__file__).parts[:-1]))
cur_dir_path = '.'
template_path = f'{tools_path}/templates/acm.yaml'
output_path = f'{cur_dir_path}/acm.yaml'
logger.info(Path(template_path).is_file())
data = ''
with open(template_path, 'r') as file:
data = file.read()
data = data.format(cert_arn=cert_arn)
with open(f'{output_path}', 'w') as file:
file.write(data)
logger.info(output_path)
@main.command()
@pass_config
@click.option("--domain", required=True)
@click.option("--server-address", required=True)
def generate_nginx_config(config, domain, server_address):
logger.info(f'generate_nginx_config: {domain=}')
nginx_template_path = os.path.join(
os.getcwd(), 'templates', 'nginx.conf')
if Path(nginx_template_path).is_file():
logger.info(f"NGINX template found at: {nginx_template_path}")
else:
raise Exception(
f"ERROR: No NGINX template found at: {nginx_template_path}")
output_path = f'/etc/nginx/nginx.conf'
if Path(output_path).is_file():
logger.info(f"NGINX default configuration found at: {output_path}")
else:
raise Exception(
f"ERROR: No NGINX default configuration found at: {output_path}. Verify NGINX installation.")
data = ''
with open(nginx_template_path, 'r') as file:
data = file.read()
data = data.format(PUBLIC_DOMAIN=domain,
NUCLEUS_SERVER_DOMAIN=server_address)
with open(output_path, 'w') as file:
file.write(data)
logger.info(output_path)
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/reverseProxy/setup.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
from setuptools import setup
with open("README.md", "r") as fh:
long_description = fh.read()
setup(
name="Reverse Proxy Tools",
version="1.0",
py_modules=["rpt"],
install_requires=["boto3", "python-dotenv", "Click"],
entry_points="""
[console_scripts]
rpt=rpt_cli:main
""",
)
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/reverseProxy/requirements.txt | -e . |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/reverseProxy/README.md | # Tools for configuring Nginx Reverse Proxy
The contents of this directory are zipped and then deployed to the reverse proxy server |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/reverseProxy/rpt/__init__.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/reverseProxy/rpt/logger.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
import os
import logging
LOG_LEVEL = os.getenv('LOG_LEVEL', 'DEBUG')
logger = logging.getLogger()
logger.setLevel(LOG_LEVEL)
def info(*args):
print(*args)
def debug(*args):
print(*args)
def warning(*args):
print(*args)
def error(*args):
print(*args) |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/tools/reverseProxy/templates/acm.yaml | # Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
---
# ACM for Nitro Enclaves config.
#
# This is an example of setting up ACM, with Nitro Enclaves and nginx.
# You can take this file and then:
# - copy it to /etc/nitro_enclaves/acm.yaml;
# - fill in your ACM certificate ARN in the `certificate_arn` field below;
# - make sure /etc/nginx/nginx.conf is set up to:
# - use the pkcs11 SSL engine, and;
# - include the stanza file configured below (under `NginxStanza`)
# somewhere in the nginx.conf `server` section;
# - start the nitro-enclaves-acm service.
#
# Enclave general configuration
enclave:
# Number of vCPUs to be assigned to the enclave
cpu_count: 2
# Memory (in MiB) to be assigned to the enclave
memory_mib: 256
tokens:
# A label for this PKCS#11 token
- label: nginx-acm-token
# Configure a managed token, sourced from an ACM certificate.
source:
Acm:
# The certificate ARN
# Note: this certificate must have been associated with the
# IAM role assigned to the instance on which ACM for
# Nitro Enclaves is run.
certificate_arn: "{cert_arn}"
target:
NginxStanza:
# Path to the nginx stanza to be written by the ACM service whenever
# the certificate configuration changes (e.g. after a certificate renewal).
# This file must be included from the main nginx config `server` section,
# as it will contain the TLS nginx configuration directives.
path: /etc/pki/nginx/nginx-acm.conf
# Stanza file owner (i.e. the user nginx is configured to run as).
user: nginx
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/customResources/reverseProxyConfig/index.py | import os
import logging
import json
from crhelper import CfnResource
import aws_utils.ssm as ssm
import aws_utils.ec2 as ec2
import config.reverseProxy as config
LOG_LEVEL = os.getenv("LOG_LEVEL", "DEBUG")
logger = logging.getLogger()
logger.setLevel(LOG_LEVEL)
helper = CfnResource(
json_logging=False, log_level="DEBUG", boto_level="CRITICAL"
)
@helper.create
def create(event, context):
logger.info("Create Event: %s", json.dumps(event, indent=2))
response = update_config(
event["ResourceProperties"]["STACK_NAME"],
event["ResourceProperties"]["ARTIFACTS_BUCKET_NAME"],
event["ResourceProperties"]["FULL_DOMAIN"],
event["ResourceProperties"]["RP_AUTOSCALING_GROUP_NAME"],
)
logger.info("Run Command Results: %s", json.dumps(response, indent=2))
@helper.update
def update(event, context):
logger.info("Update Event: %s", json.dumps(event, indent=2))
response = update_config(
event["ResourceProperties"]["STACK_NAME"],
event["ResourceProperties"]["ARTIFACTS_BUCKET_NAME"],
event["ResourceProperties"]["FULL_DOMAIN"],
event["ResourceProperties"]["RP_AUTOSCALING_GROUP_NAME"],
)
logger.info("Run Command Results: %s", json.dumps(response, indent=2))
def update_config(
stack_name,
artifacts_bucket_name,
full_domain,
rp_autoscaling_group_name
):
# get nucleus main instance id
nucleus_instances = []
try:
nucleus_instances = ec2.get_instances_by_tag(
"Name", f"{stack_name}/NucleusServer")
except Exception as e:
raise Exception(
f"Failed to get nucleus instances by name. {e}")
logger.info(f"Nucleus Instances: {nucleus_instances}")
# get nucleus main hostname
nucleus_hostname = ec2.get_instance_private_dns_name(nucleus_instances[0])
logger.info(f"Nucleus Hostname: {nucleus_hostname}")
# generate config for reverse proxy servers
commands = []
try:
commands = config.get_config(
artifacts_bucket_name, nucleus_hostname, full_domain)
logger.debug(commands)
except Exception as e:
raise Exception(f"Failed to get Reverse Proxy config. {e}")
# get reverse proxy instance ids
rp_instances = ec2.get_autoscaling_instance(rp_autoscaling_group_name)
if rp_instances is None:
return None
logger.info(rp_instances)
# run config commands
response = []
for i in rp_instances:
r = ssm.run_commands(
i, commands, document="AWS-RunShellScript"
)
response.append(r)
return response
@helper.delete
def delete(event, context):
logger.info("Delete Event: %s", json.dumps(event, indent=2))
def handler(event, context):
helper(event, context)
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/customResources/reverseProxyConfig/requirements.txt | crhelper |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/customResources/nucleusServerConfig/index.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
import os
import logging
import json
from crhelper import CfnResource
import aws_utils.ssm as ssm
import aws_utils.sm as sm
import config.nucleus as config
LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO")
logger = logging.getLogger()
logger.setLevel(LOG_LEVEL)
helper = CfnResource(json_logging=False, log_level="DEBUG",
boto_level="CRITICAL")
@helper.create
def create(event, context):
logger.info("Create Event: %s", json.dumps(event, indent=2))
instanceId = event["ResourceProperties"]["instanceId"]
reverseProxyDomain = event["ResourceProperties"]["reverseProxyDomain"]
artifactsBucket = event["ResourceProperties"]["artifactsBucket"]
nucleusBuild = event["ResourceProperties"]["nucleusBuild"]
ovMainLoginSecretArn = event["ResourceProperties"]["ovMainLoginSecretArn"]
ovServiceLoginSecretArn = event["ResourceProperties"]["ovServiceLoginSecretArn"]
response = update_nucleus_config(
instanceId,
artifactsBucket,
reverseProxyDomain,
nucleusBuild,
ovMainLoginSecretArn,
ovServiceLoginSecretArn,
)
logger.info("Run Command Results: %s", json.dumps(response, indent=2))
@helper.update
def update(event, context):
logger.info("Update Event: %s", json.dumps(event, indent=2))
instanceId = event["ResourceProperties"]["instanceId"]
reverseProxyDomain = event["ResourceProperties"]["reverseProxyDomain"]
artifactsBucket = event["ResourceProperties"]["artifactsBucket"]
nucleusBuild = event["ResourceProperties"]["nucleusBuild"]
ovMainLoginSecretArn = event["ResourceProperties"]["ovMainLoginSecretArn"]
ovServiceLoginSecretArn = event["ResourceProperties"]["ovServiceLoginSecretArn"]
response = update_nucleus_config(
instanceId,
artifactsBucket,
reverseProxyDomain,
nucleusBuild,
ovMainLoginSecretArn,
ovServiceLoginSecretArn,
)
logger.info("Run Command Results: %s", json.dumps(response, indent=2))
def update_nucleus_config(
instanceId,
artifactsBucket,
reverseProxyDomain,
nucleusBuild,
ovMainLoginSecretArn,
ovServiceLoginSecretArn,
):
ovMainLoginSecret = sm.get_secret(ovMainLoginSecretArn)
ovServiceLoginSecret = sm.get_secret(ovServiceLoginSecretArn)
ovMainLoginPassword = ovMainLoginSecret["password"]
ovServiceLoginPassword = ovServiceLoginSecret["password"]
# generate config for reverse proxy servers
commands = []
try:
commands = config.get_config(
artifactsBucket, reverseProxyDomain, nucleusBuild, ovMainLoginPassword, ovServiceLoginPassword)
logger.debug(commands)
except Exception as e:
raise Exception("Failed to get Reverse Proxy config. {}".format(e))
for p in commands:
print(p)
response = ssm.run_commands(
instanceId, commands, document="AWS-RunShellScript")
return response
@helper.delete
def delete(event, context):
logger.info("Delete Event: %s", json.dumps(event, indent=2))
def handler(event, context):
helper(event, context)
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/customResources/nucleusServerConfig/requirements.txt | crhelper |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/asgLifeCycleHooks/reverseProxy/index.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
import boto3
import os
import json
import logging
import traceback
from botocore.exceptions import ClientError
import aws_utils.ssm as ssm
import aws_utils.r53 as r53
import aws_utils.ec2 as ec2
import config.reverseProxy as config
logger = logging.getLogger()
logger.setLevel(logging.INFO)
autoscaling = boto3.client("autoscaling")
ARTIFACTS_BUCKET = os.environ["ARTIFACTS_BUCKET"]
NUCLEUS_ROOT_DOMAIN = os.environ["NUCLEUS_ROOT_DOMAIN"]
NUCLEUS_DOMAIN_PREFIX = os.environ["NUCLEUS_DOMAIN_PREFIX"]
NUCLEUS_SERVER_ADDRESS = os.environ["NUCLEUS_SERVER_ADDRESS"]
def send_lifecycle_action(event, result):
try:
response = autoscaling.complete_lifecycle_action(
LifecycleHookName=event["detail"]["LifecycleHookName"],
AutoScalingGroupName=event["detail"]["AutoScalingGroupName"],
LifecycleActionToken=event["detail"]["LifecycleActionToken"],
LifecycleActionResult=result,
InstanceId=event["detail"]["EC2InstanceId"],
)
logger.info(response)
except ClientError as e:
message = "Error completing lifecycle action: {}".format(e)
logger.error(message)
raise Exception(message)
return
def update_nginix_config(
instanceId, artifactsBucket, nucleusServerAddress, domain
):
# generate config for reverse proxy servers
commands = []
try:
commands = config.get_config(
artifactsBucket, nucleusServerAddress, domain)
logger.debug(commands)
except Exception as e:
raise Exception("Failed to get Reverse Proxy config. {}".format(e))
response = ssm.run_commands(
instanceId, commands, document="AWS-RunShellScript"
)
return response
def handler(event, context):
logger.info("Event: %s", json.dumps(event, indent=2))
instanceId = event["detail"]["EC2InstanceId"]
transition = event["detail"]["LifecycleTransition"]
if transition == "autoscaling:EC2_INSTANCE_LAUNCHING":
try:
update_nginix_config(
instanceId,
ARTIFACTS_BUCKET,
NUCLEUS_SERVER_ADDRESS,
f"{NUCLEUS_DOMAIN_PREFIX}.{NUCLEUS_ROOT_DOMAIN}",
)
send_lifecycle_action(event, "CONTINUE")
except Exception as e:
message = "Error running command: {}".format(e)
logger.warning(traceback.format_exc())
logger.error(message)
send_lifecycle_action(event, "ABANDON")
elif transition == "autoscaling:EC2_INSTANCE_TERMINATING":
try:
send_lifecycle_action(event, "CONTINUE")
except Exception as e:
message = "Error running command: {}".format(e)
logger.warning(traceback.format_exc())
logger.error(message)
send_lifecycle_action(event, "ABANDON")
logger.info("Execution Complete")
return
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/common/requirements.txt | |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/common/aws_utils/ec2.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
import os
import logging
import boto3
from botocore.exceptions import ClientError
LOG_LEVEL = os.getenv("LOG_LEVEL", "DEBUG")
logger = logging.getLogger()
logger.setLevel(LOG_LEVEL)
client = boto3.client("ec2")
ec2_resource = boto3.resource("ec2")
autoscaling = boto3.client("autoscaling")
def get_instance_public_dns_name(instanceId):
instance = get_instance_description(instanceId)
if instance is None:
return None
return instance["PublicDnsName"]
def get_instance_private_dns_name(instanceId):
instance = get_instance_description(instanceId)
if instance is None:
return None
return instance["PrivateDnsName"]
def get_instance_description(instanceId):
response = client.describe_instances(
InstanceIds=[instanceId],
)
instances = response["Reservations"][0]["Instances"]
if not instances:
return None
return instances[0]
def get_instance_status(instanceId):
response = client.describe_instance_status(
Filters=[
{
"Name": "string",
"Values": [
"string",
],
},
],
InstanceIds=[
"string",
],
MaxResults=123,
NextToken="string",
DryRun=True | False,
IncludeAllInstances=True | False,
)
statuses = response["InstanceStatuses"][0]
status = {"instanceStatus": None, "systemStatus": None}
if statuses:
status = {
"instanceStatus": statuses["InstanceStatus"]["Status"],
"systemStatus": statuses["SystemStatus"]["Status"],
}
return status
def get_autoscaling_instance(groupName):
response = autoscaling.describe_auto_scaling_groups(
AutoScalingGroupNames=[groupName]
)
logger.debug(response)
instances = response['AutoScalingGroups'][0]["Instances"]
if not instances:
return None
instanceIds = []
for i in instances:
instanceIds.append(i["InstanceId"])
return instanceIds
def update_tag_value(resourceIds: list, tagKey: str, tagValue: str):
client.create_tags(
Resources=resourceIds,
Tags=[{
'Key': tagKey,
'Value': tagValue
}],
)
def delete_tag(resourceIds: list, tagKey: str, tagValue: str):
response = client.delete_tags(
Resources=resourceIds,
Tags=[{
'Key': tagKey,
'Value': tagValue
}],
)
return response
def get_instance_state(id):
instance = ec2_resource.Instance(id)
return instance.state['Name']
def get_instances_by_tag(tagKey, tagValue):
instances = ec2_resource.instances.filter(
Filters=[{'Name': 'tag:{}'.format(tagKey), 'Values': [tagValue]}])
if not instances:
return None
instanceIds = []
for i in instances:
instanceIds.append(i.id)
return instanceIds
def get_instances_by_name(name):
instances = get_instances_by_tag("Name", name)
if not instances:
logger.error(f"ERROR: Failed to get instances by tag: Name, {name}")
return None
return instances
def get_active_instance(instances):
for i in instances:
instance_state = get_instance_state(i)
logger.info(f"Instance: {i}. State: {instance_state}")
if instance_state == "running" or instance_state == "pending":
return i
logger.warn(f"Instances are not active")
return None
def get_volumes_by_instance_id(id):
instance = ec2_resource.Instance(id)
volumes = instance.volumes.all()
volumeIds = []
for i in volumes:
volumeIds.append(i.id)
return volumeIds
def terminate_instances(instance_ids):
response = client.terminate_instances(InstanceIds=instance_ids)
logger.info(response)
return response
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/common/aws_utils/ssm.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
import os
import time
import logging
import boto3
from botocore.exceptions import ClientError
LOG_LEVEL = os.getenv("LOG_LEVEL", "DEBUG")
logger = logging.getLogger()
logger.setLevel(LOG_LEVEL)
client = boto3.client("ssm")
def get_param_value(name) -> str:
response = client.get_parameter(Name=name)
logger.info(response)
return response['Parameter']['Value']
def update_param_value(name, value) -> bool:
response = client.put_parameter(Name=name, Value=value, Overwrite=True)
logger.info(response)
try:
return (response['Version'] > 0)
except ClientError as e:
message = "Error calling SendCommand: {}".format(e)
logger.error(message)
return False
def run_commands(
instance_id, commands, document="AWS-RunPowerShellScript", comment="aws_utils.ssm.run_commands"
):
"""alt document options:
AWS-RunShellScript
"""
# Run Commands
logger.info("Calling SendCommand: {} for instance: {}".format(
commands, instance_id))
attempt = 0
response = None
while attempt < 20:
attempt = attempt + 1
try:
time.sleep(10 * attempt)
logger.info("SendCommand, attempt #: {}".format(attempt))
response = client.send_command(
InstanceIds=[instance_id],
DocumentName=document,
Parameters={"commands": commands},
Comment=comment,
CloudWatchOutputConfig={
"CloudWatchLogGroupName": instance_id,
"CloudWatchOutputEnabled": True,
},
)
logger.info(response)
if "Command" in response:
break
if attempt == 10:
message = "Command did not execute successfully in time allowed."
raise Exception(message)
except ClientError as e:
message = "Error calling SendCommand: {}".format(e)
logger.error(message)
continue
if not response:
message = "Command did not execute successfully in time allowed."
raise Exception(message)
# Check Command Status
command_id = response["Command"]["CommandId"]
logger.info(
"Calling GetCommandInvocation for command: {} for instance: {}".format(
command_id, instance_id
)
)
attempt = 0
result = None
while attempt < 10:
attempt = attempt + 1
try:
time.sleep(10 * attempt)
logger.info("GetCommandInvocation, attempt #: {}".format(attempt))
result = client.get_command_invocation(
CommandId=command_id,
InstanceId=instance_id,
)
if result["Status"] == "InProgress":
logger.info("Command is running.")
continue
elif result["Status"] == "Success":
logger.info("Command Output: {}".format(
result["StandardOutputContent"]))
if result["StandardErrorContent"]:
message = "Command returned STDERR: {}".format(
result["StandardErrorContent"])
logger.warning(message)
break
elif result["Status"] == "Failed":
message = "Error Running Command: {}".format(
result["StandardErrorContent"])
logger.error(message)
raise Exception(message)
else:
message = "Command has an unhandled status, will continue: {}".format(
e)
logger.warning(message)
continue
except client.exceptions.InvocationDoesNotExist as e:
message = "Error calling GetCommandInvocation: {}".format(e)
logger.error(message)
raise Exception(message)
if not result or result["Status"] != "Success":
message = "Command did not execute successfully in time allowed."
raise Exception(message)
return result
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/common/aws_utils/r53.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
import boto3
client = boto3.client("route53")
def update_hosted_zone_cname_record(hostedZoneID, rootDomain, domainPrefix, serverAddress):
fqdn = f"{domainPrefix}.{rootDomain}"
response = client.change_resource_record_sets(
HostedZoneId=hostedZoneID,
ChangeBatch={
"Comment": "Updating {fqdn}->{serverAddress} CNAME record",
"Changes": [
{
"Action": "UPSERT",
"ResourceRecordSet": {
"Name": fqdn,
"Type": "CNAME",
"TTL": 300,
"ResourceRecords": [{"Value": serverAddress}],
},
}
],
},
)
return response
def delete_hosted_zone_cname_record(hostedZoneID, rootDomain, domainPrefix, serverAddress):
response = client.change_resource_record_sets(
HostedZoneId=hostedZoneID,
ChangeBatch={
"Comment": "string",
"Changes": [
{
"Action": "DELETE",
"ResourceRecordSet": {
"Name": f"{domainPrefix}.{rootDomain}",
"Type": "CNAME",
"ResourceRecords": [{"Value": serverAddress}],
},
}
],
},
)
# botocore.errorfactory.InvalidInput: An error occurred (InvalidInput) when calling the ChangeResourceRecordSets operation: Invalid request:
# Expected exactly one of [AliasTarget, all of [TTL, and ResourceRecords], or TrafficPolicyInstanceId], but found none in Change with
# [Action=DELETE, Name=nucleus-dev.awsps.myinstance.com, Type=CNAME, SetIdentifier=null]
return response
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/common/aws_utils/__init__.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/common/aws_utils/sm.py | # Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-.amazon.com.-AmznSL-1.0
# Licensed under the Amazon Software License http://aws.amazon.com/asl/
import json
import boto3
SM = boto3.client("secretsmanager")
def get_secret(secret_name):
response = SM.get_secret_value(SecretId=secret_name)
secret = json.loads(response["SecretString"])
return secret
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/common/config/nucleus.py |
def start_nucleus_config() -> list[str]:
return '''
cd /opt/ove/base_stack || exit 1
echo "STARTING NUCLEUS STACK ----------------------------------"
docker-compose --env-file nucleus-stack.env -f nucleus-stack-ssl.yml start
'''.splitlines()
def stop_nucleus_config() -> list[str]:
return '''
cd /opt/ove/base_stack || exit 1
echo "STOPPING NUCLEUS STACK ----------------------------------"
docker-compose --env-file nucleus-stack.env -f nucleus-stack-ssl.yml stop
'''.splitlines()
def restart_nucleus_config() -> list[str]:
return '''
cd /opt/ove/base_stack || exit 1
echo "RESTARTING NUCLEUS STACK ----------------------------------"
docker-compose --env-file nucleus-stack.env -f nucleus-stack-ssl.yml restart
'''.splitlines()
def get_config(artifacts_bucket_name: str, full_domain: str, nucleus_build: str, ov_main_password: str, ov_service_password: str) -> list[str]:
return f'''
echo "------------------------ NUCLEUS SERVER CONFIG ------------------------"
echo "UPDATING AND INSTALLING DEPS ----------------------------------"
sudo apt-get update -y -q && sudo apt-get upgrade -y
sudo apt-get install dialog apt-utils -y
echo "INSTALLING AWS CLI ----------------------------------"
sudo curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
sudo apt-get install unzip
sudo unzip awscliv2.zip
sudo ./aws/install
sudo rm awscliv2.zip
sudo rm -fr ./aws/install
echo "INSTALLING PYTHON ----------------------------------"
sudo apt-get -y install python3.9
sudo curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
sudo python3.9 get-pip.py
sudo pip3 install --upgrade pip
sudo pip3 --version
echo "INSTALLING DOCKER ----------------------------------"
sudo apt-get remove docker docker-engine docker.io containerd runc
sudo apt-get -y install apt-transport-https ca-certificates curl gnupg-agent software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
sudo apt-get -y update
sudo apt-get -y install docker-ce docker-ce-cli containerd.io
sudo systemctl enable --now docker
echo "INSTALLING DOCKER COMPOSE ----------------------------------"
sudo curl -L "https://github.com/docker/compose/releases/download/1.29.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose
echo "INSTALLING NUCLEUS TOOLS ----------------------------------"
sudo mkdir -p /opt/ove
cd /opt/ove || exit 1
aws s3 cp --recursive s3://{artifacts_bucket_name}/tools/nucleusServer/ ./nucleusServer
cd nucleusServer || exit 1
sudo pip3 install -r requirements.txt
echo "UNPACKAGING NUCLEUS STACK ----------------------------------"
sudo tar xzvf stack/{nucleus_build}.tar.gz -C /opt/ove --strip-components=1
cd /opt/ove/base_stack || exit 1
omniverse_data_path=/var/lib/omni/nucleus-data
nucleusHost=$(curl -s http://169.254.169.254/latest/meta-data/hostname)
sudo nst generate-nucleus-stack-env --server-ip $nucleusHost --reverse-proxy-domain {full_domain} --instance-name nucleus_server --master-password {ov_main_password} --service-password {ov_service_password} --data-root $omniverse_data_path
chmod +x ./generate-sample-insecure-secrets.sh
./generate-sample-insecure-secrets.sh
echo "PULLING NUCLEUS IMAGES ----------------------------------"
docker-compose --env-file nucleus-stack.env -f nucleus-stack-ssl.yml pull
echo "STARTING NUCLEUS STACK ----------------------------------"
docker-compose --env-file nucleus-stack.env -f nucleus-stack-ssl.yml up -d
docker-compose --env-file nucleus-stack.env -f nucleus-stack-ssl.yml ps -a
'''.splitlines()
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/src/lambda/common/config/reverseProxy.py | def get_config(artifacts_bucket_name: str, nucleus_address: str, full_domain: str) -> list[str]:
return f'''
echo "------------------------ REVERSE PROXY CONFIG ------------------------"
echo "UPDATING PACKAGES ----------------------------------"
sudo yum update -y
echo "INSTALLING DEPENDENCIES ----------------------------------"
sudo yum install -y aws-cfn-bootstrap gcc openssl-devel bzip2-devel libffi-devel zlib-devel
echo "INSTALLING NGINX ----------------------------------"
sudo yum install -y amazon-linux-extras
sudo amazon-linux-extras enable nginx1
sudo yum install -y nginx
sudo nginx -v
echo "INSTALLING PYTHON ----------------------------------"
sudo wget https://www.python.org/ftp/python/3.9.9/Python-3.9.9.tgz -P /opt/python3.9
cd /opt/python3.9 || exit 1
sudo tar xzf Python-3.9.9.tgz
cd Python-3.9.9 || exit 1
sudo ./configure --prefix=/usr --enable-optimizations
sudo make install
echo "------------------------ REVERSE PROXY CONFIG ------------------------"
echo "INSTALLING REVERSE PROXY TOOLS ----------------------------------"
cd /opt || exit 1
sudo aws s3 cp --recursive s3://{artifacts_bucket_name}/tools/reverseProxy/ ./reverseProxy
cd reverseProxy || exit 1
pip3 --version
sudo pip3 install -r requirements.txt
sudo rpt generate-nginx-config --domain {full_domain} --server-address {nucleus_address}
echo "STARTING NGINX ----------------------------------"
sudo service nginx restart
'''.splitlines()
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/bin/omni-app.ts | #!/usr/bin/env node
import 'source-map-support/register';
import * as cdk from 'aws-cdk-lib';
import { AppStack } from '../lib/omni-app-stack';
import { NagSuppressions } from 'cdk-nag';
import { cleanEnv, makeValidator, str, bool, host } from 'envalid';
import { regions } from '../lib/utils/regions';
import * as dotenv from 'dotenv';
dotenv.config();
const stackname = makeValidator((x) => {
if (/^[A-Za-z][A-Za-z-0-9]{0,126}[A-Za-z0-9]$/.test(x)) return x;
else
throw new Error(
`Invalid Stack name: ${x}. Can contain only alphanumeric characters (case-sensitive) and hyphens. It must start with an alphabetic character and can't be longer than 128 characters.`
);
});
const bucketname = makeValidator((x) => {
if (/(?!(^xn--|-s3alias$))^[a-z0-9][a-z0-9-]{1,61}[a-z0-9]$/.test(x)) return x;
else
throw new Error(
`Invalid Bucket name: ${x}. Can contain only lowercase alphanumeric characters and hyphens. It must start with an alphabetic character and must be between 3 and 63 characters characters.`
);
});
const domainprefix = makeValidator((x) => {
if (/^[A-Za-z][A-Za-z-0-9]{0,126}[A-Za-z0-9]$/.test(x)) return x;
else
throw new Error(
`Invalid Domain Prefix: ${x}. Can contain only alphanumeric characters (case-sensitive) and hyphens. It must start with an alphabetic character and can't be longer than 128 characters.`
);
});
const cidrrange = makeValidator((x) => {
if (/^([0-9]{1,3}\.){3}[0-9]{1,3}(\/([0-9]|[1-2][0-9]|3[0-2]))?$/.test(x)) return x;
else throw new Error(`Invalid CIDR Range: ${x}`);
});
const env = cleanEnv(process.env, {
APP_STACK_NAME: stackname({ default: 'omni-app' }),
DEV_MODE: bool({ default: false }),
AWS_DEFAULT_REGION: str({ choices: regions }),
OMNIVERSE_ARTIFACTS_BUCKETNAME: bucketname(),
ROOT_DOMAIN: host(),
NUCLEUS_SERVER_PREFIX: domainprefix(),
NUCLEUS_BUILD: str({ default: 'nucleus-stack-2022.1.0+tag-2022.1.0.gitlab.3983146.613004ac' }),
ALLOWED_CIDR_RANGE_01: cidrrange(),
ALLOWED_CIDR_RANGE_02: cidrrange({ default: '' }),
ALLOWED_CIDR_RANGE_03: cidrrange({ default: '' })
});
// console.log(env);
let stackName = env.APP_STACK_NAME;
if (env.DEV_MODE) {
stackName += "-dev";
}
const app = new cdk.App();
const stack = new AppStack(app, stackName, {
/* If you don't specify 'env', this stack will be environment-agnostic.
* Account/Region-dependent features and context lookups will not work,
* but a single synthesized template can be deployed anywhere. */
/* Uncomment the next line to specialize this stack for the AWS Account
* and Region that are implied by the current CLI configuration. */
env: { account: process.env.CDK_DEFAULT_ACCOUNT, region: process.env.CDK_DEFAULT_REGION }
/* Uncomment the next line if you know exactly what Account and Region you
* want to deploy the stack to. */
// env: { account: '123456789012', region: 'us-east-1' },
/* For more information, see https://docs.aws.amazon.com/cdk/latest/guide/environments.html */
});
// Uncomment for security review
// cdk.Aspects.of(app).add(new AwsSolutionsChecks({ verbose: true }));
NagSuppressions.addStackSuppressions(stack, [
{
id: 'AwsSolutions-IAM4',
reason: 'Auto-generated resource with managed policy',
appliesTo: ['Policy::arn:<AWS::Partition>:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole']
},
{
id: 'AwsSolutions-IAM4',
reason: 'Internal Config rule requires AmazonSSMManagedInstanceCore be added to instances',
appliesTo: ['Policy::arn:<AWS::Partition>:iam::aws:policy/AmazonSSMManagedInstanceCore']
}
]);
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/lib/omni-app-stack.ts | import { Stack, StackProps } from 'aws-cdk-lib';
import { Construct } from 'constructs';
import { RevProxyResources } from './constructs/reverseProxy';
import { NucleusServerResources } from './constructs/nucleusServer';
import { VpcResources } from './constructs/vpc';
import { RemovalPolicy } from 'aws-cdk-lib';
import { NagSuppressions } from 'cdk-nag';
import { cleanEnv, str, bool } from 'envalid';
import * as lambda from 'aws-cdk-lib/aws-lambda';
import * as pyLambda from '@aws-cdk/aws-lambda-python-alpha';
import * as dotenv from 'dotenv';
import { StorageResources } from './constructs/storageResources';
import { LoadBalancerConstruct } from './constructs/loadBalancer';
import { Route53Resources } from './constructs/route53';
dotenv.config();
const env = cleanEnv(process.env, {
DEV_MODE: bool({ default: false }),
OMNIVERSE_ARTIFACTS_BUCKETNAME: str({ default: '' }),
ROOT_DOMAIN: str({ default: '' }),
NUCLEUS_SERVER_PREFIX: str({ default: '' })
});
export class AppStack extends Stack {
constructor(scope: Construct, id: string, props?: StackProps) {
super(scope, id, props);
const stackName: string = Stack.of(this).stackName;
const region: string = Stack.of(this).region;
var removalPolicy = RemovalPolicy.RETAIN;
var autoDelete = false;
if (env.DEV_MODE == true) {
removalPolicy = RemovalPolicy.DESTROY;
autoDelete = true;
}
const { artifactsBucket } = new StorageResources(this, "StorageResources", {
bucketName: env.OMNIVERSE_ARTIFACTS_BUCKETNAME,
autoDelete: autoDelete,
removalPolicy: removalPolicy
});
const { certificate, hostedZone } = new Route53Resources(this, 'Route53Resources', {
rootDomain: env.ROOT_DOMAIN,
});
const commonUtilsLambdaLayer = new pyLambda.PythonLayerVersion(this, 'CommonUtilsLayer', {
entry: 'src/lambda/common',
compatibleRuntimes: [lambda.Runtime.PYTHON_3_9],
description: 'Data Model Schema Layer',
layerVersionName: 'common_utils_layer',
});
const vpcResources = new VpcResources(this, 'VpcResources', {
removalPolicy: removalPolicy,
});
const nucleusServerResources = new NucleusServerResources(this, 'NucleusServerResources', {
removalPolicy: removalPolicy,
vpc: vpcResources.vpc,
subnets: vpcResources.subnets.nucleus,
artifactsBucket: artifactsBucket,
nucleusServerSG: vpcResources.securityGroups.nucleus,
lambdaLayers: [commonUtilsLambdaLayer],
});
const reverseProxyResources = new RevProxyResources(this, 'RevProxyResources', {
removalPolicy: removalPolicy,
artifactsBucket: artifactsBucket,
vpc: vpcResources.vpc,
subnets: vpcResources.subnets.reverseProxy,
securityGroup: vpcResources.securityGroups.reverseProxy,
lambdaLayers: [commonUtilsLambdaLayer],
nucleusServerInstance: nucleusServerResources.nucleusServerInstance,
});
reverseProxyResources.node.addDependency(nucleusServerResources);
new LoadBalancerConstruct(this, 'LoadBalancerConstruct', {
removalPolicy: removalPolicy,
autoDelete: autoDelete,
vpc: vpcResources.vpc,
subnets: vpcResources.subnets.loadBalancer,
securityGroup: vpcResources.securityGroups.loadBalancer,
domainPrefix: env.NUCLEUS_SERVER_PREFIX,
rootDomain: env.ROOT_DOMAIN,
certificate: certificate,
hostedZone: hostedZone,
autoScalingGroup: reverseProxyResources.autoScalingGroup,
});
// -------------------------------
// NagSuppressions
// -------------------------------
for (let i = 0; i < this.node.children.length; i++) {
const child = this.node.children[i];
if (child.constructor.name === 'LogRetentionFunction') {
NagSuppressions.addResourceSuppressionsByPath(
this,
`/${stackName}/${child.node.id}/ServiceRole/DefaultPolicy/Resource`,
[{ id: 'AwsSolutions-IAM5', reason: 'Auto-generated resource with wildcard policy' }]
);
}
}
}
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/lib/constructs/storageResources.ts |
import { Fn, Stack } from 'aws-cdk-lib';
import { Construct } from 'constructs';
import { RemovalPolicy, CfnOutput } from 'aws-cdk-lib';
import * as s3 from 'aws-cdk-lib/aws-s3';
import * as deployment from 'aws-cdk-lib/aws-s3-deployment';
import * as path from 'path';
export interface StorageResourcesProps {
removalPolicy: RemovalPolicy,
autoDelete: boolean;
bucketName?: string;
};
export class StorageResources extends Construct {
public readonly artifactsBucket: s3.Bucket;
constructor(scope: Construct, id: string, props: StorageResourcesProps) {
super(scope, id);
const bucketName = props.bucketName ?? `${Stack.of(this).stackName}-omniverse-nucleus-artifacts-bucket`;
const sourceBucket = new s3.Bucket(this, 'ArtifactsBucket', {
bucketName: bucketName,
autoDeleteObjects: props.autoDelete,
removalPolicy: props.removalPolicy,
});
const artifactsDeployment = new deployment.BucketDeployment(this, "ArtifactsDeployment", {
sources: [deployment.Source.asset(path.join(__dirname, "..", "..", "src", "tools"))],
destinationBucket: sourceBucket,
destinationKeyPrefix: "tools",
extract: true,
exclude: ["*.DS_Store"]
});
this.artifactsBucket = artifactsDeployment.deployedBucket as s3.Bucket;
/**
* CFN Outputs
*/
new CfnOutput(this, "ArtifactsBucketName", {
value: this.artifactsBucket.bucketName,
}).overrideLogicalId("ArtifactsBucketName");
new CfnOutput(this, "DeployedObjectKeys", {
value: Fn.select(0, artifactsDeployment.objectKeys)
});
}
} |
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/lib/constructs/reverseProxy.ts | import { Construct } from 'constructs';
import { Stack, RemovalPolicy, Tags } from 'aws-cdk-lib';
import { NagSuppressions } from 'cdk-nag';
import { CustomResource } from './common/customResource';
import { cleanEnv, str } from 'envalid';
import { AutoScalingResources } from './autoscaling';
import * as iam from 'aws-cdk-lib/aws-iam';
import * as s3 from 'aws-cdk-lib/aws-s3';
import * as ec2 from 'aws-cdk-lib/aws-ec2';
import * as pyLambda from '@aws-cdk/aws-lambda-python-alpha';
import * as dotenv from 'dotenv';
import * as asg from 'aws-cdk-lib/aws-autoscaling';
dotenv.config();
const env = cleanEnv(process.env, {
ROOT_DOMAIN: str({ default: '' }),
NUCLEUS_SERVER_PREFIX: str({ default: 'nucleus' }),
});
export type ConstructProps = {
removalPolicy: RemovalPolicy;
artifactsBucket: s3.IBucket;
vpc: ec2.Vpc;
subnets: ec2.ISubnet[];
securityGroup: ec2.SecurityGroup;
lambdaLayers: pyLambda.PythonLayerVersion[];
nucleusServerInstance: ec2.Instance;
};
export class RevProxyResources extends Construct {
public readonly autoScalingGroup: asg.AutoScalingGroup;
constructor(scope: Construct, id: string, props: ConstructProps) {
super(scope, id);
const region: string = Stack.of(this).region;
const account: string = Stack.of(this).account;
const stackName: string = Stack.of(this).stackName;
const instanceRole = new iam.Role(this, 'ReverseProxyInstanceRole', {
assumedBy: new iam.ServicePrincipal('ec2.amazonaws.com'),
description: 'EC2 Instance Role',
managedPolicies: [iam.ManagedPolicy.fromAwsManagedPolicyName('AmazonSSMManagedInstanceCore')],
inlinePolicies: {
reverseProxyInstancePolicy: new iam.PolicyDocument({
statements: [
new iam.PolicyStatement({
resources: [
`${props.artifactsBucket.bucketArn}`,
`${props.artifactsBucket.bucketArn}/*`,
],
actions: ['s3:ListBucket', 's3:GetObject'],
}),
new iam.PolicyStatement({
actions: [
'logs:CreateLogGroup',
'logs:CreateLogStream',
'logs:DescribeLogStreams',
'logs:PutLogEvents',
],
resources: [`arn:aws:logs:${region}:${account}:log-group:/aws/ssm/*`],
}),
],
}),
}
});
const ebsVolume: ec2.BlockDevice = {
deviceName: '/dev/xvda',
volume: ec2.BlockDeviceVolume.ebs(8, {
encrypted: true,
}),
};
// --------------------------------------------------------------------
// AUTO SCALING RESOURCES
// --------------------------------------------------------------------
const launchTemplate = new ec2.LaunchTemplate(this, 'launchTemplate', {
launchTemplateName: 'NginxReverseProxy',
instanceType: new ec2.InstanceType('t3.medium'),
machineImage: ec2.MachineImage.latestAmazonLinux({
generation: ec2.AmazonLinuxGeneration.AMAZON_LINUX_2
}),
blockDevices: [ebsVolume],
role: instanceRole,
securityGroup: props.securityGroup,
detailedMonitoring: true,
userData: ec2.UserData.forLinux()
});
Tags.of(launchTemplate).add('Name', `${stackName}/ReverseProxyServer`);
const reverseProxyConfigPolicy = new iam.PolicyDocument({
statements: [
new iam.PolicyStatement({
actions: ['ssm:GetCommandInvocation'],
resources: [`arn:aws:ssm:${region}:${account}:*`],
}),
new iam.PolicyStatement({
actions: ['ssm:SendCommand'],
resources: [`arn:aws:ssm:*:*:document/*`, `arn:aws:ec2:${region}:${account}:instance/*`],
}),
new iam.PolicyStatement({
actions: ['ssm:GetParameters', 'ssm:GetParameter', 'ssm:GetParametersByPath'],
resources: [`arn:aws:ssm:${region}:${account}:parameter/*`],
}),
new iam.PolicyStatement({
actions: ['ec2:DescribeTags', 'ec2:CreateTags', 'ec2:DeleteTags'],
resources: ['*'],
}),
new iam.PolicyStatement({
actions: ['ec2:DescribeInstances', 'ec2:DescribeInstanceStatus'],
resources: ['*'],
}),
],
});
const autoScalingResources = new AutoScalingResources(
this,
'ReverseProxyAutoScalingResources',
{
name: 'ReverseProxy',
removalPolicy: props.removalPolicy,
artifactsBucket: props.artifactsBucket,
vpcResources: {
vpc: props.vpc,
subnets: props.subnets,
},
launchTemplate: launchTemplate,
capacity: {
min: 1,
max: 1,
},
lambdaResources: {
entry: './src/lambda/asgLifeCycleHooks/reverseProxy',
layers: props.lambdaLayers,
environment: {
ARTIFACTS_BUCKET: props.artifactsBucket.bucketName,
NUCLEUS_ROOT_DOMAIN: env.ROOT_DOMAIN,
NUCLEUS_DOMAIN_PREFIX: env.NUCLEUS_SERVER_PREFIX,
NUCLEUS_SERVER_ADDRESS: props.nucleusServerInstance.instancePrivateDnsName,
},
policies: {
reverseProxyConfigPolicy: reverseProxyConfigPolicy,
},
},
}
);
autoScalingResources.autoScalingGroup.scaleOnCpuUtilization('ReverseProxyScalingPolicy', {
targetUtilizationPercent: 75,
});
this.autoScalingGroup = autoScalingResources.autoScalingGroup;
// --------------------------------------------------------------------
// CUSTOM RESOURCE - Reverse Proxy Configuration
// --------------------------------------------------------------------
const reverseProxyConfigLambdaPolicy = new iam.PolicyDocument({
statements: [
new iam.PolicyStatement({
actions: ['ssm:SendCommand'],
resources: [`arn:aws:ec2:${region}:${account}:instance/*`],
}),
new iam.PolicyStatement({
actions: ['ssm:SendCommand'],
resources: ['arn:aws:ssm:*:*:document/*'],
}),
new iam.PolicyStatement({
actions: ['ssm:GetCommandInvocation'],
resources: [`arn:aws:ssm:${region}:${account}:*`],
}),
new iam.PolicyStatement({
actions: ['ssm:GetParameters', 'ssm:GetParameter', 'ssm:GetParametersByPath'],
resources: [`arn:aws:ssm:${region}:${account}:parameter/*`],
}),
new iam.PolicyStatement({
actions: ['ec2:DescribeInstances'],
resources: ['*'],
}),
new iam.PolicyStatement({
actions: ['autoscaling:DescribeAutoScalingGroups'],
resources: ['*'],
}),
new iam.PolicyStatement({
actions: ['ec2:DescribeTags', 'ec2:CreateTags'],
resources: ['*'],
}),
],
});
const reverseProxyConfig = new CustomResource(this, 'ReverseProxyCustomResource', {
lambdaName: 'ReverseProxyConfig',
lambdaCodePath: './src/lambda/customResources/reverseProxyConfig',
lambdaPolicyDocument: reverseProxyConfigLambdaPolicy,
lambdaLayers: props.lambdaLayers,
removalPolicy: props.removalPolicy,
resourceProps: {
nounce: 2,
STACK_NAME: stackName,
ARTIFACTS_BUCKET_NAME: props.artifactsBucket.bucketName,
FULL_DOMAIN: `${env.NUCLEUS_SERVER_PREFIX}.${env.ROOT_DOMAIN}`,
RP_AUTOSCALING_GROUP_NAME: autoScalingResources.autoScalingGroup.autoScalingGroupName,
},
});
reverseProxyConfig.node.addDependency(this.autoScalingGroup);
// ------------------------------------
// CDK_NAG suppressions
// ------------------------------------
NagSuppressions.addResourceSuppressions(
instanceRole,
[
{
id: 'AwsSolutions-IAM5',
reason:
'Wildcard Permissions: Unable to know which objects exist ahead of time. Need to use wildcard',
},
{
id: 'AwsSolutions-IAM4',
reason:
'Suppress AwsSolutions-IAM4 for AWS Managed Policies policy/AmazonSSMManagedInstanceCore',
},
],
true
);
}
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/lib/constructs/loadBalancer.ts | import { Construct } from 'constructs';
import { Duration, RemovalPolicy } from 'aws-cdk-lib';
import { ISubnet, SecurityGroup, Vpc } from 'aws-cdk-lib/aws-ec2';
import { Certificate } from 'aws-cdk-lib/aws-certificatemanager';
import { ARecord, IHostedZone, RecordTarget } from 'aws-cdk-lib/aws-route53';
import { LoadBalancerTarget } from 'aws-cdk-lib/aws-route53-targets';
import { AutoScalingGroup } from 'aws-cdk-lib/aws-autoscaling';
import * as elb from 'aws-cdk-lib/aws-elasticloadbalancingv2';
import * as s3 from 'aws-cdk-lib/aws-s3';
export interface LoadBalancerProps {
removalPolicy: RemovalPolicy;
autoDelete: boolean;
vpc: Vpc;
subnets: ISubnet[];
securityGroup: SecurityGroup;
domainPrefix: string;
rootDomain: string;
certificate: Certificate;
hostedZone: IHostedZone;
autoScalingGroup: AutoScalingGroup;
}
export class LoadBalancerConstruct extends Construct {
public readonly loadBalancer: elb.ApplicationLoadBalancer;
/**
* Creates a cross-account role allowing the AWS Prototyping Team
* to access customer accounts by assuming the role.
* @param scope the construct scope.
* @param id the identifier given the construct.np
* @param props the construct configuration.
*/
constructor(scope: Construct, id: string, props: LoadBalancerProps) {
super(scope, id);
// create new Application Load Balancer
this.loadBalancer = new elb.ApplicationLoadBalancer(this, 'LoadBalancer', {
vpc: props.vpc,
vpcSubnets: { subnets: props.subnets },
securityGroup: props.securityGroup,
internetFacing: true,
http2Enabled: true,
});
// removal policy -- change in config
this.loadBalancer.applyRemovalPolicy(props.removalPolicy ?? RemovalPolicy.DESTROY);
// access logs for load balancer
this.loadBalancer.logAccessLogs(
new s3.Bucket(this, 'LoadBalancerAccessLogsBucket', {
encryption: s3.BucketEncryption.S3_MANAGED,
removalPolicy: props.removalPolicy,
autoDeleteObjects: props.autoDelete,
enforceSSL: true,
publicReadAccess: false,
blockPublicAccess: s3.BlockPublicAccess.BLOCK_ALL,
serverAccessLogsPrefix: 'bucket-logs',
}),
'loadBalancer-logs'
);
// add ALB as target for Route 53 Hosted Zone
new ARecord(this, 'LoadBalancerAliasRecord', {
zone: props.hostedZone,
recordName: `${props.domainPrefix}.${props.rootDomain}`,
ttl: Duration.seconds(300),
target: RecordTarget.fromAlias(new LoadBalancerTarget(this.loadBalancer)),
});
// --------------------------------------------------------------------
// Target Groups
// --------------------------------------------------------------------
const targetGroup = new elb.ApplicationTargetGroup(this, 'TargetGroup', {
protocol: elb.ApplicationProtocol.HTTP,
protocolVersion: elb.ApplicationProtocolVersion.HTTP1,
targetType: elb.TargetType.INSTANCE,
vpc: props.vpc,
targets: [props.autoScalingGroup],
healthCheck: {
port: '80',
path: '/healthcheck',
},
});
// --------------------------------------------------------------------
// LISTENERS
// --------------------------------------------------------------------
const httpListener = this.loadBalancer.addRedirect({
sourceProtocol: elb.ApplicationProtocol.HTTP,
sourcePort: 80,
targetProtocol: elb.ApplicationProtocol.HTTPS,
targetPort: 443,
});
const sslListener = this.loadBalancer.addListener('SSLListener', {
protocol: elb.ApplicationProtocol.HTTPS,
port: 443,
sslPolicy: elb.SslPolicy.TLS12,
certificates: [props.certificate],
defaultTargetGroups: [targetGroup],
});
}
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/lib/constructs/route53.ts | import { Construct } from 'constructs';
import { HostedZone, IHostedZone } from 'aws-cdk-lib/aws-route53';
import { Certificate, CertificateValidation } from 'aws-cdk-lib/aws-certificatemanager';
export interface Route53Props {
rootDomain: string;
}
export class Route53Resources extends Construct {
public readonly hostedZone: IHostedZone;
public readonly certificate: Certificate;
constructor(scope: Construct, id: string, props: Route53Props) {
super(scope, id);
this.hostedZone = HostedZone.fromLookup(this, 'PublicHostedZone', {
domainName: props.rootDomain,
});
this.certificate = new Certificate(this, 'PublicCertificate', {
domainName: props.rootDomain,
subjectAlternativeNames: [`*.${props.rootDomain}`],
validation: CertificateValidation.fromDns(this.hostedZone),
});
}
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/lib/constructs/vpc.ts | import { CfnOutput, RemovalPolicy, Stack } from 'aws-cdk-lib';
import { Construct } from 'constructs';
import { LogGroup, RetentionDays } from 'aws-cdk-lib/aws-logs';
import { cleanEnv, str } from 'envalid';
import * as ec2 from 'aws-cdk-lib/aws-ec2';
import * as dotenv from 'dotenv';
import { NagSuppressions } from 'cdk-nag';
dotenv.config();
const env = cleanEnv(process.env, {
ALLOWED_CIDR_RANGE_01: str({ default: '' }),
ROOT_DOMAIN: str({ default: '' }),
});
export interface VpcResourcesProps {
removalPolicy: RemovalPolicy;
}
export class VpcResources extends Construct {
public readonly vpc: ec2.Vpc;
public readonly securityGroups: {
loadBalancer: ec2.SecurityGroup;
workstation: ec2.SecurityGroup;
reverseProxy: ec2.SecurityGroup;
nucleus: ec2.SecurityGroup;
};
public readonly subnets: {
loadBalancer: ec2.ISubnet[];
workstation: ec2.ISubnet[];
reverseProxy: ec2.ISubnet[];
nucleus: ec2.ISubnet[];
};
/**
* Creates a cross-account role allowing the AWS Prototyping Team
* to access customer accounts by assuming the role.
* @param scope the construct scope.
* @param id the identifier given the construct.np
* @param props the construct configuration.
*/
constructor(scope: Construct, id: string, props: VpcResourcesProps) {
super(scope, id);
const stackName = Stack.of(this).stackName;
// ------------------------------------------------------------------------
// Subnets
// ------------------------------------------------------------------------
const natGatewaySubnet: ec2.SubnetConfiguration = {
name: 'NatGatewayPublicSubnet',
subnetType: ec2.SubnetType.PUBLIC,
cidrMask: 28, // 16
};
const loadBalancerSubnetConfig: ec2.SubnetConfiguration = {
name: 'LoadBalancerPrivateSubnet',
subnetType: ec2.SubnetType.PRIVATE_WITH_EGRESS,
cidrMask: 22, // 1024
};
const workstationSubnetConfig: ec2.SubnetConfiguration = {
name: 'WorkstationPublicSubnet',
subnetType: ec2.SubnetType.PRIVATE_WITH_EGRESS,
cidrMask: 22, // 1024
};
const reverseProxySubnetConfig: ec2.SubnetConfiguration = {
name: 'ReverseProxyPublicSubnet',
subnetType: ec2.SubnetType.PRIVATE_WITH_EGRESS,
cidrMask: 22, // 1024
};
const nucleusSubnetConfig: ec2.SubnetConfiguration = {
name: 'NucleusPrivateSubnet',
subnetType: ec2.SubnetType.PRIVATE_WITH_EGRESS,
cidrMask: 22, // 1024
};
// ------------------------------------------------------------------------
// VPC
// ------------------------------------------------------------------------
const cloudWatchLogs = new LogGroup(this, 'CloudWatchVPCLogs', {
retention: RetentionDays.ONE_WEEK,
removalPolicy: props.removalPolicy,
});
// Elastic IP for NatGateway
const eip = new ec2.CfnEIP(this, 'NATGatewayEIP', {
domain: 'vpc',
});
const natGatewayProvider = ec2.NatProvider.gateway({
eipAllocationIds: [eip.attrAllocationId],
});
const cidrRange: string = '10.0.0.0/16'; // 65,536
this.vpc = new ec2.Vpc(this, 'OmniVpc', {
ipAddresses: ec2.IpAddresses.cidr(cidrRange),
natGateways: 1,
subnetConfiguration: [
natGatewaySubnet,
loadBalancerSubnetConfig,
workstationSubnetConfig,
reverseProxySubnetConfig,
nucleusSubnetConfig,
],
natGatewayProvider: natGatewayProvider,
flowLogs: {
'vpc-logs': {
destination: ec2.FlowLogDestination.toCloudWatchLogs(cloudWatchLogs),
trafficType: ec2.FlowLogTrafficType.ALL,
},
},
createInternetGateway: true,
});
this.vpc.selectSubnets({
subnetGroupName: loadBalancerSubnetConfig.name,
}).subnets.forEach((subnet: ec2.ISubnet) => {
(subnet as ec2.Subnet).addRoute('AllowedCidrRoute', {
destinationCidrBlock: env.ALLOWED_CIDR_RANGE_01,
routerType: ec2.RouterType.GATEWAY,
routerId: this.vpc.internetGatewayId!,
enablesInternetConnectivity: true,
});
});
this.subnets = {
loadBalancer: this.vpc.selectSubnets({
subnetGroupName: loadBalancerSubnetConfig.name,
}).subnets,
workstation: this.vpc.selectSubnets({
subnetGroupName: workstationSubnetConfig.name,
}).subnets,
reverseProxy: this.vpc.selectSubnets({
subnetGroupName: reverseProxySubnetConfig.name,
}).subnets,
nucleus: this.vpc.selectSubnets({
subnetGroupName: nucleusSubnetConfig.name,
}).subnets,
};
// ------------------------------------------------------------------------
// Security Groups
// ------------------------------------------------------------------------
const natGatewaySG = new ec2.SecurityGroup(this, 'NatGatewaySG', {
securityGroupName: `${stackName}-nat-gateway-sg`,
description: 'NAT Gateway Security Group',
vpc: this.vpc,
allowAllOutbound: true,
});
const loadBalancerSG = new ec2.SecurityGroup(this, 'LoadBalancerSG', {
securityGroupName: `${stackName}-load-balancer-sg`,
description: 'Load Balancer Security Group',
vpc: this.vpc,
allowAllOutbound: true,
});
const workstationSG = new ec2.SecurityGroup(this, 'WorkstationSG', {
securityGroupName: `${stackName}-workstation-sg`,
description: 'Workstation Security Group',
vpc: this.vpc,
allowAllOutbound: true,
});
const reverseProxySG = new ec2.SecurityGroup(this, 'ReverseProxySG', {
securityGroupName: `${stackName}-reverse-proxy-sg`,
description: 'Reverse Proxy Security Group',
vpc: this.vpc,
allowAllOutbound: true,
});
const nucleusSG = new ec2.SecurityGroup(this, 'NucleusSG', {
securityGroupName: `${stackName}-nucleus-sg`,
description: 'Nucleus Server Security Group',
vpc: this.vpc,
allowAllOutbound: true,
});
const ssmEndpointSG = new ec2.SecurityGroup(this, 'SSMEndpointSG', {
vpc: this.vpc,
allowAllOutbound: true,
description: 'SSM Endpoint Security Group',
});
// loadBalancerSG rules
loadBalancerSG.addIngressRule(ec2.Peer.ipv4(env.ALLOWED_CIDR_RANGE_01), ec2.Port.tcp(80), 'HTTP access');
loadBalancerSG.addIngressRule(ec2.Peer.ipv4(env.ALLOWED_CIDR_RANGE_01), ec2.Port.tcp(443), 'HTTPS access');
loadBalancerSG.addIngressRule(ec2.Peer.ipv4(cidrRange), ec2.Port.tcp(443), 'VPC Access');
loadBalancerSG.addIngressRule(ec2.Peer.securityGroupId(workstationSG.securityGroupId), ec2.Port.tcp(80), 'Workstation access');
loadBalancerSG.addIngressRule(ec2.Peer.securityGroupId(workstationSG.securityGroupId), ec2.Port.tcp(443), 'Workstation access');
loadBalancerSG.addIngressRule(ec2.Peer.securityGroupId(natGatewaySG.securityGroupId), ec2.Port.tcp(443), 'NAT access');
reverseProxySG.addIngressRule(ec2.Peer.ipv4(cidrRange), ec2.Port.tcp(443), 'VPC Access');
reverseProxySG.addIngressRule(ec2.Peer.securityGroupId(natGatewaySG.securityGroupId), ec2.Port.tcp(443), 'NAT access');
// nucleusSG rules
const nucleusRules = [
{ port: 80, desc: 'HTTP Access' },
{ port: 8080, desc: 'Nucleus Web2' },
{ port: 3019, desc: 'Nucleus API' },
{ port: 3030, desc: 'Nucleus LFT' },
{ port: 3333, desc: 'Nucleus Discovery' },
{ port: 3100, desc: 'Nucleus Auth' },
{ port: 3180, desc: 'Nucleus Login' },
{ port: 3020, desc: 'Nucleus Tagging2' },
{ port: 3400, desc: 'Nucleus Search2' },
{ port: 34080, desc: 'Nucleus Navigator' },
];
nucleusRules.forEach((rule) => {
nucleusSG.addIngressRule(
ec2.Peer.securityGroupId(reverseProxySG.securityGroupId),
ec2.Port.tcp(rule.port),
rule.desc
);
});
nucleusSG.addIngressRule(ec2.Peer.ipv4(cidrRange), ec2.Port.tcp(443), 'VPC access');
nucleusSG.addIngressRule(ec2.Peer.securityGroupId(natGatewaySG.securityGroupId), ec2.Port.tcp(443), 'NAT access');
// workstationSG rules
workstationSG.addIngressRule(ec2.Peer.ipv4(env.ALLOWED_CIDR_RANGE_01), ec2.Port.tcp(443), 'HTTPS access');
workstationSG.addIngressRule(ec2.Peer.ipv4(env.ALLOWED_CIDR_RANGE_01), ec2.Port.udp(8443), 'UDP access');
workstationSG.addIngressRule(ec2.Peer.ipv4(cidrRange), ec2.Port.tcp(443), 'VPC access');
workstationSG.addIngressRule(ec2.Peer.securityGroupId(natGatewaySG.securityGroupId), ec2.Port.tcp(443), 'NAT access');
this.securityGroups = {
loadBalancer: loadBalancerSG,
workstation: workstationSG,
reverseProxy: reverseProxySG,
nucleus: nucleusSG,
};
// ssm endpoint rules
ssmEndpointSG.addIngressRule(ec2.Peer.ipv4(cidrRange), ec2.Port.tcp(443), 'HTTPS Access');
// ------------------------------------------------------------------------
// Service Endpoints
// ------------------------------------------------------------------------
const s3Endpoint: ec2.GatewayVpcEndpoint = this.vpc.addGatewayEndpoint('S3GatewayEndpoint', {
service: ec2.GatewayVpcEndpointAwsService.S3,
subnets: [{ subnets: this.subnets.nucleus }, { subnets: this.subnets.reverseProxy }],
});
const ssmEndpoint: ec2.InterfaceVpcEndpoint = this.vpc.addInterfaceEndpoint(
'ssm-interface-endpoint',
{
service: ec2.InterfaceVpcEndpointAwsService.SSM,
subnets: { subnets: this.subnets.nucleus },
securityGroups: [this.securityGroups.nucleus],
open: false,
}
);
// ------------------------------------------------------------------------
// Outputs
// ------------------------------------------------------------------------
new CfnOutput(this, 'VpcID', {
value: this.vpc.vpcId,
});
// ------------------------------------
// CDK_NAG (security scan) suppressions
// ------------------------------------
NagSuppressions.addResourceSuppressions(
reverseProxySG,
[
{
id: 'AwsSolutions-EC23',
reason:
'Security Group inbound access can be modified in the app configuration. For production, this will be set to the IP range for the local network.',
},
],
true
);
NagSuppressions.addResourceSuppressions(
nucleusSG,
[
{
id: 'AwsSolutions-EC23',
reason:
'Security Group inbound access can be modified in the app configuration. For production, this will be set to the IP range for the local network.',
},
],
true
);
NagSuppressions.addResourceSuppressions(
loadBalancerSG,
[
{
id: 'AwsSolutions-EC23',
reason:
'Security Group inbound access can be modified in the app configuration. For production, this will be set to the IP range for the local network.',
},
],
true
);
}
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/lib/constructs/nucleusServer.ts | import { Construct } from 'constructs';
import { Stack, Tags, RemovalPolicy } from 'aws-cdk-lib';
import { NagSuppressions } from 'cdk-nag';
import { CustomResource } from './common/customResource';
import { cleanEnv, bool, str } from 'envalid';
import * as iam from 'aws-cdk-lib/aws-iam';
import * as s3 from 'aws-cdk-lib/aws-s3';
import * as ec2 from 'aws-cdk-lib/aws-ec2';
import * as secretsmanager from 'aws-cdk-lib/aws-secretsmanager';
import * as pyLambda from '@aws-cdk/aws-lambda-python-alpha';
import * as dotenv from 'dotenv';
import * as fs from 'fs';
import * as path from 'path';
dotenv.config();
const env = cleanEnv(process.env, {
ALLOWED_CIDR_RANGE_01: str({ default: '' }),
ALLOWED_CIDR_RANGE_02: str({ default: '' }),
DEV_MODE: bool({ default: false }),
ROOT_DOMAIN: str({ default: '' }),
NUCLEUS_SERVER_PREFIX: str({ default: 'nucleus' }),
NUCLEUS_BUILD: str({ default: '' }),
});
export type ConstructProps = {
removalPolicy: RemovalPolicy;
vpc: ec2.Vpc;
subnets: ec2.ISubnet[];
artifactsBucket: s3.IBucket;
nucleusServerSG: ec2.SecurityGroup;
lambdaLayers: pyLambda.PythonLayerVersion[];
};
export class NucleusServerResources extends Construct {
public readonly nucleusServerInstance: ec2.Instance;
constructor(scope: Construct, id: string, props: ConstructProps) {
super(scope, id);
const region: string = Stack.of(this).region;
const account: string = Stack.of(this).account;
const stackName: string = Stack.of(this).stackName;
const fullDomainName = `${env.NUCLEUS_SERVER_PREFIX}.${env.ROOT_DOMAIN}`;
// Templated secret
const ovMainLogin = new secretsmanager.Secret(this, 'ovMainLogin', {
generateSecretString: {
secretStringTemplate: JSON.stringify({ username: 'omniverse' }),
excludePunctuation: true,
generateStringKey: 'password',
},
});
// Templated secret
const ovServiceLogin = new secretsmanager.Secret(this, 'ovServiceLogin', {
generateSecretString: {
secretStringTemplate: JSON.stringify({ username: 'omniverse' }),
excludePunctuation: true,
generateStringKey: 'password',
},
});
const instance_role = new iam.Role(this, 'InstanceRole', {
assumedBy: new iam.ServicePrincipal('ec2.amazonaws.com'),
description: 'EC2 Instance Role',
managedPolicies: [iam.ManagedPolicy.fromAwsManagedPolicyName('AmazonSSMManagedInstanceCore')],
});
const ebs_volume: ec2.BlockDevice = {
deviceName: '/dev/sda1',
volume: ec2.BlockDeviceVolume.ebs(512, {
encrypted: true,
}),
};
// Canonical, Ubuntu, 20.04 LTS, amd64
const nucleusServerAMI = ec2.MachineImage.fromSsmParameter(
'/aws/service/canonical/ubuntu/server/focal/stable/current/amd64/hvm/ebs-gp2/ami-id',
{
os: ec2.OperatingSystemType.LINUX,
}
);
this.nucleusServerInstance = new ec2.Instance(this, 'NucleusServer', {
instanceType: new ec2.InstanceType('c5.4xlarge'),
machineImage: nucleusServerAMI,
blockDevices: [ebs_volume],
vpc: props.vpc,
role: instance_role,
securityGroup: props.nucleusServerSG,
vpcSubnets: { subnets: props.subnets },
detailedMonitoring: true,
});
this.nucleusServerInstance.applyRemovalPolicy(props.removalPolicy);
Tags.of(this.nucleusServerInstance).add('Name', `${stackName}/NucleusServer`);
// artifacts bucket
instance_role.addToPolicy(
new iam.PolicyStatement({
resources: [`${props.artifactsBucket.bucketArn}`, `${props.artifactsBucket.bucketArn}/*`],
actions: ['s3:ListBucket', 's3:GetObject'],
})
);
instance_role.addToPolicy(
new iam.PolicyStatement({
actions: [
'logs:CreateLogGroup',
'logs:CreateLogStream',
'logs:DescribeLogStreams',
'logs:PutLogEvents',
],
resources: ['arn:aws:logs:*:*:log-group:/aws/ssm/*'],
})
);
// --------------------------------------------------------------------
// CUSTOM RESOURCE - Nucleus Server Config
// --------------------------------------------------------------------
// Custom Resource to manage nucleus server configuration
const nucleusConfigLambdaPolicy = new iam.PolicyDocument({
statements: [
new iam.PolicyStatement({
actions: ['ssm:SendCommand'],
resources: [
`arn:aws:ec2:${region}:${account}:instance/${this.nucleusServerInstance.instanceId}`,
],
}),
new iam.PolicyStatement({
actions: ['ssm:SendCommand'],
resources: ['arn:aws:ssm:*:*:document/*'],
}),
new iam.PolicyStatement({
actions: ['ssm:GetCommandInvocation'],
resources: [`arn:aws:ssm:${region}:${account}:*`],
}),
new iam.PolicyStatement({
actions: ['secretsmanager:GetSecretValue', 'secretsmanager:DescribeSecret'],
resources: [ovMainLogin.secretArn, ovServiceLogin.secretArn],
}),
],
});
const nucleusServerConfig = new CustomResource(this, 'NucleusServerConfig', {
lambdaName: 'NucleusServerConfig',
lambdaCodePath: './src/lambda/customResources/nucleusServerConfig',
lambdaPolicyDocument: nucleusConfigLambdaPolicy,
resourceProps: {
nounce: 2,
instanceId: this.nucleusServerInstance.instanceId,
reverseProxyDomain: fullDomainName,
nucleusBuild: env.NUCLEUS_BUILD,
artifactsBucket: props.artifactsBucket.bucketName,
ovMainLoginSecretArn: ovMainLogin.secretName,
ovServiceLoginSecretArn: ovServiceLogin.secretArn,
},
lambdaLayers: props.lambdaLayers,
removalPolicy: props.removalPolicy
});
nucleusServerConfig.resource.node.addDependency(this.nucleusServerInstance);
// -------------------------------
// CDK_NAG (security scan) suppressions
// -------------------------------
NagSuppressions.addResourceSuppressions(
ovMainLogin,
[
{
id: 'AwsSolutions-SMG4',
reason:
'Auto rotate secrets: Secrets Manager used to hold credentials required for deployment. Will be replaced by SSO strategy in production',
},
],
true
);
NagSuppressions.addResourceSuppressions(
ovServiceLogin,
[
{
id: 'AwsSolutions-SMG4',
reason:
'Auto rotate secrets: Secrets Manager used to hold credentials required for deployment. Will be replaced by SSO strategy in production',
},
],
true
);
NagSuppressions.addResourceSuppressions(
instance_role,
[
{
id: 'AwsSolutions-IAM5',
reason:
'Wildcard Permissions: Unable to know which objects exist ahead of time. Need to use wildcard',
},
],
true
);
NagSuppressions.addResourceSuppressions(
this.nucleusServerInstance,
[
{
id: 'AwsSolutions-EC29',
reason: 'CDK_NAG is not recognizing the applied removalPolicy',
},
],
true
);
}
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/lib/constructs/autoscaling.ts | import { Construct } from 'constructs';
import { Stack, Duration, RemovalPolicy } from 'aws-cdk-lib';
import * as autoscaling from 'aws-cdk-lib/aws-autoscaling';
import * as ec2 from 'aws-cdk-lib/aws-ec2';
import * as iam from 'aws-cdk-lib/aws-iam';
import * as s3 from 'aws-cdk-lib/aws-s3';
import * as pyLambda from '@aws-cdk/aws-lambda-python-alpha';
import * as lambda from 'aws-cdk-lib/aws-lambda';
import * as logs from 'aws-cdk-lib/aws-logs';
import * as events from 'aws-cdk-lib/aws-events';
import * as targets from 'aws-cdk-lib/aws-events-targets';
import { NagSuppressions } from 'cdk-nag';
export interface AutoScalingResourceProps {
name: string;
removalPolicy: RemovalPolicy;
artifactsBucket: s3.IBucket;
vpcResources: {
vpc: ec2.Vpc;
subnets: ec2.ISubnet[];
};
launchTemplate: ec2.LaunchTemplate;
capacity: {
min: number;
max: number;
};
lambdaResources?: {
entry: string;
layers: pyLambda.PythonLayerVersion[];
environment: { [key: string]: string; };
policies?: { [key: string]: iam.PolicyDocument; };
};
}
export class AutoScalingResources extends Construct {
public readonly autoScalingGroup: autoscaling.AutoScalingGroup;
constructor(scope: Construct, id: string, props: AutoScalingResourceProps) {
super(scope, id);
const region: string = Stack.of(this).region;
const account: string = Stack.of(this).account;
this.autoScalingGroup = new autoscaling.AutoScalingGroup(
this,
`${props.name}AutoScalingGroup`,
{
vpc: props.vpcResources.vpc,
vpcSubnets: { subnets: props.vpcResources.subnets },
minCapacity: props.capacity.min,
maxCapacity: props.capacity.max,
launchTemplate: props.launchTemplate,
updatePolicy: autoscaling.UpdatePolicy.replacingUpdate(),
healthCheck: autoscaling.HealthCheck.ec2({ grace: Duration.minutes(1) }),
}
);
if (props.lambdaResources != undefined) {
// Scale Up Lifecycle Hook
this.autoScalingGroup.addLifecycleHook(`${props.name}ScaleUpLifecycleHook`, {
heartbeatTimeout: Duration.seconds(300),
defaultResult: autoscaling.DefaultResult.ABANDON,
lifecycleTransition: autoscaling.LifecycleTransition.INSTANCE_LAUNCHING,
});
// Scale Down Lifecycle Hook
this.autoScalingGroup.addLifecycleHook(`${props.name}ScaleDownLifecycleHook`, {
heartbeatTimeout: Duration.seconds(300),
defaultResult: autoscaling.DefaultResult.ABANDON,
lifecycleTransition: autoscaling.LifecycleTransition.INSTANCE_TERMINATING,
});
const lifecycleLambdaPolicy = new iam.PolicyDocument({
statements: [
new iam.PolicyStatement({
resources: [`${this.autoScalingGroup.autoScalingGroupArn}`],
actions: ['autoscaling:CompleteLifecycleAction'],
}),
new iam.PolicyStatement({
actions: ['autoscaling:DescribeAutoScalingGroups'],
resources: ['*'],
}),
new iam.PolicyStatement({
resources: [
`arn:aws:ssm:${region}::document/AWS-RunPowerShellScript`,
`arn:aws:ssm:${region}::document/AWS-RunShellScript`,
],
actions: ['ssm:SendCommand'],
}),
new iam.PolicyStatement({
resources: ['arn:aws:ec2:*:*:instance/*'],
actions: ['ssm:SendCommand'],
conditions: {
StringEquals: {
'iam:ssm:ResourceTag/aws:autoscaling:groupName':
this.autoScalingGroup.autoScalingGroupName,
},
},
}),
new iam.PolicyStatement({
resources: ['*'],
actions: ['ssm:GetCommandInvocation'],
}),
],
});
const configLambdaPolicy = new iam.PolicyDocument({
statements: [
new iam.PolicyStatement({
actions: ['ssm:SendCommand'],
resources: [`arn:aws:ec2:${region}:${account}:instance/*`],
}),
new iam.PolicyStatement({
actions: ['ec2:DescribeInstances', 'ec2:DescribeInstanceStatus'],
resources: [`*`],
}),
new iam.PolicyStatement({
actions: ['ssm:SendCommand'],
resources: ['arn:aws:ssm:*:*:document/*'],
}),
new iam.PolicyStatement({
actions: ['ssm:GetCommandInvocation'],
resources: [`arn:aws:ssm:${region}:${account}:*`],
}),
],
});
const lifecycleLambdaRole = new iam.Role(this, `${props.name}LifecycleLambdaRole`, {
assumedBy: new iam.ServicePrincipal('lambda.amazonaws.com'),
managedPolicies: [iam.ManagedPolicy.fromAwsManagedPolicyName('service-role/AWSLambdaVPCAccessExecutionRole')],
inlinePolicies: {
lifecycleLambdaPolicy: lifecycleLambdaPolicy,
configLambdaPolicy: configLambdaPolicy,
...props.lambdaResources.policies,
},
});
const lambdaName = `${props.name}AutoScalingLifecycleLambdaFunction`.slice(0, 64);
const logGroup = new logs.LogGroup(this, 'LifecycleLambdaFnLogGroup', {
retention: logs.RetentionDays.ONE_WEEK,
removalPolicy: props.removalPolicy,
});
const lifecycleLambdaFn = new pyLambda.PythonFunction(
this,
`${props.name}LifecycleLambdaFn`,
{
functionName: lambdaName,
runtime: lambda.Runtime.PYTHON_3_9,
handler: 'handler',
entry: props.lambdaResources.entry,
role: lifecycleLambdaRole,
timeout: Duration.minutes(5),
layers: props.lambdaResources.layers,
environment: props.lambdaResources.environment,
vpc: props.vpcResources.vpc,
vpcSubnets: {
subnets: props.vpcResources.subnets
},
}
);
lifecycleLambdaFn.node.addDependency(logGroup);
lifecycleLambdaFn.addToRolePolicy(
new iam.PolicyStatement({
actions: ['logs:CreateLogStream', 'logs:PutLogEvents'],
resources: [logGroup.logGroupArn],
})
);
const rule = new events.Rule(this, `${props.name}EventRule`, {
eventPattern: {
source: ['aws.autoscaling'],
detailType: [
'EC2 Instance-launch Lifecycle Action',
'EC2 Instance-terminate Lifecycle Action',
],
detail: {
AutoScalingGroupName: [this.autoScalingGroup.autoScalingGroupName],
},
},
});
rule.node.addDependency(lifecycleLambdaFn);
rule.addTarget(new targets.LambdaFunction(lifecycleLambdaFn));
NagSuppressions.addResourceSuppressions(
lifecycleLambdaRole,
[
{
id: 'AwsSolutions-IAM5',
reason:
'Wildcard Permissions: This is a Dummy Policy with minimal actions. This policy is updated on the fly by the revProxyCertAssociation custom resource',
},
],
true
);
}
NagSuppressions.addResourceSuppressions(
this.autoScalingGroup,
[
{
id: 'AwsSolutions-AS3',
reason:
'Autoscaling Event notifications: Backlogged, will provide guidance in production document',
},
],
true
);
}
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/lib/constructs/common/customResource.ts | import { Construct } from 'constructs';
import { Duration, Stack, RemovalPolicy } from 'aws-cdk-lib';
import { NagSuppressions } from 'cdk-nag';
import * as cdk from 'aws-cdk-lib';
import * as iam from 'aws-cdk-lib/aws-iam';
import * as logs from 'aws-cdk-lib/aws-logs';
import * as cr from 'aws-cdk-lib/custom-resources';
import * as lambda from 'aws-cdk-lib/aws-lambda';
import * as pyLambda from '@aws-cdk/aws-lambda-python-alpha';
import fs = require('fs');
import crypto = require('crypto');
interface LooseTypeObject {
[key: string]: any;
}
export type ConstructProps = {
lambdaName: string;
lambdaCodePath: string;
lambdaPolicyDocument: iam.PolicyDocument;
resourceProps: LooseTypeObject;
removalPolicy: RemovalPolicy;
lambdaLayers?: pyLambda.PythonLayerVersion[];
};
export class CustomResource extends Construct {
public readonly resource: cdk.CustomResource;
constructor(scope: Construct, id: string, props: ConstructProps) {
super(scope, id);
const region: string = Stack.of(this).region;
const account: string = Stack.of(this).account;
const lambdaRole = new iam.Role(this, 'lambdaRole', {
assumedBy: new iam.ServicePrincipal('lambda.amazonaws.com'),
inlinePolicies: {
lambdaPolicyDocument: props.lambdaPolicyDocument,
},
});
const lambdaName = `${Stack.of(this).stackName}-${props.lambdaName}-CustomResource`.slice(0, 64);
const lambdaLogGroup = `/aws/lambda/${lambdaName}`;
const logGroup = new logs.LogGroup(this, 'lambdaFnLogGroup', {
logGroupName: lambdaLogGroup,
retention: logs.RetentionDays.ONE_WEEK,
removalPolicy: props.removalPolicy ?? RemovalPolicy.DESTROY,
});
const lambdaFn = new pyLambda.PythonFunction(this, 'lambdaFn', {
functionName: lambdaName,
runtime: lambda.Runtime.PYTHON_3_9,
handler: 'handler',
entry: props.lambdaCodePath,
role: lambdaRole,
timeout: Duration.minutes(5),
layers: props.lambdaLayers || [],
});
lambdaFn.node.addDependency(logGroup);
lambdaFn.addToRolePolicy(
new iam.PolicyStatement({
actions: ['logs:CreateLogStream', 'logs:PutLogEvents'],
resources: [logGroup.logGroupArn],
})
);
const provider = new cr.Provider(this, 'provider', {
onEventHandler: lambdaFn,
});
// force resource to update when code changes
const fileBuffer = fs.readFileSync(`${props.lambdaCodePath}/index.py`);
const hashSum = crypto.createHash('sha256');
hashSum.update(fileBuffer);
const hex = hashSum.digest('hex');
props.resourceProps.codeHash = hex;
props.resourceProps.region = region;
this.resource = new cdk.CustomResource(this, 'resource', {
serviceToken: provider.serviceToken,
properties: props.resourceProps,
});
// Nag NagSuppressions
NagSuppressions.addResourceSuppressions(
lambdaRole,
[
{
id: 'AwsSolutions-IAM5',
reason:
'Wildcard Permissions: Unable to know which objects exist ahead of time. Need to use wildcard',
},
],
true
);
NagSuppressions.addResourceSuppressions(
provider,
[
{
id: 'AwsSolutions-IAM4',
reason: 'Auto-generated resource with managed policy',
},
{
id: 'AwsSolutions-IAM5',
reason: 'Auto-generated resource with wildcard policy',
},
{
id: 'AwsSolutions-L1',
reason: 'Auto-generated resource not configured to use the latest runtime',
},
],
true
);
}
}
|
aws-samples/nvidia-omniverse-nucleus-on-amazon-ec2/lib/utils/regions.ts | export const regions = [
'us-east-1',
'us-east-2',
'us-west-1',
'us-west-2',
'af-south-1',
'ap-east-1',
'ap-south-2',
'ap-southeast-3',
'ap-south-1',
'ap-northeast-3',
'ap-northeast-2',
'ap-southeast-1',
'ap-southeast-2',
'ap-northeast-1',
'ca-central-1',
'eu-central-1',
'eu-west-1',
'eu-west-2',
'eu-south-1',
'eu-west-3',
'eu-south-2',
'eu-north-1',
'eu-central-2',
'me-south-1',
'me-central-1',
'sa-east-1'
]; |
arhix52/Strelka/conanfile.py | import os
from conan import ConanFile
from conan.tools.cmake import cmake_layout
from conan.tools.files import copy
class StrelkaRecipe(ConanFile):
settings = "os", "compiler", "build_type", "arch"
generators = "CMakeToolchain", "CMakeDeps"
def requirements(self):
self.requires("glm/cci.20230113")
self.requires("spdlog/[>=1.4.1]")
self.requires("imgui/1.89.3")
self.requires("glfw/3.3.8")
self.requires("stb/cci.20230920")
self.requires("glad/0.1.36")
self.requires("doctest/2.4.11")
self.requires("cxxopts/3.1.1")
self.requires("tinygltf/2.8.19")
self.requires("nlohmann_json/3.11.3")
def generate(self):
copy(self, "*glfw*", os.path.join(self.dependencies["imgui"].package_folder,
"res", "bindings"), os.path.join(self.source_folder, "external", "imgui"))
copy(self, "*opengl3*", os.path.join(self.dependencies["imgui"].package_folder,
"res", "bindings"), os.path.join(self.source_folder, "external", "imgui"))
copy(self, "*metal*", os.path.join(self.dependencies["imgui"].package_folder,
"res", "bindings"), os.path.join(self.source_folder, "external", "imgui"))
def layout(self):
cmake_layout(self)
|
arhix52/Strelka/BuildOpenUSD.md | USD building:
VS2019 + python 3.10
To build debug on windows:
python USD\build_scripts\build_usd.py "C:\work\USD_build_debug" --python --materialx --build-variant debug
For USD 23.03 you could use VS2022
Linux:
* python3 ./OpenUSD/build_scripts/build_usd.py /home/<user>/work/OpenUSD_build/ --python --materialx
|
arhix52/Strelka/CMakeLists.txt | cmake_minimum_required(VERSION 3.22)
project(Strelka LANGUAGES CXX)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(CMAKE_CXX_EXTENSIONS OFF)
# Set to TRUE to enable USD
set(ENABLE_HYDRA FALSE)
if(NOT DEFINED CMAKE_CUDA_STANDARD)
set(CMAKE_CUDA_STANDARD 11)
set(CMAKE_CUDA_STANDARD_REQUIRED ON)
endif()
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${CMAKE_SOURCE_DIR}/cmake/")
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
set(CMAKE_POSITION_INDEPENDENT_CODE ON)
if(UNIX AND NOT APPLE)
set(LINUX TRUE)
endif()
if(WIN32)
add_compile_definitions(NOMINMAX)
add_compile_definitions(_USE_MATH_DEFINES)
add_compile_definitions(_ALLOW_ITERATOR_DEBUG_LEVEL_MISMATCH)
endif()
set(ROOT_HOME ${CMAKE_CURRENT_LIST_DIR})
set(OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR})
add_subdirectory(src/log)
add_subdirectory(src/settings)
add_subdirectory(src/render)
add_subdirectory(src/scene)
add_subdirectory(src/materialmanager)
add_subdirectory(src/display)
if (ENABLE_HYDRA)
add_subdirectory(src/HdStrelka)
add_subdirectory(src/hdRunner)
endif()
add_subdirectory(src/sceneloader)
add_subdirectory(src/app)
if(WIN32 OR LINUX)
add_subdirectory(tests)
endif()
|
arhix52/Strelka/build.sh | #!/bin/bash
if [ "$#" -ne 1 ] && [ "$#" -ne 2 ]; then
echo "Usage: $0 <build_type> [clean]"
exit 1
fi
build_type="$1"
clean_option="$2"
# Function to convert the input parameter to start with a capital letter
ucfirst() {
echo "$1" | awk '{print toupper(substr($0,1,1)) tolower(substr($0,2))}'
}
# Convert the build_type to start with a capital letter
build_type=$(ucfirst "$build_type")
# Step 1: Install Conan dependencies
conan install . -c tools.cmake.cmaketoolchain:generator=Ninja -c tools.system.package_manager:mode=install -c tools.system.package_manager:sudo=True --build=missing --settings=build_type="$build_type"
# Step 2: Navigate to the build directory
cd build/"$build_type"
# Check if the "clean" option is specified
if [ "$clean_option" == "clean" ]; then
# Clean the build directory
cmake --build . --target clean
fi
# Step 3: Source the Conan environment variables
source ./generators/conanbuild.sh
# Step 4: Run CMake with the appropriate toolchain file
cmake ../.. -G Ninja -DCMAKE_TOOLCHAIN_FILE=generators/conan_toolchain.cmake -DCMAKE_BUILD_TYPE="$build_type"
# Step 5: Build the project and capture the time
start_time=$(date +%s)
cmake --build .
end_time=$(date +%s)
# Calculate the elapsed time
elapsed_time=$((end_time - start_time))
# Output the build time
echo "Build completed in $elapsed_time seconds."
|
arhix52/Strelka/README.md | # Strelka
Path tracing render based on NVIDIA OptiX + NVIDIA MDL and Apple Metal
## OpenUSD Hydra render delegate
![Kitchen Set from OpenUSD](images/Kitchen_2048i_4d_2048spp_0.png)
## Basis curves support
![Hairs](images/hairmat_2_light_10000i_6d_10000spp_0.png)
![Einar](images/einar_1024i_3d_1024spp_0.png)
## Project Dependencies
OpenUSD https://github.com/PixarAnimationStudios/OpenUSD
* Set evn var: `USD_DIR=c:\work\USD_build`
OptiX
* Set evn var: `OPTIX_DIR=C:\work\OptiX SDK 8.0.0`
Download MDL sdk (for example: mdl-sdk-367100.2992): https://developer.nvidia.com/nvidia-mdl-sdk-get-started
* unzip content to /external/mdl-sdk/
LLVM 12.0.1 (https://github.com/llvm/llvm-project/releases/tag/llvmorg-12.0.1) for MDL ptx code generator
* for win: https://github.com/llvm/llvm-project/releases/download/llvmorg-12.0.1/LLVM-12.0.1-win64.exe
* for linux: https://github.com/llvm/llvm-project/releases/download/llvmorg-12.0.1/clang+llvm-12.0.1-x86_64-linux-gnu-ubuntu-16.04.tar.xz
* install it to `c:\work` for example
* add to PATH: `c:\work\LLVM\bin`
* extract 2 header files files from external/clang12_patched to `C:\work\LLVM\lib\clang\12.0.1\include`
Strelka uses conan https://conan.io/
* install conan: `pip install conan`
* install ninja [https://ninja-build.org/] build system: `sudo apt install ninja-build`
detect conan profile: `conan profile detect --force`
1. `conan install . --build=missing --settings=build_type=Debug`
2. `cd build`
3. `cmake .. -G "Visual Studio 17 2022" -DCMAKE_TOOLCHAIN_FILE=generators\conan_toolchain.cmake`
4. `cmake --build . --config Debug`
On Mac/Linux:
1. `conan install . -c tools.cmake.cmaketoolchain:generator=Ninja -c tools.system.package_manager:mode=install -c tools.system.package_manager:sudo=True --build=missing --settings=build_type=Debug`
2. `cd build/Debug`
3. `source ./generators/conanbuild.sh`
4. `cmake ../.. -DCMAKE_TOOLCHAIN_FILE=generators/conan_toolchain.cmake -DCMAKE_BUILD_TYPE=Debug`
5. `cmake --build .`
#### Installation
#### Launch
## Synopsis
Strelka -s <USD Scene path> [OPTION...] positional parameters
-s, --scene arg scene path (default: "")
-i, --iteration arg Iteration to capture (default: -1)
-h, --help Print usage
To set log level use
`export SPDLOG_LEVEL=debug`
The available log levels are: trace, debug, info, warn, and err.
## Example
./Strelka -s misc/coffeemaker.usdc -i 100
## USD
USD env:
export USD_DIR=/Users/<user>/work/usd_build/
export PATH=/Users/<user>/work/usd_build/bin:$PATH
export PYTHONPATH=/Users/<user>/work/usd_build/lib/python:$PYTHONPATH
Install plugin:
cmake --install . --component HdStrelka
## License
* USD plugin design and material translation code based on Pablo Gatling code:
https://github.com/pablode/gatling |
arhix52/Strelka/src/HdStrelka/RenderParam.h | #pragma once
#include "pxr/pxr.h"
#include "pxr/imaging/hd/renderDelegate.h"
#include "pxr/imaging/hd/renderThread.h"
#include <scene/scene.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaRenderParam final : public HdRenderParam
{
public:
HdStrelkaRenderParam(oka::Scene* scene, HdRenderThread* renderThread, std::atomic<int>* sceneVersion)
: mScene(scene), mRenderThread(renderThread), mSceneVersion(sceneVersion)
{
}
virtual ~HdStrelkaRenderParam() = default;
/// Accessor for the top-level embree scene.
oka::Scene* AcquireSceneForEdit()
{
mRenderThread->StopRender();
(*mSceneVersion)++;
return mScene;
}
private:
oka::Scene* mScene;
/// A handle to the global render thread.
HdRenderThread* mRenderThread;
/// A version counter for edits to mScene.
std::atomic<int>* mSceneVersion;
};
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/BasisCurves.h | #pragma once
#include <pxr/pxr.h>
#include <pxr/imaging/hd/basisCurves.h>
#include <scene/scene.h>
#include <pxr/base/gf/vec2f.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaBasisCurves final : public HdBasisCurves
{
public:
HF_MALLOC_TAG_NEW("new HdStrelkaBasicCurves");
HdStrelkaBasisCurves(const SdfPath& id, oka::Scene* scene);
~HdStrelkaBasisCurves() override;
void Sync(HdSceneDelegate* sceneDelegate,
HdRenderParam* renderParam,
HdDirtyBits* dirtyBits,
const TfToken& reprToken) override;
HdDirtyBits GetInitialDirtyBitsMask() const override;
void _ConvertCurve();
const std::vector<glm::float3>& GetPoints() const;
const std::vector<float>& GetWidths() const;
const std::vector<uint32_t>& GetVertexCounts() const;
const GfMatrix4d& GetPrototypeTransform() const;
const char* getName() const;
protected:
void _InitRepr(const TfToken& reprName, HdDirtyBits* dirtyBits) override;
HdDirtyBits _PropagateDirtyBits(HdDirtyBits bits) const override;
private:
bool _FindPrimvar(HdSceneDelegate* sceneDelegate, const TfToken& primvarName, HdInterpolation& interpolation) const;
void _PullPrimvars(HdSceneDelegate* sceneDelegate,
VtVec3fArray& points,
VtVec3fArray& normals,
VtFloatArray& widths,
bool& indexedNormals,
bool& indexedUVs,
GfVec3f& color,
bool& hasColor) const;
void _UpdateGeometry(HdSceneDelegate* sceneDelegate);
oka::Scene* mScene;
std::string mName;
GfVec3f mColor;
VtIntArray mVertexCounts;
VtVec3fArray mPoints;
VtVec3fArray mNormals;
VtFloatArray mWidths;
GfMatrix4d m_prototypeTransform;
HdBasisCurvesTopology mTopology;
std::vector<glm::float3> mCurvePoints;
std::vector<float> mCurveWidths;
std::vector<uint32_t> mCurveVertexCounts;
// std::vector<GfVec2f> m_uvs;
};
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Tokens.cpp | #include "Tokens.h"
PXR_NAMESPACE_OPEN_SCOPE
TF_DEFINE_PUBLIC_TOKENS(HdStrelkaSettingsTokens, HD_STRELKA_SETTINGS_TOKENS);
TF_DEFINE_PUBLIC_TOKENS(HdStrelkaNodeIdentifiers, HD_STRELKA_NODE_IDENTIFIER_TOKENS);
TF_DEFINE_PUBLIC_TOKENS(HdStrelkaSourceTypes, HD_STRELKA_SOURCE_TYPE_TOKENS);
TF_DEFINE_PUBLIC_TOKENS(HdStrelkaDiscoveryTypes, HD_STRELKA_DISCOVERY_TYPE_TOKENS);
TF_DEFINE_PUBLIC_TOKENS(HdStrelkaRenderContexts, HD_STRELKA_RENDER_CONTEXT_TOKENS);
TF_DEFINE_PUBLIC_TOKENS(HdStrelkaNodeContexts, HD_STRELKA_NODE_CONTEXT_TOKENS);
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/MdlDiscoveryPlugin.h | #pragma once
#include <pxr/usd/ndr/discoveryPlugin.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaMdlDiscoveryPlugin final : public NdrDiscoveryPlugin
{
public:
NdrNodeDiscoveryResultVec DiscoverNodes(const Context& ctx) override;
const NdrStringVec& GetSearchURIs() const override;
};
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Material.h | #pragma once
#include "materialmanager.h"
#include "MaterialNetworkTranslator.h"
#include <pxr/imaging/hd/material.h>
#include <pxr/imaging/hd/sceneDelegate.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaMaterial final : public HdMaterial
{
public:
HF_MALLOC_TAG_NEW("new HdStrelkaMaterial");
HdStrelkaMaterial(const SdfPath& id, const MaterialNetworkTranslator& translator);
~HdStrelkaMaterial() override;
HdDirtyBits GetInitialDirtyBitsMask() const override;
void Sync(HdSceneDelegate* sceneDelegate, HdRenderParam* renderParam, HdDirtyBits* dirtyBits) override;
const std::string& GetStrelkaMaterial() const;
bool isMdl() const
{
return mIsMdl;
}
std::string getFileUri()
{
return mMdlFileUri;
}
std::string getSubIdentifier()
{
return mMdlSubIdentifier;
}
const std::vector<oka::MaterialManager::Param>& getParams() const
{
return mMaterialParams;
}
private:
const MaterialNetworkTranslator& m_translator;
bool mIsMdl = false;
std::string mMaterialXCode;
// MDL related
std::string mMdlFileUri;
std::string mMdlSubIdentifier;
std::vector<oka::MaterialManager::Param> mMaterialParams;
};
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Light.cpp | #include "Light.h"
#include <glm/glm.hpp>
#include <glm/gtc/matrix_transform.hpp>
#include <glm/gtc/type_ptr.hpp>
#include <glm/gtx/compatibility.hpp>
#include <pxr/imaging/hd/instancer.h>
#include <pxr/imaging/hd/meshUtil.h>
#include <pxr/imaging/hd/smoothNormals.h>
#include <pxr/imaging/hd/vertexAdjacency.h>
PXR_NAMESPACE_OPEN_SCOPE
// Lookup table from:
// Colour Rendering of Spectra
// by John Walker
// https://www.fourmilab.ch/documents/specrend/specrend.c
//
// Covers range from 1000k to 10000k in 500k steps
// assuming Rec709 / sRGB colorspace chromaticity.
//
// NOTE: 6500K doesn't give a pure white because the D65
// illuminant used by Rec. 709 doesn't lie on the
// Planckian Locus. We would need to compute the
// Correlated Colour Temperature (CCT) using Ohno's
// method to get pure white. Maybe one day.
//
// Note that the beginning and ending knots are repeated to simplify
// boundary behavior. The last 4 knots represent the segment starting
// at 1.0.
//
static GfVec3f const _blackbodyRGB[] = {
GfVec3f(1.000000f, 0.027490f, 0.000000f), // 1000 K (Approximation)
GfVec3f(1.000000f, 0.027490f, 0.000000f), // 1000 K (Approximation)
GfVec3f(1.000000f, 0.149664f, 0.000000f), // 1500 K (Approximation)
GfVec3f(1.000000f, 0.256644f, 0.008095f), // 2000 K
GfVec3f(1.000000f, 0.372033f, 0.067450f), // 2500 K
GfVec3f(1.000000f, 0.476725f, 0.153601f), // 3000 K
GfVec3f(1.000000f, 0.570376f, 0.259196f), // 3500 K
GfVec3f(1.000000f, 0.653480f, 0.377155f), // 4000 K
GfVec3f(1.000000f, 0.726878f, 0.501606f), // 4500 K
GfVec3f(1.000000f, 0.791543f, 0.628050f), // 5000 K
GfVec3f(1.000000f, 0.848462f, 0.753228f), // 5500 K
GfVec3f(1.000000f, 0.898581f, 0.874905f), // 6000 K
GfVec3f(1.000000f, 0.942771f, 0.991642f), // 6500 K
GfVec3f(0.906947f, 0.890456f, 1.000000f), // 7000 K
GfVec3f(0.828247f, 0.841838f, 1.000000f), // 7500 K
GfVec3f(0.765791f, 0.801896f, 1.000000f), // 8000 K
GfVec3f(0.715255f, 0.768579f, 1.000000f), // 8500 K
GfVec3f(0.673683f, 0.740423f, 1.000000f), // 9000 K
GfVec3f(0.638992f, 0.716359f, 1.000000f), // 9500 K
GfVec3f(0.609681f, 0.695588f, 1.000000f), // 10000 K
GfVec3f(0.609681f, 0.695588f, 1.000000f), // 10000 K
GfVec3f(0.609681f, 0.695588f, 1.000000f) // 10000 K
};
// Catmull-Rom basis
static const float _basis[4][4] = {
{ -0.5f, 1.5f, -1.5f, 0.5f }, { 1.f, -2.5f, 2.0f, -0.5f }, { -0.5f, 0.0f, 0.5f, 0.0f }, { 0.f, 1.0f, 0.0f, 0.0f }
};
static inline float _Rec709RgbToLuma(const GfVec3f& rgb)
{
return GfDot(rgb, GfVec3f(0.2126f, 0.7152f, 0.0722f));
}
static GfVec3f _BlackbodyTemperatureAsRgb(float temp)
{
// Catmull-Rom interpolation of _blackbodyRGB
constexpr int numKnots = sizeof(_blackbodyRGB) / sizeof(_blackbodyRGB[0]);
// Parametric distance along spline
const float u_spline = GfClamp((temp - 1000.0f) / 9000.0f, 0.0f, 1.0f);
// Last 4 knots represent a trailing segment starting at u_spline==1.0,
// to simplify boundary behavior
constexpr int numSegs = (numKnots - 4);
const float x = u_spline * numSegs;
const int seg = int(floor(x));
const float u_seg = x - seg; // Parameter within segment
// Knot values for this segment
GfVec3f k0 = _blackbodyRGB[seg + 0];
GfVec3f k1 = _blackbodyRGB[seg + 1];
GfVec3f k2 = _blackbodyRGB[seg + 2];
GfVec3f k3 = _blackbodyRGB[seg + 3];
// Compute cubic coefficients. Could fold constants (zero, one) here
// if speed is a concern.
GfVec3f a = _basis[0][0] * k0 + _basis[0][1] * k1 + _basis[0][2] * k2 + _basis[0][3] * k3;
GfVec3f b = _basis[1][0] * k0 + _basis[1][1] * k1 + _basis[1][2] * k2 + _basis[1][3] * k3;
GfVec3f c = _basis[2][0] * k0 + _basis[2][1] * k1 + _basis[2][2] * k2 + _basis[2][3] * k3;
GfVec3f d = _basis[3][0] * k0 + _basis[3][1] * k1 + _basis[3][2] * k2 + _basis[3][3] * k3;
// Eval cubic polynomial.
GfVec3f rgb = ((a * u_seg + b) * u_seg + c) * u_seg + d;
// Normalize to the same luminance as (1,1,1)
rgb /= _Rec709RgbToLuma(rgb);
// Clamp at zero, since the spline can produce small negative values,
// e.g. in the blue component at 1300k.
rgb[0] = GfMax(rgb[0], 0.f);
rgb[1] = GfMax(rgb[1], 0.f);
rgb[2] = GfMax(rgb[2], 0.f);
return rgb;
}
HdStrelkaLight::HdStrelkaLight(const SdfPath& id, TfToken const& lightType) : HdLight(id), mLightType(lightType)
{
}
HdStrelkaLight::~HdStrelkaLight()
{
}
void HdStrelkaLight::Sync(HdSceneDelegate* sceneDelegate, HdRenderParam* renderParam, HdDirtyBits* dirtyBits)
{
TF_UNUSED(renderParam);
bool pullLight = (*dirtyBits & DirtyBits::DirtyParams);
*dirtyBits = DirtyBits::Clean;
if (!pullLight)
{
return;
}
const SdfPath& id = GetId();
// const VtValue& resource = sceneDelegate->GetMaterialResource(id);
// Get the color of the light
GfVec3f hdc = sceneDelegate->GetLightParamValue(id, HdLightTokens->color).Get<GfVec3f>();
// Color temperature
VtValue enableColorTemperatureVal = sceneDelegate->GetLightParamValue(id, HdLightTokens->enableColorTemperature);
if (enableColorTemperatureVal.GetWithDefault<bool>(false))
{
VtValue colorTemperatureVal = sceneDelegate->GetLightParamValue(id, HdLightTokens->colorTemperature);
if (colorTemperatureVal.IsHolding<float>())
{
float colorTemperature = colorTemperatureVal.Get<float>();
hdc = GfCompMult(hdc, _BlackbodyTemperatureAsRgb(colorTemperature));
}
}
// Intensity
float intensity = sceneDelegate->GetLightParamValue(id, HdLightTokens->intensity).Get<float>();
// Exposure
float exposure = sceneDelegate->GetLightParamValue(id, HdLightTokens->exposure).Get<float>();
intensity *= powf(2.0f, GfClamp(exposure, -50.0f, 50.0f));
// Transform
{
GfMatrix4d transform = sceneDelegate->GetTransform(id);
glm::float4x4 xform;
for (int i = 0; i < 4; ++i)
{
for (int j = 0; j < 4; ++j)
{
xform[i][j] = (float)transform[i][j];
}
}
mLightDesc.xform = xform;
mLightDesc.useXform = true;
}
mLightDesc.color = glm::float3(hdc[0], hdc[1], hdc[2]);
mLightDesc.intensity = intensity;
if (mLightType == HdPrimTypeTokens->rectLight)
{
mLightDesc.type = 0;
float width = 0.0f;
float height = 0.0f;
VtValue widthVal = sceneDelegate->GetLightParamValue(id, HdLightTokens->width);
if (widthVal.IsHolding<float>())
{
width = widthVal.Get<float>();
}
VtValue heightVal = sceneDelegate->GetLightParamValue(id, HdLightTokens->height);
if (heightVal.IsHolding<float>())
{
height = heightVal.Get<float>();
}
mLightDesc.height = height;
mLightDesc.width = width;
}
else if (mLightType == HdPrimTypeTokens->diskLight || mLightType == HdPrimTypeTokens->sphereLight)
{
mLightDesc.type = mLightType == HdPrimTypeTokens->diskLight ? 1 : 2;
float radius = 0.0;
VtValue radiusVal = sceneDelegate->GetLightParamValue(id, HdLightTokens->radius);
if (radiusVal.IsHolding<float>())
{
radius = radiusVal.Get<float>();
}
mLightDesc.radius = radius * mLightDesc.xform[0][0]; // uniform scale
}
else if (mLightType == HdPrimTypeTokens->distantLight)
{
float angle = 0.0f;
mLightDesc.type = 3; // TODO: move to enum
VtValue angleVal = sceneDelegate->GetLightParamValue(id, HdLightTokens->angle);
if (angleVal.IsHolding<float>())
{
angle = angleVal.Get<float>();
}
mLightDesc.halfAngle = angle * 0.5f * (M_PI / 180.0f);
mLightDesc.intensity /= M_PI * powf(sin(mLightDesc.halfAngle), 2.0f);
}
}
HdDirtyBits HdStrelkaLight::GetInitialDirtyBitsMask() const
{
return (DirtyParams | DirtyTransform);
}
oka::Scene::UniformLightDesc HdStrelkaLight::getLightDesc()
{
return mLightDesc;
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/MdlParserPlugin.cpp | // Copyright (C) 2021 Pablo Delgado Krämer
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <https://www.gnu.org/licenses/>.
#include "MdlParserPlugin.h"
#include <pxr/base/tf/staticTokens.h>
#include <pxr/usd/sdr/shaderNode.h>
#include <pxr/usd/ar/resolver.h>
#include "pxr/usd/ar/resolvedPath.h"
#include "pxr/usd/ar/asset.h"
#include <pxr/usd/ar/ar.h>
//#include "Tokens.h"
PXR_NAMESPACE_OPEN_SCOPE
NDR_REGISTER_PARSER_PLUGIN(HdStrelkaMdlParserPlugin);
// clang-format off
TF_DEFINE_PRIVATE_TOKENS(_tokens,
(mdl)
(subIdentifier));
// clang-format on
NdrNodeUniquePtr HdStrelkaMdlParserPlugin::Parse(const NdrNodeDiscoveryResult& discoveryResult)
{
NdrTokenMap metadata = discoveryResult.metadata;
metadata[_tokens->subIdentifier] = discoveryResult.subIdentifier;
return std::make_unique<SdrShaderNode>(discoveryResult.identifier, discoveryResult.version, discoveryResult.name,
discoveryResult.family, _tokens->mdl, discoveryResult.sourceType,
discoveryResult.uri, discoveryResult.resolvedUri, NdrPropertyUniquePtrVec{},
metadata);
}
const NdrTokenVec& HdStrelkaMdlParserPlugin::GetDiscoveryTypes() const
{
static NdrTokenVec s_discoveryTypes{ _tokens->mdl };
return s_discoveryTypes;
}
const TfToken& HdStrelkaMdlParserPlugin::GetSourceType() const
{
return _tokens->mdl;
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Instancer.cpp | // Copyright (C) 2021 Pablo Delgado Krämer
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <https://www.gnu.org/licenses/>.
#include "Instancer.h"
#include <pxr/base/gf/quatd.h>
#include <pxr/imaging/hd/sceneDelegate.h>
PXR_NAMESPACE_OPEN_SCOPE
HdStrelkaInstancer::HdStrelkaInstancer(HdSceneDelegate* delegate,
const SdfPath& id)
: HdInstancer(delegate, id)
{
}
HdStrelkaInstancer::~HdStrelkaInstancer()
{
}
void HdStrelkaInstancer::Sync(HdSceneDelegate* sceneDelegate,
HdRenderParam* renderParam,
HdDirtyBits* dirtyBits)
{
TF_UNUSED(renderParam);
_UpdateInstancer(sceneDelegate, dirtyBits);
const SdfPath& id = GetId();
if (!HdChangeTracker::IsAnyPrimvarDirty(*dirtyBits, id))
{
return;
}
const HdPrimvarDescriptorVector& primvars = sceneDelegate->GetPrimvarDescriptors(id, HdInterpolation::HdInterpolationInstance);
for (const HdPrimvarDescriptor& primvar : primvars)
{
TfToken primName = primvar.name;
if (primName != HdInstancerTokens->translate &&
primName != HdInstancerTokens->rotate &&
primName != HdInstancerTokens->scale &&
primName != HdInstancerTokens->instanceTransform)
{
continue;
}
if (!HdChangeTracker::IsPrimvarDirty(*dirtyBits, id, primName))
{
continue;
}
VtValue value = sceneDelegate->Get(id, primName);
m_primvarMap[primName] = value;
}
}
VtMatrix4dArray HdStrelkaInstancer::ComputeInstanceTransforms(const SdfPath& prototypeId)
{
HdSceneDelegate* sceneDelegate = GetDelegate();
const SdfPath& id = GetId();
// Calculate instance transforms for this instancer.
VtValue boxedTranslates = m_primvarMap[HdInstancerTokens->translate];
VtValue boxedRotates = m_primvarMap[HdInstancerTokens->rotate];
VtValue boxedScales = m_primvarMap[HdInstancerTokens->scale];
VtValue boxedInstanceTransforms = m_primvarMap[HdInstancerTokens->instanceTransform];
VtVec3fArray translates;
if (boxedTranslates.IsHolding<VtVec3fArray>())
{
translates = boxedTranslates.UncheckedGet<VtVec3fArray>();
}
else if (!boxedTranslates.IsEmpty())
{
TF_CODING_WARNING("Instancer translate values are not of type Vec3f!");
}
VtVec4fArray rotates;
if (boxedRotates.IsHolding<VtVec4fArray>())
{
rotates = boxedRotates.Get<VtVec4fArray>();
}
else if (!boxedRotates.IsEmpty())
{
TF_CODING_WARNING("Instancer rotate values are not of type Vec3f!");
}
VtVec3fArray scales;
if (boxedScales.IsHolding<VtVec3fArray>())
{
scales = boxedScales.Get<VtVec3fArray>();
}
else if (!boxedScales.IsEmpty())
{
TF_CODING_WARNING("Instancer scale values are not of type Vec3f!");
}
VtMatrix4dArray instanceTransforms;
if (boxedInstanceTransforms.IsHolding<VtMatrix4dArray>())
{
instanceTransforms = boxedInstanceTransforms.Get<VtMatrix4dArray>();
}
GfMatrix4d instancerTransform = sceneDelegate->GetInstancerTransform(id);
const VtIntArray& instanceIndices = sceneDelegate->GetInstanceIndices(id, prototypeId);
VtMatrix4dArray transforms;
transforms.resize(instanceIndices.size());
for (size_t i = 0; i < instanceIndices.size(); i++)
{
int instanceIndex = instanceIndices[i];
GfMatrix4d mat = instancerTransform;
GfMatrix4d temp;
if (i < translates.size())
{
auto trans = GfVec3d(translates[instanceIndex]);
temp.SetTranslate(trans);
mat = temp * mat;
}
if (i < rotates.size())
{
GfVec4f rot = rotates[instanceIndex];
temp.SetRotate(GfQuatd(rot[0], rot[1], rot[2], rot[3]));
mat = temp * mat;
}
if (i < scales.size())
{
auto scale = GfVec3d(scales[instanceIndex]);
temp.SetScale(scale);
mat = temp * mat;
}
if (i < instanceTransforms.size())
{
temp = instanceTransforms[instanceIndex];
mat = temp * mat;
}
transforms[i] = mat;
}
// Calculate instance transforms for all instancer instances.
const SdfPath& parentId = GetParentId();
if (parentId.IsEmpty())
{
return transforms;
}
const HdRenderIndex& renderIndex = sceneDelegate->GetRenderIndex();
HdInstancer* boxedParentInstancer = renderIndex.GetInstancer(parentId);
HdStrelkaInstancer* parentInstancer = dynamic_cast<HdStrelkaInstancer*>(boxedParentInstancer);
VtMatrix4dArray parentTransforms = parentInstancer->ComputeInstanceTransforms(id);
VtMatrix4dArray transformProducts;
transformProducts.resize(parentTransforms.size() * transforms.size());
for (size_t i = 0; i < parentTransforms.size(); i++)
{
for (size_t j = 0; j < transforms.size(); j++)
{
size_t index = i * transforms.size() + j;
transformProducts[index] = transforms[j] * parentTransforms[i];
}
}
return transformProducts;
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/RenderDelegate.h | #pragma once
#include <pxr/imaging/hd/renderDelegate.h>
#include "MaterialNetworkTranslator.h"
#include <render/common.h>
#include <scene/scene.h>
#include <render/render.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaRenderDelegate final : public HdRenderDelegate
{
public:
HdStrelkaRenderDelegate(const HdRenderSettingsMap& settingsMap, const MaterialNetworkTranslator& translator);
~HdStrelkaRenderDelegate() override;
void SetDrivers(HdDriverVector const& drivers) override;
HdRenderSettingDescriptorList GetRenderSettingDescriptors() const override;
HdRenderPassSharedPtr CreateRenderPass(HdRenderIndex* index, const HdRprimCollection& collection) override;
HdResourceRegistrySharedPtr GetResourceRegistry() const override;
void CommitResources(HdChangeTracker* tracker) override;
HdInstancer* CreateInstancer(HdSceneDelegate* delegate, const SdfPath& id) override;
void DestroyInstancer(HdInstancer* instancer) override;
HdAovDescriptor GetDefaultAovDescriptor(const TfToken& name) const override;
/* Rprim */
const TfTokenVector& GetSupportedRprimTypes() const override;
HdRprim* CreateRprim(const TfToken& typeId, const SdfPath& rprimId) override;
void DestroyRprim(HdRprim* rPrim) override;
/* Sprim */
const TfTokenVector& GetSupportedSprimTypes() const override;
HdSprim* CreateSprim(const TfToken& typeId, const SdfPath& sprimId) override;
HdSprim* CreateFallbackSprim(const TfToken& typeId) override;
void DestroySprim(HdSprim* sprim) override;
/* Bprim */
const TfTokenVector& GetSupportedBprimTypes() const override;
HdBprim* CreateBprim(const TfToken& typeId, const SdfPath& bprimId) override;
HdBprim* CreateFallbackBprim(const TfToken& typeId) override;
void DestroyBprim(HdBprim* bprim) override;
TfToken GetMaterialBindingPurpose() const override;
// In a USD file, there can be multiple networks associated with a material:
// token outputs:mdl:surface.connect = </Root/Glass.outputs:out>
// token outputs:surface.connect = </Root/GlassPreviewSurface.outputs:surface>
// This function returns the order of preference used when selecting one for rendering.
TfTokenVector GetMaterialRenderContexts() const override;
TfTokenVector GetShaderSourceTypes() const override;
oka::SharedContext& getSharedContext();
private:
const MaterialNetworkTranslator& m_translator;
HdRenderSettingDescriptorList m_settingDescriptors;
HdResourceRegistrySharedPtr m_resourceRegistry;
const TfTokenVector SUPPORTED_BPRIM_TYPES = { HdPrimTypeTokens->renderBuffer };
const TfTokenVector SUPPORTED_RPRIM_TYPES = { HdPrimTypeTokens->mesh, HdPrimTypeTokens->basisCurves };
const TfTokenVector SUPPORTED_SPRIM_TYPES = {
HdPrimTypeTokens->camera, HdPrimTypeTokens->material, HdPrimTypeTokens->light,
HdPrimTypeTokens->rectLight, HdPrimTypeTokens->diskLight, HdPrimTypeTokens->sphereLight,
HdPrimTypeTokens->distantLight,
};
oka::SharedContext* mSharedCtx;
oka::Scene mScene;
oka::Render* mRenderer;
};
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/RenderDelegate.cpp | #include "RenderDelegate.h"
#include "Camera.h"
#include "Instancer.h"
#include "Light.h"
#include "Material.h"
#include "Mesh.h"
#include "BasisCurves.h"
#include "RenderBuffer.h"
#include "RenderPass.h"
#include "Tokens.h"
#include <pxr/base/gf/vec4f.h>
#include <pxr/imaging/hd/resourceRegistry.h>
#include <log.h>
#include <memory>
PXR_NAMESPACE_OPEN_SCOPE
TF_DEFINE_PRIVATE_TOKENS(_Tokens, (HdStrelkaDriver));
HdStrelkaRenderDelegate::HdStrelkaRenderDelegate(const HdRenderSettingsMap& settingsMap,
const MaterialNetworkTranslator& translator)
: m_translator(translator)
{
m_resourceRegistry = std::make_shared<HdResourceRegistry>();
m_settingDescriptors.push_back(
HdRenderSettingDescriptor{ "Samples per pixel", HdStrelkaSettingsTokens->spp, VtValue{ 8 } });
m_settingDescriptors.push_back(
HdRenderSettingDescriptor{ "Max bounces", HdStrelkaSettingsTokens->max_bounces, VtValue{ 4 } });
_PopulateDefaultSettings(m_settingDescriptors);
for (const auto& setting : settingsMap)
{
const TfToken& key = setting.first;
const VtValue& value = setting.second;
_settingsMap[key] = value;
}
oka::RenderType type = oka::RenderType::eOptiX;
#ifdef __APPLE__
type = oka::RenderType::eMetal;
#endif
mRenderer = oka::RenderFactory::createRender(type);
mRenderer->setScene(&mScene);
}
HdStrelkaRenderDelegate::~HdStrelkaRenderDelegate()
{
}
void HdStrelkaRenderDelegate::SetDrivers(HdDriverVector const& drivers)
{
for (HdDriver* hdDriver : drivers)
{
if (hdDriver->name == _Tokens->HdStrelkaDriver && hdDriver->driver.IsHolding<oka::SharedContext*>())
{
assert(mRenderer);
mSharedCtx = hdDriver->driver.UncheckedGet<oka::SharedContext*>();
mRenderer->setSharedContext(mSharedCtx);
mRenderer->init();
mSharedCtx->mRender = mRenderer;
break;
}
}
}
HdRenderSettingDescriptorList HdStrelkaRenderDelegate::GetRenderSettingDescriptors() const
{
return m_settingDescriptors;
}
HdRenderPassSharedPtr HdStrelkaRenderDelegate::CreateRenderPass(HdRenderIndex* index, const HdRprimCollection& collection)
{
return HdRenderPassSharedPtr(new HdStrelkaRenderPass(index, collection, _settingsMap, mRenderer, &mScene));
}
HdResourceRegistrySharedPtr HdStrelkaRenderDelegate::GetResourceRegistry() const
{
return m_resourceRegistry;
}
void HdStrelkaRenderDelegate::CommitResources(HdChangeTracker* tracker)
{
TF_UNUSED(tracker);
// We delay BVH building and GPU uploads to the next render call.
}
HdInstancer* HdStrelkaRenderDelegate::CreateInstancer(HdSceneDelegate* delegate, const SdfPath& id)
{
return new HdStrelkaInstancer(delegate, id);
}
void HdStrelkaRenderDelegate::DestroyInstancer(HdInstancer* instancer)
{
delete instancer;
}
HdAovDescriptor HdStrelkaRenderDelegate::GetDefaultAovDescriptor(const TfToken& name) const
{
TF_UNUSED(name);
HdAovDescriptor aovDescriptor;
aovDescriptor.format = HdFormatFloat32Vec4;
aovDescriptor.multiSampled = false;
aovDescriptor.clearValue = GfVec4f(0.0f, 0.0f, 0.0f, 0.0f);
return aovDescriptor;
}
const TfTokenVector& HdStrelkaRenderDelegate::GetSupportedRprimTypes() const
{
return SUPPORTED_RPRIM_TYPES;
}
HdRprim* HdStrelkaRenderDelegate::CreateRprim(const TfToken& typeId, const SdfPath& rprimId)
{
if (typeId == HdPrimTypeTokens->mesh)
{
return new HdStrelkaMesh(rprimId, &mScene);
}
else if (typeId == HdPrimTypeTokens->basisCurves)
{
return new HdStrelkaBasisCurves(rprimId, &mScene);
}
STRELKA_ERROR("Unknown Rprim Type {}", typeId.GetText());
return nullptr;
}
void HdStrelkaRenderDelegate::DestroyRprim(HdRprim* rprim)
{
delete rprim;
}
const TfTokenVector& HdStrelkaRenderDelegate::GetSupportedSprimTypes() const
{
return SUPPORTED_SPRIM_TYPES;
}
HdSprim* HdStrelkaRenderDelegate::CreateSprim(const TfToken& typeId, const SdfPath& sprimId)
{
STRELKA_DEBUG("CreateSprim Type: {}", typeId.GetText());
if (sprimId.IsEmpty())
{
STRELKA_DEBUG("skipping creation of empty sprim path");
return nullptr;
}
HdSprim* res = nullptr;
if (typeId == HdPrimTypeTokens->camera)
{
res = new HdStrelkaCamera(sprimId, mScene);
}
else if (typeId == HdPrimTypeTokens->material)
{
res = new HdStrelkaMaterial(sprimId, m_translator);
}
else if (typeId == HdPrimTypeTokens->rectLight || typeId == HdPrimTypeTokens->diskLight ||
typeId == HdPrimTypeTokens->sphereLight || typeId == HdPrimTypeTokens->distantLight)
{
res = new HdStrelkaLight(sprimId, typeId);
}
else
{
STRELKA_ERROR("Unknown Sprim Type {}", typeId.GetText());
}
return res;
}
HdSprim* HdStrelkaRenderDelegate::CreateFallbackSprim(const TfToken& typeId)
{
const SdfPath& sprimId = SdfPath::EmptyPath();
return CreateSprim(typeId, sprimId);
}
void HdStrelkaRenderDelegate::DestroySprim(HdSprim* sprim)
{
delete sprim;
}
const TfTokenVector& HdStrelkaRenderDelegate::GetSupportedBprimTypes() const
{
return SUPPORTED_BPRIM_TYPES;
}
HdBprim* HdStrelkaRenderDelegate::CreateBprim(const TfToken& typeId, const SdfPath& bprimId)
{
if (typeId == HdPrimTypeTokens->renderBuffer)
{
return new HdStrelkaRenderBuffer(bprimId, mSharedCtx);
}
return nullptr;
}
HdBprim* HdStrelkaRenderDelegate::CreateFallbackBprim(const TfToken& typeId)
{
const SdfPath& bprimId = SdfPath::EmptyPath();
return CreateBprim(typeId, bprimId);
}
void HdStrelkaRenderDelegate::DestroyBprim(HdBprim* bprim)
{
delete bprim;
}
TfToken HdStrelkaRenderDelegate::GetMaterialBindingPurpose() const
{
//return HdTokens->full;
return HdTokens->preview;
}
TfTokenVector HdStrelkaRenderDelegate::GetMaterialRenderContexts() const
{
return TfTokenVector{ HdStrelkaRenderContexts->mtlx, HdStrelkaRenderContexts->mdl };
}
TfTokenVector HdStrelkaRenderDelegate::GetShaderSourceTypes() const
{
return TfTokenVector{ HdStrelkaSourceTypes->mtlx, HdStrelkaSourceTypes->mdl };
}
oka::SharedContext& HdStrelkaRenderDelegate::getSharedContext()
{
return mRenderer->getSharedContext();
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/BasisCurves.cpp | #include "BasisCurves.h"
#include <log.h>
PXR_NAMESPACE_OPEN_SCOPE
void HdStrelkaBasisCurves::Sync(HdSceneDelegate* sceneDelegate,
HdRenderParam* renderParam,
HdDirtyBits* dirtyBits,
const TfToken& reprToken)
{
TF_UNUSED(renderParam);
TF_UNUSED(reprToken);
HdRenderIndex& renderIndex = sceneDelegate->GetRenderIndex();
const SdfPath& id = GetId();
mName = id.GetText();
STRELKA_INFO("Curve Name: {}", mName.c_str());
if (*dirtyBits & HdChangeTracker::DirtyMaterialId)
{
const SdfPath& materialId = sceneDelegate->GetMaterialId(id);
SetMaterialId(materialId);
}
if (*dirtyBits & HdChangeTracker::DirtyTopology)
{
mTopology = sceneDelegate->GetBasisCurvesTopology(id);
}
if (*dirtyBits & HdChangeTracker::DirtyTransform)
{
m_prototypeTransform = sceneDelegate->GetTransform(id);
}
bool updateGeometry = (*dirtyBits & HdChangeTracker::DirtyPoints) | (*dirtyBits & HdChangeTracker::DirtyNormals) |
(*dirtyBits & HdChangeTracker::DirtyTopology);
*dirtyBits = HdChangeTracker::Clean;
if (!updateGeometry)
{
return;
}
// m_faces.clear();
mPoints.clear();
mNormals.clear();
_UpdateGeometry(sceneDelegate);
}
bool HdStrelkaBasisCurves::_FindPrimvar(HdSceneDelegate* sceneDelegate,
const TfToken& primvarName,
HdInterpolation& interpolation) const
{
HdInterpolation interpolations[] = {
HdInterpolation::HdInterpolationVertex, HdInterpolation::HdInterpolationFaceVarying,
HdInterpolation::HdInterpolationConstant, HdInterpolation::HdInterpolationUniform,
HdInterpolation::HdInterpolationVarying, HdInterpolation::HdInterpolationInstance
};
for (HdInterpolation i : interpolations)
{
const auto& primvarDescs = GetPrimvarDescriptors(sceneDelegate, i);
for (const HdPrimvarDescriptor& primvar : primvarDescs)
{
if (primvar.name == primvarName)
{
interpolation = i;
return true;
}
}
}
return false;
}
void HdStrelkaBasisCurves::_PullPrimvars(HdSceneDelegate* sceneDelegate,
VtVec3fArray& points,
VtVec3fArray& normals,
VtFloatArray& widths,
bool& indexedNormals,
bool& indexedUVs,
GfVec3f& color,
bool& hasColor) const
{
const SdfPath& id = GetId();
// Handle points.
HdInterpolation pointInterpolation;
bool foundPoints = _FindPrimvar(sceneDelegate, HdTokens->points, pointInterpolation);
if (!foundPoints)
{
STRELKA_ERROR("Points primvar not found!");
return;
}
else if (pointInterpolation != HdInterpolation::HdInterpolationVertex)
{
STRELKA_ERROR("Points primvar is not vertex-interpolated!");
return;
}
VtValue boxedPoints = sceneDelegate->Get(id, HdTokens->points);
points = boxedPoints.Get<VtVec3fArray>();
// Handle color.
HdInterpolation colorInterpolation;
bool foundColor = _FindPrimvar(sceneDelegate, HdTokens->displayColor, colorInterpolation);
if (foundColor && colorInterpolation == HdInterpolation::HdInterpolationConstant)
{
VtValue boxedColors = sceneDelegate->Get(id, HdTokens->displayColor);
const VtVec3fArray& colors = boxedColors.Get<VtVec3fArray>();
color = colors[0];
hasColor = true;
}
HdBasisCurvesTopology topology = GetBasisCurvesTopology(sceneDelegate);
VtIntArray curveVertexCounts = topology.GetCurveVertexCounts();
// Handle normals.
HdInterpolation normalInterpolation;
bool foundNormals = _FindPrimvar(sceneDelegate, HdTokens->normals, normalInterpolation);
if (foundNormals && normalInterpolation == HdInterpolation::HdInterpolationVarying)
{
VtValue boxedNormals = sceneDelegate->Get(id, HdTokens->normals);
normals = boxedNormals.Get<VtVec3fArray>();
indexedNormals = true;
}
// Handle width.
HdInterpolation widthInterpolation;
bool foundWidth = _FindPrimvar(sceneDelegate, HdTokens->widths, widthInterpolation);
if (foundWidth)
{
VtValue boxedWidths = sceneDelegate->Get(id, HdTokens->widths);
widths = boxedWidths.Get<VtFloatArray>();
}
}
void HdStrelkaBasisCurves::_UpdateGeometry(HdSceneDelegate* sceneDelegate)
{
const HdBasisCurvesTopology& topology = mTopology;
const SdfPath& id = GetId();
// Get USD Curve Metadata
mVertexCounts = topology.GetCurveVertexCounts();
TfToken curveType = topology.GetCurveType();
TfToken curveBasis = topology.GetCurveBasis();
TfToken curveWrap = topology.GetCurveWrap();
size_t num_curves = mVertexCounts.size();
size_t num_keys = 0;
bool indexedNormals;
bool indexedUVs;
bool hasColor = true;
_PullPrimvars(sceneDelegate, mPoints, mNormals, mWidths, indexedNormals, indexedUVs, mColor, hasColor);
_ConvertCurve();
}
HdStrelkaBasisCurves::HdStrelkaBasisCurves(const SdfPath& id, oka::Scene* scene) : HdBasisCurves(id), mScene(scene)
{
}
HdStrelkaBasisCurves::~HdStrelkaBasisCurves()
{
}
HdDirtyBits HdStrelkaBasisCurves::GetInitialDirtyBitsMask() const
{
return HdChangeTracker::DirtyPoints | HdChangeTracker::DirtyNormals | HdChangeTracker::DirtyTopology |
HdChangeTracker::DirtyInstancer | HdChangeTracker::DirtyInstanceIndex | HdChangeTracker::DirtyTransform |
HdChangeTracker::DirtyMaterialId | HdChangeTracker::DirtyPrimvar;
}
HdDirtyBits HdStrelkaBasisCurves::_PropagateDirtyBits(HdDirtyBits bits) const
{
return bits;
}
void HdStrelkaBasisCurves::_InitRepr(const TfToken& reprName, HdDirtyBits* dirtyBits)
{
TF_UNUSED(reprName);
TF_UNUSED(dirtyBits);
}
void HdStrelkaBasisCurves::_ConvertCurve()
{
// calculate phantom points
// https://raytracing-docs.nvidia.com/optix7/guide/index.html#curves#differences-between-curves-spheres-and-triangles
glm::float3 p1 = glm::float3(mPoints[0][0], mPoints[0][1], mPoints[0][2]);
glm::float3 p2 = glm::float3(mPoints[1][0], mPoints[1][1], mPoints[1][2]);
glm::float3 p0 = p1 + (p1 - p2);
mCurvePoints.push_back(p0);
for (const GfVec3f& p : mPoints)
{
mCurvePoints.push_back(glm::float3(p[0], p[1], p[2]));
}
int n = mPoints.size() - 1;
glm::float3 pn = glm::float3(mPoints[n][0], mPoints[n][1], mPoints[n][2]);
glm::float3 pn1 = glm::float3(mPoints[n - 1][0], mPoints[n - 1][1], mPoints[n - 1][2]);
glm::float3 pnn = pn + (pn - pn1);
mCurvePoints.push_back(pnn);
mCurveWidths.push_back(mWidths[0] * 0.5);
assert((mWidths.size() == mPoints.size()) || (mWidths.size() == 1));
if (mWidths.size() == 1)
{
for (int i = 0; i < mPoints.size(); ++i)
{
mCurveWidths.push_back(mWidths[0] * 0.5);
}
}
else
{
for (const float w : mWidths)
{
mCurveWidths.push_back(w * 0.5f);
}
}
mCurveWidths.push_back(mCurveWidths.back());
for (const int i : mVertexCounts)
{
mCurveVertexCounts.push_back(i);
}
}
const std::vector<glm::float3>& HdStrelkaBasisCurves::GetPoints() const
{
return mCurvePoints;
}
const std::vector<float>& HdStrelkaBasisCurves::GetWidths() const
{
return mCurveWidths;
}
const std::vector<uint32_t>& HdStrelkaBasisCurves::GetVertexCounts() const
{
return mCurveVertexCounts;
}
const GfMatrix4d& HdStrelkaBasisCurves::GetPrototypeTransform() const
{
return m_prototypeTransform;
}
const char* HdStrelkaBasisCurves::getName() const
{
return mName.c_str();
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/RenderBuffer.cpp | #include "RenderBuffer.h"
#include "render.h"
#include <pxr/base/gf/vec3i.h>
PXR_NAMESPACE_OPEN_SCOPE
HdStrelkaRenderBuffer::HdStrelkaRenderBuffer(const SdfPath& id, oka::SharedContext* ctx) : HdRenderBuffer(id), mCtx(ctx)
{
m_isMapped = false;
m_isConverged = false;
m_bufferMem = nullptr;
}
HdStrelkaRenderBuffer::~HdStrelkaRenderBuffer()
{
_Deallocate();
}
bool HdStrelkaRenderBuffer::Allocate(const GfVec3i& dimensions, HdFormat format, bool multiSampled)
{
if (dimensions[2] != 1)
{
return false;
}
m_width = dimensions[0];
m_height = dimensions[1];
m_format = format;
m_isMultiSampled = multiSampled;
size_t size = m_width * m_height * HdDataSizeOfFormat(m_format);
m_bufferMem = realloc(m_bufferMem, size);
if (!m_bufferMem)
{
return false;
}
if (mResult)
{
mResult->resize(m_width, m_height);
}
else
{
oka::BufferDesc desc{};
desc.format = oka::BufferFormat::FLOAT4;
desc.width = m_width;
desc.height = m_height;
mResult = mCtx->mRender->createBuffer(desc);
}
if (!mResult)
{
return false;
}
return true;
}
unsigned int HdStrelkaRenderBuffer::GetWidth() const
{
return m_width;
}
unsigned int HdStrelkaRenderBuffer::GetHeight() const
{
return m_height;
}
unsigned int HdStrelkaRenderBuffer::GetDepth() const
{
return 1u;
}
HdFormat HdStrelkaRenderBuffer::GetFormat() const
{
return m_format;
}
bool HdStrelkaRenderBuffer::IsMultiSampled() const
{
return m_isMultiSampled;
}
VtValue HdStrelkaRenderBuffer::GetResource(bool multiSampled) const
{
return VtValue((uint8_t*)mResult);
}
bool HdStrelkaRenderBuffer::IsConverged() const
{
return m_isConverged;
}
void HdStrelkaRenderBuffer::SetConverged(bool converged)
{
m_isConverged = converged;
}
void* HdStrelkaRenderBuffer::Map()
{
m_isMapped = true;
return m_bufferMem;
}
bool HdStrelkaRenderBuffer::IsMapped() const
{
return m_isMapped;
}
void HdStrelkaRenderBuffer::Unmap()
{
m_isMapped = false;
}
void HdStrelkaRenderBuffer::Resolve()
{
}
void HdStrelkaRenderBuffer::_Deallocate()
{
free(m_bufferMem);
delete mResult;
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Tokens.h | #pragma once
#include <pxr/base/tf/staticTokens.h>
PXR_NAMESPACE_OPEN_SCOPE
#define HD_STRELKA_SETTINGS_TOKENS \
((spp, "spp"))((max_bounces, "max-bounces"))
// mtlx node identifier is given by usdMtlx.
#define HD_STRELKA_NODE_IDENTIFIER_TOKENS \
(mtlx)(mdl)
#define HD_STRELKA_SOURCE_TYPE_TOKENS \
(mtlx)(mdl)
#define HD_STRELKA_DISCOVERY_TYPE_TOKENS \
(mtlx)(mdl)
#define HD_STRELKA_RENDER_CONTEXT_TOKENS \
(mtlx)(mdl)
#define HD_STRELKA_NODE_CONTEXT_TOKENS \
(mtlx)(mdl)
#define HD_STRELKA_NODE_METADATA_TOKENS \
(subIdentifier)
TF_DECLARE_PUBLIC_TOKENS(HdStrelkaSettingsTokens, HD_STRELKA_SETTINGS_TOKENS);
TF_DECLARE_PUBLIC_TOKENS(HdStrelkaNodeIdentifiers, HD_STRELKA_NODE_IDENTIFIER_TOKENS);
TF_DECLARE_PUBLIC_TOKENS(HdStrelkaSourceTypes, HD_STRELKA_SOURCE_TYPE_TOKENS);
TF_DECLARE_PUBLIC_TOKENS(HdStrelkaDiscoveryTypes, HD_STRELKA_DISCOVERY_TYPE_TOKENS);
TF_DECLARE_PUBLIC_TOKENS(HdStrelkaRenderContexts, HD_STRELKA_RENDER_CONTEXT_TOKENS);
TF_DECLARE_PUBLIC_TOKENS(HdStrelkaNodeContexts, HD_STRELKA_NODE_CONTEXT_TOKENS);
TF_DECLARE_PUBLIC_TOKENS(HdStrelkaNodeMetadata, HD_STRELKA_NODE_METADATA_TOKENS);
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Camera.h | #pragma once
#include <pxr/imaging/hd/camera.h>
#include <scene/scene.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaCamera final : public HdCamera
{
public:
HdStrelkaCamera(const SdfPath& id, oka::Scene& scene);
~HdStrelkaCamera() override;
public:
float GetVFov() const;
uint32_t GetCameraIndex() const;
public:
void Sync(HdSceneDelegate* sceneDelegate,
HdRenderParam* renderParam,
HdDirtyBits* dirtyBits) override;
HdDirtyBits GetInitialDirtyBitsMask() const override;
private:
oka::Camera _ConstructStrelkaCamera();
float m_vfov;
oka::Scene& mScene;
uint32_t mCameraIndex = -1;
};
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/MdlDiscoveryPlugin.cpp | #include "MdlDiscoveryPlugin.h"
#include <pxr/base/tf/staticTokens.h>
//#include "Tokens.h"
PXR_NAMESPACE_OPEN_SCOPE
// clang-format off
TF_DEFINE_PRIVATE_TOKENS(_tokens,
(mdl)
);
// clang-format on
NDR_REGISTER_DISCOVERY_PLUGIN(HdStrelkaMdlDiscoveryPlugin);
NdrNodeDiscoveryResultVec HdStrelkaMdlDiscoveryPlugin::DiscoverNodes(const Context& ctx)
{
NdrNodeDiscoveryResultVec result;
NdrNodeDiscoveryResult mdlNode(
/* identifier */ _tokens->mdl,
/* version */ NdrVersion(1),
/* name */ _tokens->mdl,
/* family */ TfToken(),
/* discoveryType */ _tokens->mdl,
/* sourceType */ _tokens->mdl,
/* uri */ std::string(),
/* resolvedUri */ std::string());
result.push_back(mdlNode);
return result;
}
const NdrStringVec& HdStrelkaMdlDiscoveryPlugin::GetSearchURIs() const
{
static const NdrStringVec s_searchURIs;
return s_searchURIs;
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/plugInfo.json | {
"Plugins": [
{
"Info": {
"Types": {
"HdStrelkaRendererPlugin": {
"bases": [
"HdRendererPlugin"
],
"displayName": "Strelka",
"priority": 99
},
"HdStrelkaMdlDiscoveryPlugin": {
"bases": ["NdrDiscoveryPlugin"],
"displayName": "MDL Discovery"
},
"HdStrelkaMdlParserPlugin": {
"bases": ["NdrParserPlugin"],
"displayName": "MDL Node Parser"
}
}
},
"LibraryPath": "../HdStrelka.dylib",
"Name": "HdStrelka",
"ResourcePath": "resources",
"Root": "..",
"Type": "library"
}
]
}
|
arhix52/Strelka/src/HdStrelka/CMakeLists.txt | cmake_minimum_required(VERSION 3.22)
find_package(USD REQUIRED HINTS ${USD_DIR} NAMES pxr)
message(STATUS "USD LIBRARY: ${USD_DIR}")
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
set(CMAKE_POSITION_INDEPENDENT_CODE ON)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(CMAKE_CXX_EXTENSIONS OFF)
add_compile_definitions(BOOST_NO_CXX98_FUNCTION_BASE)
# Hydra plugin
set(HD_PLUGIN_SOURCES
${ROOT_HOME}/include/HdStrelka/RendererPlugin.h
${ROOT_HOME}/src/HdStrelka/RendererPlugin.cpp
${ROOT_HOME}/src/HdStrelka/RenderParam.h
${ROOT_HOME}/src/HdStrelka/RenderBuffer.h
${ROOT_HOME}/src/HdStrelka/RenderDelegate.h
${ROOT_HOME}/src/HdStrelka/RenderPass.h
${ROOT_HOME}/src/HdStrelka/RenderBuffer.cpp
${ROOT_HOME}/src/HdStrelka/RenderDelegate.cpp
${ROOT_HOME}/src/HdStrelka/RenderPass.cpp
${ROOT_HOME}/src/HdStrelka/Instancer.h
${ROOT_HOME}/src/HdStrelka/Instancer.cpp
${ROOT_HOME}/src/HdStrelka/Material.h
${ROOT_HOME}/src/HdStrelka/Material.cpp
${ROOT_HOME}/src/HdStrelka/Camera.h
${ROOT_HOME}/src/HdStrelka/Camera.cpp
${ROOT_HOME}/src/HdStrelka/Mesh.h
${ROOT_HOME}/src/HdStrelka/Mesh.cpp
${ROOT_HOME}/src/HdStrelka/BasisCurves.h
${ROOT_HOME}/src/HdStrelka/BasisCurves.cpp
${ROOT_HOME}/src/HdStrelka/Light.h
${ROOT_HOME}/src/HdStrelka/Light.cpp
${ROOT_HOME}/src/HdStrelka/Tokens.h
${ROOT_HOME}/src/HdStrelka/Tokens.cpp
${ROOT_HOME}/src/HdStrelka/MaterialNetworkTranslator.h
${ROOT_HOME}/src/HdStrelka/MaterialNetworkTranslator.cpp
${ROOT_HOME}/src/HdStrelka/MdlParserPlugin.h
${ROOT_HOME}/src/HdStrelka/MdlParserPlugin.cpp
${ROOT_HOME}/src/HdStrelka/MdlDiscoveryPlugin.h
${ROOT_HOME}/src/HdStrelka/MdlDiscoveryPlugin.cpp)
set(HD_PLUGIN_NAME HdStrelka)
set(Boost_USE_STATIC_LIBS OFF)
set(BUILD_SHARED_LIBS ON)
add_library(${HD_PLUGIN_NAME} SHARED ${HD_PLUGIN_SOURCES})
set_target_properties(
${HD_PLUGIN_NAME}
PROPERTIES LINKER_LANGUAGE CXX
CXX_STANDARD 17
CXX_STANDARD_REQUIRED ON
CXX_EXTENSIONS OFF
INSTALL_RPATH_USE_LINK_PATH TRUE
# The other libs in the plugin dir have no "lib" prefix, so let's
# match this
PREFIX "")
target_compile_definitions(
${HD_PLUGIN_NAME}
PUBLIC # Required for PLUG_THIS_PLUGIN macro
MFB_PACKAGE_NAME=${HD_PLUGIN_NAME}
PRIVATE
# Workaround for
# https://github.com/PixarAnimationStudios/USD/issues/1471#issuecomment-799813477
"$<$<OR:$<CONFIG:>,$<CONFIG:Debug>>:TBB_USE_DEBUG>")
# Workaround for https://github.com/PixarAnimationStudios/USD/issues/1279
if(MSVC_VERSION GREATER_EQUAL 1920)
target_compile_options(${HD_PLUGIN_NAME} PRIVATE "/Zc:inline-")
endif()
set(Boost_USE_STATIC_LIBS OFF)
set(BUILD_SHARED_LIBS ON)
target_include_directories(${HD_PLUGIN_NAME} PUBLIC ${ROOT_HOME}/include/log)
target_include_directories(${HD_PLUGIN_NAME}
PUBLIC ${ROOT_HOME}/include/HdStrelka)
target_include_directories(${HD_PLUGIN_NAME} PUBLIC ${CMAKE_CURRENT_SOURCE_DIR})
target_include_directories(${HD_PLUGIN_NAME} PUBLIC hd)
target_include_directories(${HD_PLUGIN_NAME} PRIVATE usdImaging hdMtlx)
# Add the linker options to suppress the MSVCRT conflict warning
if(WIN32)
target_link_options(${HD_PLUGIN_NAME} PRIVATE "/NODEFAULTLIB:MSVCRT")
target_link_options(${HD_PLUGIN_NAME} PRIVATE "/NODEFAULTLIB:LIBCMT")
endif()
if(WIN32 OR LINUX)
target_link_libraries(
${HD_PLUGIN_NAME}
PRIVATE usdImaging
hdMtlx
render
scene
materialmanager
PUBLIC hd)
endif()
if(APPLE)
target_include_directories(${HD_PLUGIN_NAME}
PUBLIC ${ROOT_HOME}/include/materialmanager)
target_link_libraries(
${HD_PLUGIN_NAME}
PRIVATE usdImaging hdMtlx render scene
PUBLIC hd)
target_link_libraries(${HD_PLUGIN_NAME} PUBLIC "-framework Foundation")
target_link_libraries(${HD_PLUGIN_NAME} PUBLIC "-framework QuartzCore")
target_link_libraries(${HD_PLUGIN_NAME} PUBLIC "-framework Metal")
target_link_libraries(${HD_PLUGIN_NAME} PUBLIC "-framework MetalKit")
endif(APPLE)
target_link_libraries(${HD_PLUGIN_NAME} PUBLIC logger)
set(PLUGINFO_PATH "${CMAKE_CURRENT_BINARY_DIR}/plugInfo.json")
set(CMAKE_INSTALL_PREFIX "${USD_DIR}/plugin/usd/")
file(READ ${CMAKE_CURRENT_SOURCE_DIR}/plugInfo.json.in PLUGINFO)
file(
GENERATE
OUTPUT "${PLUGINFO_PATH}"
CONTENT ${PLUGINFO})
install(
FILES "${PLUGINFO_PATH}"
DESTINATION "${CMAKE_INSTALL_PREFIX}/HdStrelka/resources"
COMPONENT ${HD_PLUGIN_NAME})
install(
TARGETS ${HD_PLUGIN_NAME}
LIBRARY DESTINATION "${CMAKE_INSTALL_PREFIX}" COMPONENT ${HD_PLUGIN_NAME}
RUNTIME DESTINATION "${CMAKE_INSTALL_PREFIX}" COMPONENT ${HD_PLUGIN_NAME}
ARCHIVE DESTINATION "${CMAKE_INSTALL_PREFIX}" COMPONENT ${HD_PLUGIN_NAME})
|
arhix52/Strelka/src/HdStrelka/Material.cpp | #include "Material.h"
#include <pxr/base/gf/vec2f.h>
#include <pxr/usd/sdr/registry.h>
#include <pxr/usdImaging/usdImaging/tokens.h>
#include <log.h>
PXR_NAMESPACE_OPEN_SCOPE
HdStrelkaMaterial::HdStrelkaMaterial(const SdfPath& id, const MaterialNetworkTranslator& translator)
: HdMaterial(id), m_translator(translator)
{
}
HdStrelkaMaterial::~HdStrelkaMaterial() = default;
HdDirtyBits HdStrelkaMaterial::GetInitialDirtyBitsMask() const
{
// return DirtyBits::DirtyParams;
return DirtyBits::AllDirty;
}
void HdStrelkaMaterial::Sync(HdSceneDelegate* sceneDelegate, HdRenderParam* renderParam, HdDirtyBits* dirtyBits)
{
TF_UNUSED(renderParam);
const bool pullMaterial = (*dirtyBits & DirtyBits::DirtyParams) != 0u;
*dirtyBits = DirtyBits::Clean;
if (!pullMaterial)
{
return;
}
const SdfPath& id = GetId();
const std::string& name = id.GetString();
STRELKA_INFO("Hydra Material: {}", name.c_str());
const VtValue& resource = sceneDelegate->GetMaterialResource(id);
if (!resource.IsHolding<HdMaterialNetworkMap>())
{
return;
}
auto networkMap = resource.GetWithDefault<HdMaterialNetworkMap>();
HdMaterialNetwork& surfaceNetwork = networkMap.map[HdMaterialTerminalTokens->surface];
bool isUsdPreviewSurface = false;
HdMaterialNode* previewSurfaceNode = nullptr;
// store material parameters
uint32_t nodeIdx = 0;
for (auto& node : surfaceNetwork.nodes)
{
STRELKA_DEBUG("Node #{}: {}", nodeIdx, node.path.GetText());
if (node.identifier == UsdImagingTokens->UsdPreviewSurface)
{
previewSurfaceNode = &node;
isUsdPreviewSurface = true;
}
for (const auto& params : node.parameters)
{
const std::string& name = params.first.GetString();
const TfType type = params.second.GetType();
STRELKA_DEBUG("Node name: {}\tParam name: {}\t{}", node.path.GetName(), name.c_str(),
params.second.GetTypeName().c_str());
if (type.IsA<GfVec3f>())
{
oka::MaterialManager::Param param;
param.name = params.first;
param.type = oka::MaterialManager::Param::Type::eFloat3;
GfVec3f val = params.second.Get<GfVec3f>();
param.value.resize(sizeof(val));
memcpy(param.value.data(), &val, sizeof(val));
mMaterialParams.push_back(param);
}
else if (type.IsA<GfVec4f>())
{
oka::MaterialManager::Param param;
param.name = params.first;
param.type = oka::MaterialManager::Param::Type::eFloat4;
GfVec4f val = params.second.Get<GfVec4f>();
param.value.resize(sizeof(val));
memcpy(param.value.data(), &val, sizeof(val));
mMaterialParams.push_back(param);
}
else if (type.IsA<float>())
{
oka::MaterialManager::Param param;
param.name = params.first;
param.type = oka::MaterialManager::Param::Type::eFloat;
float val = params.second.Get<float>();
param.value.resize(sizeof(val));
memcpy(param.value.data(), &val, sizeof(val));
mMaterialParams.push_back(param);
}
else if (type.IsA<int>())
{
oka::MaterialManager::Param param;
param.name = params.first;
param.type = oka::MaterialManager::Param::Type::eInt;
int val = params.second.Get<int>();
param.value.resize(sizeof(val));
memcpy(param.value.data(), &val, sizeof(val));
mMaterialParams.push_back(param);
}
else if (type.IsA<bool>())
{
oka::MaterialManager::Param param;
param.name = params.first;
param.type = oka::MaterialManager::Param::Type::eBool;
bool val = params.second.Get<bool>();
param.value.resize(sizeof(val));
memcpy(param.value.data(), &val, sizeof(val));
mMaterialParams.push_back(param);
}
else if (type.IsA<SdfAssetPath>())
{
oka::MaterialManager::Param param;
param.name = node.path.GetName() + "_" + std::string(params.first);
param.type = oka::MaterialManager::Param::Type::eTexture;
const SdfAssetPath val = params.second.Get<SdfAssetPath>();
// STRELKA_DEBUG("path: {}", val.GetAssetPath().c_str());
STRELKA_DEBUG("path: {}", val.GetResolvedPath().c_str());
// std::string texPath = val.GetAssetPath();
std::string texPath = val.GetResolvedPath();
if (!texPath.empty())
{
param.value.resize(texPath.size());
memcpy(param.value.data(), texPath.data(), texPath.size());
mMaterialParams.push_back(param);
}
}
else if (type.IsA<GfVec2f>())
{
oka::MaterialManager::Param param;
param.name = params.first;
param.type = oka::MaterialManager::Param::Type::eFloat2;
GfVec2f val = params.second.Get<GfVec2f>();
param.value.resize(sizeof(val));
memcpy(param.value.data(), &val, sizeof(val));
mMaterialParams.push_back(param);
}
else if (type.IsA<TfToken>())
{
const TfToken val = params.second.Get<TfToken>();
STRELKA_DEBUG("TfToken: {}", val.GetText());
}
else if (type.IsA<std::string>())
{
const std::string val = params.second.Get<std::string>();
STRELKA_DEBUG("String: {}", val.c_str());
}
else
{
STRELKA_ERROR("Unknown parameter type!\n");
}
}
nodeIdx++;
}
bool isVolume = false;
const HdMaterialNetwork2 network = HdConvertToHdMaterialNetwork2(networkMap, &isVolume);
if (isVolume)
{
STRELKA_ERROR("Volume %s unsupported", id.GetText());
return;
}
if (isUsdPreviewSurface)
{
mMaterialXCode = m_translator.ParseNetwork(id, network);
// STRELKA_DEBUG("MaterialX code:\n {}\n", mMaterialXCode.c_str());
}
else
{
// MDL
const bool res = MaterialNetworkTranslator::ParseMdlNetwork(network, mMdlFileUri, mMdlSubIdentifier);
if (!res)
{
STRELKA_ERROR("Failed to translate material, replace to default!");
mMdlFileUri = "default.mdl";
mMdlSubIdentifier = "default_material";
}
mIsMdl = true;
}
}
const std::string& HdStrelkaMaterial::GetStrelkaMaterial() const
{
return mMaterialXCode;
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Camera.cpp | #include "Camera.h"
#include <pxr/imaging/hd/sceneDelegate.h>
#include <pxr/base/gf/vec4d.h>
#include <pxr/base/gf/camera.h>
#include <cmath>
#include <glm/glm.hpp>
#include <glm/gtc/matrix_transform.hpp>
#include <glm/gtc/quaternion.hpp>
#include <glm/gtc/type_ptr.hpp>
#include <glm/gtx/compatibility.hpp>
#include <glm/gtx/matrix_decompose.hpp>
PXR_NAMESPACE_OPEN_SCOPE
HdStrelkaCamera::HdStrelkaCamera(const SdfPath& id, oka::Scene& scene) : HdCamera(id), mScene(scene), m_vfov(M_PI_2)
{
const std::string& name = id.GetString();
oka::Camera okaCamera;
okaCamera.name = name;
mCameraIndex = mScene.addCamera(okaCamera);
}
HdStrelkaCamera::~HdStrelkaCamera()
{
}
float HdStrelkaCamera::GetVFov() const
{
return m_vfov;
}
uint32_t HdStrelkaCamera::GetCameraIndex() const
{
return mCameraIndex;
}
void HdStrelkaCamera::Sync(HdSceneDelegate* sceneDelegate, HdRenderParam* renderParam, HdDirtyBits* dirtyBits)
{
HdDirtyBits dirtyBitsCopy = *dirtyBits;
HdCamera::Sync(sceneDelegate, renderParam, &dirtyBitsCopy);
if (*dirtyBits & DirtyBits::DirtyParams)
{
// See https://wiki.panotools.org/Field_of_View
float aperture = _verticalAperture * GfCamera::APERTURE_UNIT;
float focalLength = _focalLength * GfCamera::FOCAL_LENGTH_UNIT;
float vfov = 2.0f * std::atan(aperture / (2.0f * focalLength));
m_vfov = vfov;
oka::Camera cam = _ConstructStrelkaCamera();
mScene.updateCamera(cam, mCameraIndex);
}
*dirtyBits = DirtyBits::Clean;
}
HdDirtyBits HdStrelkaCamera::GetInitialDirtyBitsMask() const
{
return DirtyBits::DirtyParams | DirtyBits::DirtyTransform;
}
oka::Camera HdStrelkaCamera::_ConstructStrelkaCamera()
{
oka::Camera strelkaCamera;
GfMatrix4d perspMatrix = ComputeProjectionMatrix();
GfMatrix4d absInvViewMatrix = GetTransform();
GfMatrix4d relViewMatrix = absInvViewMatrix; //*m_rootMatrix;
glm::float4x4 xform;
for (int i = 0; i < 4; ++i)
{
for (int j = 0; j < 4; ++j)
{
xform[i][j] = (float)relViewMatrix[i][j];
}
}
glm::float4x4 persp;
for (int i = 0; i < 4; ++i)
{
for (int j = 0; j < 4; ++j)
{
persp[i][j] = (float)perspMatrix[i][j];
}
}
{
glm::vec3 scale;
glm::quat rotation;
glm::vec3 translation;
glm::vec3 skew;
glm::vec4 perspective;
glm::decompose(xform, scale, rotation, translation, skew, perspective);
rotation = glm::conjugate(rotation);
strelkaCamera.position = translation * scale;
strelkaCamera.mOrientation = rotation;
}
strelkaCamera.matrices.perspective = persp;
strelkaCamera.matrices.invPerspective = glm::inverse(persp);
strelkaCamera.fov = glm::degrees(GetVFov());
const std::string& name = GetId().GetString();
strelkaCamera.name = name;
return strelkaCamera;
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/RenderPass.cpp | #include "RenderPass.h"
#include "Camera.h"
#include "Instancer.h"
#include "Material.h"
#include "Mesh.h"
#include "BasisCurves.h"
#include "Light.h"
#include "RenderBuffer.h"
#include "Tokens.h"
#include <pxr/base/gf/matrix3d.h>
#include <pxr/base/gf/quatd.h>
#include <pxr/imaging/hd/renderDelegate.h>
#include <pxr/imaging/hd/renderPassState.h>
#include <pxr/imaging/hd/rprim.h>
#include <pxr/imaging/hd/basisCurves.h>
#include <log.h>
#include <glm/glm.hpp>
#include <glm/gtc/matrix_transform.hpp>
#include <glm/gtc/type_ptr.hpp>
#include <glm/gtx/compatibility.hpp>
PXR_NAMESPACE_OPEN_SCOPE
HdStrelkaRenderPass::HdStrelkaRenderPass(HdRenderIndex* index,
const HdRprimCollection& collection,
const HdRenderSettingsMap& settings,
oka::Render* renderer,
oka::Scene* scene)
: HdRenderPass(index, collection),
m_settings(settings),
m_isConverged(false),
m_lastSceneStateVersion(UINT32_MAX),
m_lastRenderSettingsVersion(UINT32_MAX),
mRenderer(renderer),
mScene(scene)
{
}
HdStrelkaRenderPass::~HdStrelkaRenderPass()
{
}
bool HdStrelkaRenderPass::IsConverged() const
{
return m_isConverged;
}
// valid range of coordinates [-1; 1]
uint32_t packNormal(const glm::float3& normal)
{
uint32_t packed = (uint32_t)((normal.x + 1.0f) / 2.0f * 511.99999f);
packed += (uint32_t)((normal.y + 1.0f) / 2.0f * 511.99999f) << 10;
packed += (uint32_t)((normal.z + 1.0f) / 2.0f * 511.99999f) << 20;
return packed;
}
// valid range of coordinates [-10; 10]
uint32_t packUV(const glm::float2& uv)
{
int32_t packed = (uint32_t)((uv.x + 10.0f) / 20.0f * 16383.99999f);
packed += (uint32_t)((uv.y + 10.0f) / 20.0f * 16383.99999f) << 16;
return packed;
}
void HdStrelkaRenderPass::_BakeMeshInstance(const HdStrelkaMesh* mesh, GfMatrix4d transform, uint32_t materialIndex)
{
const GfMatrix4d normalMatrix = transform.GetInverse().GetTranspose();
const std::vector<GfVec3f>& meshPoints = mesh->GetPoints();
const std::vector<GfVec3f>& meshNormals = mesh->GetNormals();
const std::vector<GfVec3f>& meshTangents = mesh->GetTangents();
const std::vector<GfVec3i>& meshFaces = mesh->GetFaces();
const std::vector<GfVec2f>& meshUVs = mesh->GetUVs();
TF_VERIFY(meshPoints.size() == meshNormals.size());
const size_t vertexCount = meshPoints.size();
std::vector<oka::Scene::Vertex> vertices(vertexCount);
std::vector<uint32_t> indices(meshFaces.size() * 3);
for (size_t j = 0; j < meshFaces.size(); ++j)
{
const GfVec3i& vertexIndices = meshFaces[j];
indices[j * 3 + 0] = vertexIndices[0];
indices[j * 3 + 1] = vertexIndices[1];
indices[j * 3 + 2] = vertexIndices[2];
}
for (size_t j = 0; j < vertexCount; ++j)
{
const GfVec3f& point = meshPoints[j];
const GfVec3f& normal = meshNormals[j];
const GfVec3f& tangent = meshTangents[j];
oka::Scene::Vertex& vertex = vertices[j];
vertex.pos[0] = point[0];
vertex.pos[1] = point[1];
vertex.pos[2] = point[2];
const glm::float3 glmNormal = glm::float3(normal[0], normal[1], normal[2]);
vertex.normal = packNormal(glmNormal);
const glm::float3 glmTangent = glm::float3(tangent[0], tangent[1], tangent[2]);
vertex.tangent = packNormal(glmTangent);
// Texture coord
if (!meshUVs.empty())
{
const GfVec2f& uv = meshUVs[j];
const glm::float2 glmUV = glm::float2(uv[0], 1.0f - uv[1]); // Flip v coordinate
vertex.uv = packUV(glmUV);
}
}
glm::float4x4 glmTransform;
for (int i = 0; i < 4; ++i)
{
for (int j = 0; j < 4; ++j)
{
glmTransform[i][j] = (float)transform[i][j];
}
}
uint32_t meshId = mScene->createMesh(vertices, indices);
assert(meshId != -1);
uint32_t instId = mScene->createInstance(oka::Instance::Type::eMesh, meshId, materialIndex, glmTransform);
assert(instId != -1);
}
void HdStrelkaRenderPass::_BakeMeshes(HdRenderIndex* renderIndex, GfMatrix4d rootTransform)
{
TfHashMap<SdfPath, uint32_t, SdfPath::Hash> materialMapping;
materialMapping[SdfPath::EmptyPath()] = 0;
auto getOrCreateMaterial = [&](const SdfPath& materialId) {
uint32_t materialIndex = 0;
if (materialMapping.find(materialId) != materialMapping.end())
{
materialIndex = materialMapping[materialId];
}
else
{
HdSprim* sprim = renderIndex->GetSprim(HdPrimTypeTokens->material, materialId);
if (!sprim)
{
STRELKA_ERROR("Cannot retrive material!");
return 0u;
}
HdStrelkaMaterial* material = dynamic_cast<HdStrelkaMaterial*>(sprim);
if (material->isMdl())
{
const std::string& fileUri = material->getFileUri();
const std::string& name = material->getSubIdentifier();
oka::Scene::MaterialDescription materialDesc;
materialDesc.file = fileUri;
materialDesc.name = name;
materialDesc.type = oka::Scene::MaterialDescription::Type::eMdl;
materialDesc.params = material->getParams();
materialIndex = mScene->addMaterial(materialDesc);
}
else
{
const std::string& code = material->GetStrelkaMaterial();
const std::string& name = material->getSubIdentifier();
oka::Scene::MaterialDescription materialDesc;
materialDesc.name = name;
materialDesc.code = code;
materialDesc.type = oka::Scene::MaterialDescription::Type::eMaterialX;
materialDesc.params = material->getParams();
materialIndex = mScene->addMaterial(materialDesc);
}
materialMapping[materialId] = materialIndex;
}
return materialIndex;
};
for (const auto& rprimId : renderIndex->GetRprimIds())
{
const HdRprim* rprim = renderIndex->GetRprim(rprimId);
if (dynamic_cast<const HdMesh*>(rprim))
{
const HdStrelkaMesh* mesh = dynamic_cast<const HdStrelkaMesh*>(rprim);
if (!mesh->IsVisible())
{
// TODO: add UI/setting control here
continue;
}
const TfToken renderTag = mesh->GetRenderTag();
if ((renderTag != "geometry") && (renderTag != "render"))
{
// skip all proxy meshes
continue;
}
VtMatrix4dArray transforms;
const SdfPath& instancerId = mesh->GetInstancerId();
if (instancerId.IsEmpty())
{
transforms.resize(1);
transforms[0] = GfMatrix4d(1.0);
}
else
{
HdInstancer* boxedInstancer = renderIndex->GetInstancer(instancerId);
HdStrelkaInstancer* instancer = dynamic_cast<HdStrelkaInstancer*>(boxedInstancer);
const SdfPath& meshId = mesh->GetId();
transforms = instancer->ComputeInstanceTransforms(meshId);
}
const SdfPath& materialId = mesh->GetMaterialId();
const std::string& materialName = materialId.GetString();
STRELKA_INFO("Hydra: Mesh: {0} \t Material: {1}", mesh->getName(), materialName.c_str());
uint32_t materialIndex = 0;
if (materialId.IsEmpty())
{
GfVec3f color(1.0f);
if (mesh->HasColor())
{
color = mesh->GetColor();
}
// materialName += "_color";
const std::string& fileUri = "default.mdl";
const std::string& name = "default_material";
oka::Scene::MaterialDescription material;
material.file = fileUri;
material.name = name;
material.type = oka::Scene::MaterialDescription::Type::eMdl;
material.color = glm::float3(color[0], color[1], color[2]);
material.hasColor = true;
oka::MaterialManager::Param colorParam = {};
colorParam.name = "diffuse_color";
colorParam.type = oka::MaterialManager::Param::Type::eFloat3;
colorParam.value.resize(sizeof(float) * 3);
memcpy(colorParam.value.data(), glm::value_ptr(material.color), sizeof(float) * 3);
material.params.push_back(colorParam);
materialIndex = mScene->addMaterial(material);
}
else
{
materialIndex = getOrCreateMaterial(materialId);
}
const GfMatrix4d& prototypeTransform = mesh->GetPrototypeTransform();
for (size_t i = 0; i < transforms.size(); i++)
{
const GfMatrix4d transform = prototypeTransform * transforms[i]; // *rootTransform;
// GfMatrix4d transform = GfMatrix4d(1.0);
_BakeMeshInstance(mesh, transform, materialIndex);
}
}
else if (dynamic_cast<const HdBasisCurves*>(rprim))
{
const HdStrelkaBasisCurves* curve = dynamic_cast<const HdStrelkaBasisCurves*>(rprim);
const std::vector<glm::float3>& points = curve->GetPoints();
const std::vector<float>& widths = curve->GetWidths();
const std::vector<uint32_t>& vertexCounts = curve->GetVertexCounts();
const SdfPath& materialId = curve->GetMaterialId();
const std::string& materialName = materialId.GetString();
STRELKA_INFO("Hydra: Curve: {0} \t Material: {1}", curve->getName(), materialName.c_str());
const uint32_t materialIndex = getOrCreateMaterial(materialId);
const GfMatrix4d& prototypeTransform = curve->GetPrototypeTransform();
glm::float4x4 glmTransform;
for (int i = 0; i < 4; ++i)
{
for (int j = 0; j < 4; ++j)
{
glmTransform[i][j] = (float)prototypeTransform[i][j];
}
}
uint32_t curveId = mScene->createCurve(oka::Curve::Type::eCubic, vertexCounts, points, widths);
mScene->createInstance(oka::Instance::Type::eCurve, curveId, materialIndex, glmTransform, -1);
}
}
STRELKA_INFO("Meshes: {}", mScene->getMeshes().size());
STRELKA_INFO("Instances: {}", mScene->getInstances().size());
STRELKA_INFO("Materials: {}", mScene->getMaterials().size());
STRELKA_INFO("Curves: {}", mScene->getCurves().size());
}
void HdStrelkaRenderPass::_Execute(const HdRenderPassStateSharedPtr& renderPassState, const TfTokenVector& renderTags)
{
TF_UNUSED(renderTags);
HD_TRACE_FUNCTION();
HF_MALLOC_TAG_FUNCTION();
m_isConverged = false;
const auto* camera = dynamic_cast<const HdStrelkaCamera*>(renderPassState->GetCamera());
if (!camera)
{
return;
}
const HdRenderPassAovBindingVector& aovBindings = renderPassState->GetAovBindings();
if (aovBindings.empty())
{
return;
}
const HdRenderPassAovBinding* colorAovBinding = nullptr;
for (const HdRenderPassAovBinding& aovBinding : aovBindings)
{
if (aovBinding.aovName != HdAovTokens->color)
{
HdStrelkaRenderBuffer* renderBuffer = dynamic_cast<HdStrelkaRenderBuffer*>(aovBinding.renderBuffer);
renderBuffer->SetConverged(true);
continue;
}
colorAovBinding = &aovBinding;
}
if (!colorAovBinding)
{
return;
}
HdRenderIndex* renderIndex = GetRenderIndex();
HdChangeTracker& changeTracker = renderIndex->GetChangeTracker();
HdRenderDelegate* renderDelegate = renderIndex->GetRenderDelegate();
HdStrelkaRenderBuffer* renderBuffer = dynamic_cast<HdStrelkaRenderBuffer*>(colorAovBinding->renderBuffer);
uint32_t sceneStateVersion = changeTracker.GetSceneStateVersion();
uint32_t renderSettingsStateVersion = renderDelegate->GetRenderSettingsVersion();
bool sceneChanged = (sceneStateVersion != m_lastSceneStateVersion);
bool renderSettingsChanged = (renderSettingsStateVersion != m_lastRenderSettingsVersion);
// if (!sceneChanged && !renderSettingsChanged)
//{
// renderBuffer->SetConverged(true);
// return;
//}
oka::Buffer* outputImage = renderBuffer->GetResource(false).UncheckedGet<oka::Buffer*>();
renderBuffer->SetConverged(false);
m_lastSceneStateVersion = sceneStateVersion;
m_lastRenderSettingsVersion = renderSettingsStateVersion;
// Transform scene into camera space to increase floating point precision.
GfMatrix4d viewMatrix = camera->GetTransform().GetInverse();
static int counter = 0;
if (counter == 0)
{
++counter;
_BakeMeshes(renderIndex, viewMatrix);
m_rootMatrix = viewMatrix;
mRenderer->setScene(mScene);
const uint32_t camIndex = camera->GetCameraIndex();
// mRenderer->setActiveCameraIndex(camIndex);
oka::Scene::UniformLightDesc desc{};
desc.color = glm::float3(1.0f);
desc.height = 0.4f;
desc.width = 0.4f;
desc.position = glm::float3(0, 1.1, 0.67);
desc.orientation = glm::float3(179.68, 29.77, -89.97);
desc.intensity = 160.0f;
static const TfTokenVector lightTypes = { HdPrimTypeTokens->domeLight, HdPrimTypeTokens->simpleLight,
HdPrimTypeTokens->sphereLight, HdPrimTypeTokens->rectLight,
HdPrimTypeTokens->diskLight, HdPrimTypeTokens->cylinderLight,
HdPrimTypeTokens->distantLight };
size_t count = 0;
// TF_FOR_ALL(it, lightTypes)
{
// TODO: refactor this to more generic code, templates?
if (renderIndex->IsSprimTypeSupported(HdPrimTypeTokens->rectLight))
{
SdfPathVector sprimPaths =
renderIndex->GetSprimSubtree(HdPrimTypeTokens->rectLight, SdfPath::AbsoluteRootPath());
for (int lightIdx = 0; lightIdx < sprimPaths.size(); ++lightIdx)
{
HdSprim* sprim = renderIndex->GetSprim(HdPrimTypeTokens->rectLight, sprimPaths[lightIdx]);
HdStrelkaLight* light = dynamic_cast<HdStrelkaLight*>(sprim);
mScene->createLight(light->getLightDesc());
}
}
if (renderIndex->IsSprimTypeSupported(HdPrimTypeTokens->diskLight))
{
SdfPathVector sprimPaths =
renderIndex->GetSprimSubtree(HdPrimTypeTokens->diskLight, SdfPath::AbsoluteRootPath());
for (int lightIdx = 0; lightIdx < sprimPaths.size(); ++lightIdx)
{
HdSprim* sprim = renderIndex->GetSprim(HdPrimTypeTokens->diskLight, sprimPaths[lightIdx]);
HdStrelkaLight* light = dynamic_cast<HdStrelkaLight*>(sprim);
mScene->createLight(light->getLightDesc());
}
}
if (renderIndex->IsSprimTypeSupported(HdPrimTypeTokens->sphereLight))
{
SdfPathVector sprimPaths =
renderIndex->GetSprimSubtree(HdPrimTypeTokens->sphereLight, SdfPath::AbsoluteRootPath());
for (int lightIdx = 0; lightIdx < sprimPaths.size(); ++lightIdx)
{
HdSprim* sprim = renderIndex->GetSprim(HdPrimTypeTokens->sphereLight, sprimPaths[lightIdx]);
HdStrelkaLight* light = dynamic_cast<HdStrelkaLight*>(sprim);
mScene->createLight(light->getLightDesc());
}
}
if (renderIndex->IsSprimTypeSupported(HdPrimTypeTokens->distantLight))
{
SdfPathVector sprimPaths =
renderIndex->GetSprimSubtree(HdPrimTypeTokens->distantLight, SdfPath::AbsoluteRootPath());
for (int lightIdx = 0; lightIdx < sprimPaths.size(); ++lightIdx)
{
HdSprim* sprim = renderIndex->GetSprim(HdPrimTypeTokens->distantLight, sprimPaths[lightIdx]);
HdStrelkaLight* light = dynamic_cast<HdStrelkaLight*>(sprim);
mScene->createLight(light->getLightDesc());
}
}
}
}
// mScene.createLight(desc);
float* img_data = (float*)renderBuffer->Map();
mRenderer->render(outputImage);
renderBuffer->Unmap();
// renderBuffer->SetConverged(true);
m_isConverged = true;
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/MaterialNetworkTranslator.h | // Copyright (C) 2021 Pablo Delgado Krämer
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <https://www.gnu.org/licenses/>.
#pragma once
#include <pxr/usd/sdf/path.h>
#include <string>
#include <MaterialXCore/Document.h>
#include <memory>
PXR_NAMESPACE_OPEN_SCOPE
struct HdMaterialNetwork2;
class MaterialNetworkTranslator
{
public:
MaterialNetworkTranslator(const std::string& mtlxLibPath);
std::string ParseNetwork(const SdfPath& id, const HdMaterialNetwork2& network) const;
static bool ParseMdlNetwork(const HdMaterialNetwork2& network, std::string& fileUri, std::string& subIdentifier);
private:
MaterialX::DocumentPtr CreateMaterialXDocumentFromNetwork(const SdfPath& id, const HdMaterialNetwork2& network) const;
void patchMaterialNetwork(HdMaterialNetwork2& network) const;
private:
MaterialX::DocumentPtr m_nodeLib;
};
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Mesh.cpp | #include "Mesh.h"
#include <pxr/imaging/hd/instancer.h>
#include <pxr/imaging/hd/meshUtil.h>
#include <pxr/imaging/hd/smoothNormals.h>
#include <pxr/imaging/hd/vertexAdjacency.h>
#include <log.h>
PXR_NAMESPACE_OPEN_SCOPE
// clang-format off
TF_DEFINE_PRIVATE_TOKENS(_tokens,
(st)
);
// clang-format on
HdStrelkaMesh::HdStrelkaMesh(const SdfPath& id, oka::Scene* scene)
: HdMesh(id), mPrototypeTransform(1.0), mColor(0.0, 0.0, 0.0), mHasColor(false), mScene(scene)
{
}
HdStrelkaMesh::~HdStrelkaMesh() = default;
void HdStrelkaMesh::Sync(HdSceneDelegate* sceneDelegate,
HdRenderParam* renderParam,
HdDirtyBits* dirtyBits,
const TfToken& reprToken)
{
TF_UNUSED(renderParam);
TF_UNUSED(reprToken);
HD_TRACE_FUNCTION();
HF_MALLOC_TAG_FUNCTION();
HdRenderIndex& renderIndex = sceneDelegate->GetRenderIndex();
if ((*dirtyBits & HdChangeTracker::DirtyInstancer) | (*dirtyBits & HdChangeTracker::DirtyInstanceIndex))
{
HdDirtyBits dirtyBitsCopy = *dirtyBits;
_UpdateInstancer(sceneDelegate, &dirtyBitsCopy);
const SdfPath& instancerId = GetInstancerId();
HdInstancer::_SyncInstancerAndParents(renderIndex, instancerId);
}
const SdfPath& id = GetId();
mName = id.GetText();
if (*dirtyBits & HdChangeTracker::DirtyMaterialId)
{
const SdfPath& materialId = sceneDelegate->GetMaterialId(id);
SetMaterialId(materialId);
}
if (*dirtyBits & HdChangeTracker::DirtyTransform)
{
mPrototypeTransform = sceneDelegate->GetTransform(id);
}
const bool updateGeometry = (*dirtyBits & HdChangeTracker::DirtyPoints) |
(*dirtyBits & HdChangeTracker::DirtyNormals) |
(*dirtyBits & HdChangeTracker::DirtyTopology);
*dirtyBits = HdChangeTracker::Clean;
if (!updateGeometry)
{
return;
}
mFaces.clear();
mPoints.clear();
mNormals.clear();
_UpdateGeometry(sceneDelegate);
}
// valid range of coordinates [-1; 1]
static uint32_t packNormal(const glm::float3& normal)
{
uint32_t packed = (uint32_t)((normal.x + 1.0f) / 2.0f * 511.99999f);
packed += (uint32_t)((normal.y + 1.0f) / 2.0f * 511.99999f) << 10;
packed += (uint32_t)((normal.z + 1.0f) / 2.0f * 511.99999f) << 20;
return packed;
}
void HdStrelkaMesh::_ConvertMesh()
{
const std::vector<GfVec3f>& meshPoints = GetPoints();
const std::vector<GfVec3f>& meshNormals = GetNormals();
const std::vector<GfVec3i>& meshFaces = GetFaces();
TF_VERIFY(meshPoints.size() == meshNormals.size());
const size_t vertexCount = meshPoints.size();
std::vector<oka::Scene::Vertex> vertices(vertexCount);
std::vector<uint32_t> indices(meshFaces.size() * 3);
for (size_t j = 0; j < meshFaces.size(); ++j)
{
const GfVec3i& vertexIndices = meshFaces[j];
indices[j * 3 + 0] = vertexIndices[0];
indices[j * 3 + 1] = vertexIndices[1];
indices[j * 3 + 2] = vertexIndices[2];
}
for (size_t j = 0; j < vertexCount; ++j)
{
const GfVec3f& point = meshPoints[j];
const GfVec3f& normal = meshNormals[j];
oka::Scene::Vertex& vertex = vertices[j];
vertex.pos[0] = point[0];
vertex.pos[1] = point[1];
vertex.pos[2] = point[2];
const glm::float3 glmNormal = glm::float3(normal[0], normal[1], normal[2]);
vertex.normal = packNormal(glmNormal);
}
mStrelkaMeshId = mScene->createMesh(vertices, indices);
assert(mStrelkaMeshId != -1);
}
void HdStrelkaMesh::_UpdateGeometry(HdSceneDelegate* sceneDelegate)
{
const HdMeshTopology& topology = GetMeshTopology(sceneDelegate);
const SdfPath& id = GetId();
const HdMeshUtil meshUtil(&topology, id);
VtVec3iArray indices;
VtIntArray primitiveParams;
meshUtil.ComputeTriangleIndices(&indices, &primitiveParams);
VtVec3fArray points;
VtVec3fArray normals;
VtVec2fArray uvs;
bool indexedNormals;
bool indexedUVs;
_PullPrimvars(sceneDelegate, points, normals, uvs, indexedNormals, indexedUVs, mColor, mHasColor);
const bool hasUVs = !uvs.empty();
for (int i = 0; i < indices.size(); i++)
{
GfVec3i newFaceIndices(i * 3 + 0, i * 3 + 1, i * 3 + 2);
mFaces.push_back(newFaceIndices);
const GfVec3i& faceIndices = indices[i];
mPoints.push_back(points[faceIndices[0]]);
mPoints.push_back(points[faceIndices[1]]);
mPoints.push_back(points[faceIndices[2]]);
auto computeTangent = [](const GfVec3f& normal) {
GfVec3f c1 = GfCross(normal, GfVec3f(1.0f, 0.0f, 0.0f));
GfVec3f c2 = GfCross(normal, GfVec3f(0.0f, 1.0f, 0.0f));
GfVec3f tangent;
if (c1.GetLengthSq() > c2.GetLengthSq())
{
tangent = c1;
}
else
{
tangent = c2;
}
GfNormalize(&tangent);
return tangent;
};
mNormals.push_back(normals[indexedNormals ? faceIndices[0] : newFaceIndices[0]]);
mTangents.push_back(computeTangent(normals[indexedNormals ? faceIndices[0] : newFaceIndices[0]]));
mNormals.push_back(normals[indexedNormals ? faceIndices[1] : newFaceIndices[1]]);
mTangents.push_back(computeTangent(normals[indexedNormals ? faceIndices[1] : newFaceIndices[1]]));
mNormals.push_back(normals[indexedNormals ? faceIndices[2] : newFaceIndices[2]]);
mTangents.push_back(computeTangent(normals[indexedNormals ? faceIndices[2] : newFaceIndices[2]]));
if (hasUVs)
{
mUvs.push_back(uvs[indexedUVs ? faceIndices[0] : newFaceIndices[0]]);
mUvs.push_back(uvs[indexedUVs ? faceIndices[1] : newFaceIndices[1]]);
mUvs.push_back(uvs[indexedUVs ? faceIndices[2] : newFaceIndices[2]]);
}
}
}
bool HdStrelkaMesh::_FindPrimvar(HdSceneDelegate* sceneDelegate,
const TfToken& primvarName,
HdInterpolation& interpolation) const
{
const HdInterpolation interpolations[] = {
HdInterpolation::HdInterpolationVertex, HdInterpolation::HdInterpolationFaceVarying,
HdInterpolation::HdInterpolationConstant, HdInterpolation::HdInterpolationUniform,
HdInterpolation::HdInterpolationVarying, HdInterpolation::HdInterpolationInstance
};
for (const HdInterpolation& currInteroplation : interpolations)
{
const auto& primvarDescs = GetPrimvarDescriptors(sceneDelegate, currInteroplation);
for (const HdPrimvarDescriptor& primvar : primvarDescs)
{
if (primvar.name == primvarName)
{
interpolation = currInteroplation;
return true;
}
}
}
return false;
}
void HdStrelkaMesh::_PullPrimvars(HdSceneDelegate* sceneDelegate,
VtVec3fArray& points,
VtVec3fArray& normals,
VtVec2fArray& uvs,
bool& indexedNormals,
bool& indexedUVs,
GfVec3f& color,
bool& hasColor) const
{
const SdfPath& id = GetId();
// Handle points.
HdInterpolation pointInterpolation;
const bool foundPoints = _FindPrimvar(sceneDelegate, HdTokens->points, pointInterpolation);
if (!foundPoints)
{
TF_RUNTIME_ERROR("Points primvar not found!");
return;
}
else if (pointInterpolation != HdInterpolation::HdInterpolationVertex)
{
TF_RUNTIME_ERROR("Points primvar is not vertex-interpolated!");
return;
}
const VtValue boxedPoints = sceneDelegate->Get(id, HdTokens->points);
points = boxedPoints.Get<VtVec3fArray>();
// Handle color.
HdInterpolation colorInterpolation;
const bool foundColor = _FindPrimvar(sceneDelegate, HdTokens->displayColor, colorInterpolation);
if (foundColor && colorInterpolation == HdInterpolation::HdInterpolationConstant)
{
const VtValue boxedColors = sceneDelegate->Get(id, HdTokens->displayColor);
const VtVec3fArray& colors = boxedColors.Get<VtVec3fArray>();
color = colors[0];
hasColor = true;
}
const HdMeshTopology topology = GetMeshTopology(sceneDelegate);
// Handle normals.
HdInterpolation normalInterpolation;
const bool foundNormals = _FindPrimvar(sceneDelegate, HdTokens->normals, normalInterpolation);
if (foundNormals && normalInterpolation == HdInterpolation::HdInterpolationVertex)
{
const VtValue boxedNormals = sceneDelegate->Get(id, HdTokens->normals);
normals = boxedNormals.Get<VtVec3fArray>();
indexedNormals = true;
}
if (foundNormals && normalInterpolation == HdInterpolation::HdInterpolationFaceVarying)
{
const VtValue boxedFvNormals = sceneDelegate->Get(id, HdTokens->normals);
const VtVec3fArray& fvNormals = boxedFvNormals.Get<VtVec3fArray>();
const HdMeshUtil meshUtil(&topology, id);
VtValue boxedTriangulatedNormals;
if (!meshUtil.ComputeTriangulatedFaceVaryingPrimvar(
fvNormals.cdata(), fvNormals.size(), HdTypeFloatVec3, &boxedTriangulatedNormals))
{
TF_CODING_ERROR("Unable to triangulate face-varying normals of %s", id.GetText());
}
normals = boxedTriangulatedNormals.Get<VtVec3fArray>();
indexedNormals = false;
}
else
{
Hd_VertexAdjacency adjacency;
adjacency.BuildAdjacencyTable(&topology);
normals = Hd_SmoothNormals::ComputeSmoothNormals(&adjacency, points.size(), points.cdata());
indexedNormals = true;
}
// Handle texture coords
HdInterpolation textureCoordInterpolation;
const bool foundTextureCoord = _FindPrimvar(sceneDelegate, _tokens->st, textureCoordInterpolation);
if (foundTextureCoord && textureCoordInterpolation == HdInterpolationVertex)
{
uvs = sceneDelegate->Get(id, _tokens->st).Get<VtVec2fArray>();
indexedUVs = true;
}
if (foundTextureCoord && textureCoordInterpolation == HdInterpolation::HdInterpolationFaceVarying)
{
const VtValue boxedUVs = sceneDelegate->Get(id, _tokens->st);
const VtVec2fArray& fvUVs = boxedUVs.Get<VtVec2fArray>();
const HdMeshUtil meshUtil(&topology, id);
VtValue boxedTriangulatedUVS;
if (!meshUtil.ComputeTriangulatedFaceVaryingPrimvar(
fvUVs.cdata(), fvUVs.size(), HdTypeFloatVec2, &boxedTriangulatedUVS))
{
TF_CODING_ERROR("Unable to triangulate face-varying UVs of %s", id.GetText());
}
uvs = boxedTriangulatedUVS.Get<VtVec2fArray>();
indexedUVs = false;
}
}
const TfTokenVector& HdStrelkaMesh::GetBuiltinPrimvarNames() const
{
return BUILTIN_PRIMVAR_NAMES;
}
const std::vector<GfVec3f>& HdStrelkaMesh::GetPoints() const
{
return mPoints;
}
const std::vector<GfVec3f>& HdStrelkaMesh::GetNormals() const
{
return mNormals;
}
const std::vector<GfVec3f>& HdStrelkaMesh::GetTangents() const
{
return mTangents;
}
const std::vector<GfVec3i>& HdStrelkaMesh::GetFaces() const
{
return mFaces;
}
const std::vector<GfVec2f>& HdStrelkaMesh::GetUVs() const
{
return mUvs;
}
const GfMatrix4d& HdStrelkaMesh::GetPrototypeTransform() const
{
return mPrototypeTransform;
}
const GfVec3f& HdStrelkaMesh::GetColor() const
{
return mColor;
}
bool HdStrelkaMesh::HasColor() const
{
return mHasColor;
}
const char* HdStrelkaMesh::getName() const
{
return mName.c_str();
}
HdDirtyBits HdStrelkaMesh::GetInitialDirtyBitsMask() const
{
return HdChangeTracker::DirtyPoints | HdChangeTracker::DirtyNormals | HdChangeTracker::DirtyTopology |
HdChangeTracker::DirtyInstancer | HdChangeTracker::DirtyInstanceIndex | HdChangeTracker::DirtyTransform |
HdChangeTracker::DirtyMaterialId | HdChangeTracker::DirtyPrimvar;
}
HdDirtyBits HdStrelkaMesh::_PropagateDirtyBits(HdDirtyBits bits) const
{
return bits;
}
void HdStrelkaMesh::_InitRepr(const TfToken& reprName, HdDirtyBits* dirtyBits)
{
TF_UNUSED(reprName);
TF_UNUSED(dirtyBits);
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Instancer.h | // Copyright (C) 2021 Pablo Delgado Krämer
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <https://www.gnu.org/licenses/>.
#pragma once
#include <pxr/imaging/hd/instancer.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaInstancer final : public HdInstancer
{
public:
HdStrelkaInstancer(HdSceneDelegate* delegate,
const SdfPath& id);
~HdStrelkaInstancer() override;
public:
VtMatrix4dArray ComputeInstanceTransforms(const SdfPath& prototypeId);
void Sync(HdSceneDelegate* sceneDelegate,
HdRenderParam* renderParam,
HdDirtyBits* dirtyBits) override;
private:
TfHashMap<TfToken, VtValue, TfToken::HashFunctor> m_primvarMap;
};
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Light.h | #pragma once
#include "pxr/pxr.h"
#include <pxr/imaging/hd/light.h>
#include <pxr/imaging/hd/sceneDelegate.h>
#include <scene/scene.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaLight final : public HdLight
{
public:
HF_MALLOC_TAG_NEW("new HdStrelkaLight");
HdStrelkaLight(const SdfPath& id, TfToken const& lightType);
~HdStrelkaLight() override;
public:
void Sync(HdSceneDelegate* delegate,
HdRenderParam* renderParam,
HdDirtyBits* dirtyBits) override;
HdDirtyBits GetInitialDirtyBitsMask() const override;
oka::Scene::UniformLightDesc getLightDesc();
private:
TfToken mLightType;
oka::Scene::UniformLightDesc mLightDesc;
};
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/MdlParserPlugin.h | // Copyright (C) 2021 Pablo Delgado Krämer
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <https://www.gnu.org/licenses/>.
#pragma once
#include <pxr/usd/ndr/parserPlugin.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaMdlParserPlugin final : public NdrParserPlugin
{
public:
NdrNodeUniquePtr Parse(const NdrNodeDiscoveryResult& discoveryResult) override;
const NdrTokenVec& GetDiscoveryTypes() const override;
const TfToken& GetSourceType() const override;
};
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/MaterialNetworkTranslator.cpp | // Copyright (C) 2021 Pablo Delgado Krämer
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <https://www.gnu.org/licenses/>.
#include "MaterialNetworkTranslator.h"
#include <pxr/imaging/hd/material.h>
#include <pxr/usd/sdr/registry.h>
#include <pxr/imaging/hdMtlx/hdMtlx.h>
#include <pxr/imaging/hd/tokens.h>
#include <MaterialXCore/Document.h>
#include <MaterialXCore/Library.h>
#include <MaterialXCore/Material.h>
#include <MaterialXCore/Definition.h>
#include <MaterialXFormat/File.h>
#include <MaterialXFormat/Util.h>
#include "Tokens.h"
using std::string;
namespace mx = MaterialX;
PXR_NAMESPACE_OPEN_SCOPE
// clang-format off
TF_DEFINE_PRIVATE_TOKENS(
_tokens,
// USD node types
(UsdPreviewSurface)
(UsdUVTexture)
(UsdTransform2d)
(UsdPrimvarReader_float)
(UsdPrimvarReader_float2)
(UsdPrimvarReader_float3)
(UsdPrimvarReader_float4)
(UsdPrimvarReader_int)
(UsdPrimvarReader_string)
(UsdPrimvarReader_normal)
(UsdPrimvarReader_point)
(UsdPrimvarReader_vector)
(UsdPrimvarReader_matrix)
// MaterialX USD node type equivalents
(ND_UsdPreviewSurface_surfaceshader)
(ND_UsdUVTexture)
(ND_UsdPrimvarReader_integer)
(ND_UsdPrimvarReader_boolean)
(ND_UsdPrimvarReader_string)
(ND_UsdPrimvarReader_float)
(ND_UsdPrimvarReader_vector2)
(ND_UsdPrimvarReader_vector3)
(ND_UsdPrimvarReader_vector4)
(ND_UsdTransform2d)
(ND_UsdPrimvarReader_matrix44)
(mdl)
(subIdentifier)
(ND_convert_color3_vector3)
(diffuse_color_constant)
(normal)
(rgb)
(in)
(out)
);
// clang-format on
bool _ConvertNodesToMaterialXNodes(const HdMaterialNetwork2& network, HdMaterialNetwork2& mtlxNetwork)
{
mtlxNetwork = network;
for (auto& node : mtlxNetwork.nodes)
{
TfToken& nodeTypeId = node.second.nodeTypeId;
SdrRegistry& sdrRegistry = SdrRegistry::GetInstance();
if (sdrRegistry.GetShaderNodeByIdentifierAndType(nodeTypeId, HdStrelkaDiscoveryTypes->mtlx))
{
continue;
}
if (nodeTypeId == _tokens->UsdPreviewSurface)
{
nodeTypeId = _tokens->ND_UsdPreviewSurface_surfaceshader;
}
else if (nodeTypeId == _tokens->UsdUVTexture)
{
nodeTypeId = _tokens->ND_UsdUVTexture;
}
else if (nodeTypeId == _tokens->UsdTransform2d)
{
nodeTypeId = _tokens->ND_UsdTransform2d;
}
else if (nodeTypeId == _tokens->UsdPrimvarReader_float)
{
nodeTypeId = _tokens->ND_UsdPrimvarReader_float;
}
else if (nodeTypeId == _tokens->UsdPrimvarReader_float2)
{
nodeTypeId = _tokens->ND_UsdPrimvarReader_vector2;
}
else if (nodeTypeId == _tokens->UsdPrimvarReader_float3)
{
nodeTypeId = _tokens->ND_UsdPrimvarReader_vector3;
}
else if (nodeTypeId == _tokens->UsdPrimvarReader_float4)
{
nodeTypeId = _tokens->ND_UsdPrimvarReader_vector4;
}
else if (nodeTypeId == _tokens->UsdPrimvarReader_int)
{
nodeTypeId = _tokens->ND_UsdPrimvarReader_integer;
}
else if (nodeTypeId == _tokens->UsdPrimvarReader_string)
{
nodeTypeId = _tokens->ND_UsdPrimvarReader_string;
}
else if (nodeTypeId == _tokens->UsdPrimvarReader_normal)
{
nodeTypeId = _tokens->ND_UsdPrimvarReader_vector3;
}
else if (nodeTypeId == _tokens->UsdPrimvarReader_point)
{
nodeTypeId = _tokens->ND_UsdPrimvarReader_vector3;
}
else if (nodeTypeId == _tokens->UsdPrimvarReader_vector)
{
nodeTypeId = _tokens->ND_UsdPrimvarReader_vector3;
}
else if (nodeTypeId == _tokens->UsdPrimvarReader_matrix)
{
nodeTypeId = _tokens->ND_UsdPrimvarReader_matrix44;
}
else
{
TF_WARN("Unable to translate material node of type %s to MaterialX counterpart", nodeTypeId.GetText());
return false;
}
}
return true;
}
bool GetMaterialNetworkSurfaceTerminal(const HdMaterialNetwork2& network2,
HdMaterialNode2& surfaceTerminal,
SdfPath& terminalPath)
{
const auto& connectionIt = network2.terminals.find(HdMaterialTerminalTokens->surface);
if (connectionIt == network2.terminals.end())
{
return false;
}
const HdMaterialConnection2& connection = connectionIt->second;
terminalPath = connection.upstreamNode;
const auto& nodeIt = network2.nodes.find(terminalPath);
if (nodeIt == network2.nodes.end())
{
return false;
}
surfaceTerminal = nodeIt->second;
return true;
}
MaterialNetworkTranslator::MaterialNetworkTranslator(const std::string& mtlxLibPath)
{
m_nodeLib = mx::createDocument();
const mx::FilePathVec libFolders; // All directories if left empty.
const mx::FileSearchPath folderSearchPath(mtlxLibPath);
mx::loadLibraries(libFolders, folderSearchPath, m_nodeLib);
}
std::string MaterialNetworkTranslator::ParseNetwork(const SdfPath& id, const HdMaterialNetwork2& network) const
{
HdMaterialNetwork2 mtlxNetwork;
if (!_ConvertNodesToMaterialXNodes(network, mtlxNetwork))
{
return "";
}
patchMaterialNetwork(mtlxNetwork);
const mx::DocumentPtr doc = CreateMaterialXDocumentFromNetwork(id, mtlxNetwork);
if (!doc)
{
return "";
}
mx::string docStr = mx::writeToXmlString(doc);
return docStr;
}
bool MaterialNetworkTranslator::ParseMdlNetwork(const HdMaterialNetwork2& network,
std::string& fileUri,
std::string& subIdentifier)
{
if (network.nodes.size() == 1)
{
const HdMaterialNode2& node = network.nodes.begin()->second;
SdrRegistry& sdrRegistry = SdrRegistry::GetInstance();
SdrShaderNodeConstPtr sdrNode = sdrRegistry.GetShaderNodeByIdentifier(node.nodeTypeId);
if ((sdrNode == nullptr) || sdrNode->GetContext() != _tokens->mdl)
{
return false;
}
const NdrTokenMap& metadata = sdrNode->GetMetadata();
const auto& subIdentifierIt = metadata.find(_tokens->subIdentifier);
TF_DEV_AXIOM(subIdentifierIt != metadata.end());
subIdentifier = (*subIdentifierIt).second;
fileUri = sdrNode->GetResolvedImplementationURI();
return true;
}
TF_RUNTIME_ERROR("Unsupported multi-node MDL material!");
return false;
}
mx::DocumentPtr MaterialNetworkTranslator::CreateMaterialXDocumentFromNetwork(const SdfPath& id,
const HdMaterialNetwork2& network) const
{
HdMaterialNode2 surfaceTerminal;
SdfPath terminalPath;
if (!GetMaterialNetworkSurfaceTerminal(network, surfaceTerminal, terminalPath))
{
TF_WARN("Unable to find surface terminal for material network");
return nullptr;
}
HdMtlxTexturePrimvarData mxHdData;
return HdMtlxCreateMtlxDocumentFromHdNetwork(network, surfaceTerminal, terminalPath, id, m_nodeLib, &mxHdData);
}
void MaterialNetworkTranslator::patchMaterialNetwork(HdMaterialNetwork2& network) const
{
for (auto& pathNodePair : network.nodes)
{
HdMaterialNode2& node = pathNodePair.second;
if (node.nodeTypeId != _tokens->ND_UsdPreviewSurface_surfaceshader)
{
continue;
}
auto& inputs = node.inputConnections;
const auto patchColor3Vector3InputConnection = [&inputs, &network](const TfToken& inputName) {
auto inputIt = inputs.find(inputName);
if (inputIt == inputs.end())
{
return;
}
auto& connections = inputIt->second;
for (HdMaterialConnection2& connection : connections)
{
if (connection.upstreamOutputName != _tokens->rgb)
{
continue;
}
SdfPath upstreamNodePath = connection.upstreamNode;
SdfPath convertNodePath = upstreamNodePath;
for (int i = 0; network.nodes.count(convertNodePath) > 0; i++)
{
const std::string convertNodeName = "convert" + std::to_string(i);
convertNodePath = upstreamNodePath.AppendElementString(convertNodeName);
}
HdMaterialNode2 convertNode;
convertNode.nodeTypeId = _tokens->ND_convert_color3_vector3;
convertNode.inputConnections[_tokens->in] = { { upstreamNodePath, _tokens->rgb } };
network.nodes[convertNodePath] = convertNode;
connection.upstreamNode = convertNodePath;
connection.upstreamOutputName = _tokens->out;
}
};
patchColor3Vector3InputConnection(_tokens->normal);
}
}
PXR_NAMESPACE_CLOSE_SCOPE
|
arhix52/Strelka/src/HdStrelka/Mesh.h | #pragma once
#include <pxr/pxr.h>
#include <pxr/imaging/hd/mesh.h>
#include <scene/scene.h>
#include <pxr/base/gf/vec2f.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaMesh final : public HdMesh
{
public:
HF_MALLOC_TAG_NEW("new HdStrelkaMesh");
HdStrelkaMesh(const SdfPath& id, oka::Scene* scene);
~HdStrelkaMesh() override;
void Sync(HdSceneDelegate* delegate,
HdRenderParam* renderParam,
HdDirtyBits* dirtyBits,
const TfToken& reprToken) override;
HdDirtyBits GetInitialDirtyBitsMask() const override;
const TfTokenVector& GetBuiltinPrimvarNames() const override;
const std::vector<GfVec3f>& GetPoints() const;
const std::vector<GfVec3f>& GetNormals() const;
const std::vector<GfVec3f>& GetTangents() const;
const std::vector<GfVec3i>& GetFaces() const;
const std::vector<GfVec2f>& GetUVs() const;
const GfMatrix4d& GetPrototypeTransform() const;
const GfVec3f& GetColor() const;
bool HasColor() const;
const char* getName() const;
protected:
HdDirtyBits _PropagateDirtyBits(HdDirtyBits bits) const override;
void _InitRepr(const TfToken& reprName, HdDirtyBits* dirtyBits) override;
private:
void _ConvertMesh();
void _UpdateGeometry(HdSceneDelegate* sceneDelegate);
bool _FindPrimvar(HdSceneDelegate* sceneDelegate, const TfToken& primvarName, HdInterpolation& interpolation) const;
void _PullPrimvars(HdSceneDelegate* sceneDelegate,
VtVec3fArray& points,
VtVec3fArray& normals,
VtVec2fArray& uvs,
bool& indexedNormals,
bool& indexedUVs,
GfVec3f& color,
bool& hasColor) const;
const TfTokenVector BUILTIN_PRIMVAR_NAMES = { HdTokens->points, HdTokens->normals };
GfMatrix4d mPrototypeTransform;
std::vector<GfVec3f> mPoints;
std::vector<GfVec3f> mNormals;
std::vector<GfVec3f> mTangents;
std::vector<GfVec2f> mUvs;
std::vector<GfVec3i> mFaces;
GfVec3f mColor;
bool mHasColor;
oka::Scene* mScene;
std::string mName;
uint32_t mStrelkaMeshId;
};
PXR_NAMESPACE_CLOSE_SCOPE
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arhix52/Strelka/src/HdStrelka/RenderBuffer.h | #pragma once
#include <pxr/imaging/hd/renderBuffer.h>
#include <pxr/pxr.h>
#include <render/common.h>
#include <render/buffer.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaRenderBuffer final : public HdRenderBuffer
{
public:
HdStrelkaRenderBuffer(const SdfPath& id, oka::SharedContext* ctx);
~HdStrelkaRenderBuffer() override;
public:
bool Allocate(const GfVec3i& dimensions, HdFormat format, bool multiSamples) override;
public:
unsigned int GetWidth() const override;
unsigned int GetHeight() const override;
unsigned int GetDepth() const override;
HdFormat GetFormat() const override;
bool IsMultiSampled() const override;
VtValue GetResource(bool multiSampled) const override;
public:
bool IsConverged() const override;
void SetConverged(bool converged);
public:
void* Map() override;
bool IsMapped() const override;
void Unmap() override;
void Resolve() override;
protected:
void _Deallocate() override;
private:
// oka::Image* mResult = nullptr;
oka::SharedContext* mCtx = nullptr;
oka::Buffer* mResult = nullptr;
void* m_bufferMem = nullptr;
uint32_t m_width;
uint32_t m_height;
HdFormat m_format;
bool m_isMultiSampled;
bool m_isMapped;
bool m_isConverged;
};
PXR_NAMESPACE_CLOSE_SCOPE
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arhix52/Strelka/src/HdStrelka/RenderPass.h | #pragma once
#include <pxr/imaging/hd/renderDelegate.h>
#include <pxr/imaging/hd/renderPass.h>
#include <pxr/pxr.h>
#include <scene/camera.h>
#include <scene/scene.h>
#include <render/render.h>
PXR_NAMESPACE_OPEN_SCOPE
class HdStrelkaCamera;
class HdStrelkaMesh;
class HdStrelkaRenderPass final : public HdRenderPass
{
public:
HdStrelkaRenderPass(HdRenderIndex* index,
const HdRprimCollection& collection,
const HdRenderSettingsMap& settings,
oka::Render* renderer,
oka::Scene* scene);
~HdStrelkaRenderPass() override;
bool IsConverged() const override;
protected:
void _Execute(const HdRenderPassStateSharedPtr& renderPassState,
const TfTokenVector& renderTags) override;
private:
void _BakeMeshInstance(const HdStrelkaMesh* mesh,
GfMatrix4d transform,
uint32_t materialIndex);
void _BakeMeshes(HdRenderIndex* renderIndex,
GfMatrix4d rootTransform);
const HdRenderSettingsMap& m_settings;
bool m_isConverged;
uint32_t m_lastSceneStateVersion;
uint32_t m_lastRenderSettingsVersion;
GfMatrix4d m_rootMatrix;
oka::Scene* mScene;
// ptr to global render
oka::Render* mRenderer;
};
PXR_NAMESPACE_CLOSE_SCOPE
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