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import os, sys | |
import torch | |
# Directly run `python -m pytest` or | |
# Directly run `python -m pytest -v -s --disable-warnings` for Debugging | |
# To test single function: | |
# pytest tests/test_t2v.py::test_function_name | |
dummy_prompts = [ | |
"a teddy bear walking on the street, 2k, high quality", | |
"a panda taking a selfie, 2k, high quality", | |
"a polar bear playing drum kit in NYC Times Square, 4k, high resolution", | |
"jungle river at sunset, ultra quality", | |
"a shark swimming in clear Carribean ocean, 2k, high quality", | |
"a Corgi walking in the park at sunrise, oil painting style", | |
] | |
import sys | |
sys.path.append("src") | |
def test_LaVie(): | |
from videogen_hub.infermodels import LaVie | |
model = LaVie() | |
assert model is not None | |
out_video = model.infer_one_video(dummy_prompts[0]) | |
assert out_video is not None | |
# check if out_video is a tensor or not | |
assert isinstance(out_video, torch.Tensor) | |
print(out_video.shape) | |
def test_VideoCrafter2(): | |
from videogen_hub.infermodels import VideoCrafter2 | |
model = VideoCrafter2() | |
assert model is not None | |
out_video = model.infer_one_video(dummy_prompts[0]) | |
assert out_video is not None | |
# check if out_video is a tensor or not | |
assert isinstance(out_video, torch.Tensor) | |
print(out_video.shape) | |
def test_ModelScope(): | |
from videogen_hub.infermodels import ModelScope | |
model = ModelScope() | |
assert model is not None | |
out_video = model.infer_one_video(dummy_prompts[0]) | |
print("video ouputted") | |
assert out_video is not None | |
# check if out_video is a tensor or not | |
assert isinstance(out_video, torch.Tensor) | |
print(out_video.shape) | |
def test_StreamingT2V(): | |
from videogen_hub.infermodels import StreamingT2V | |
model = StreamingT2V() | |
assert model is not None | |
out_video = model.infer_one_video(dummy_prompts[0]) | |
print("video ouputted") | |
assert out_video is not None | |
# check if out_video is a tensor or not | |
assert isinstance(out_video, torch.Tensor) | |
print(out_video.shape) | |
def test_OpenSora(): | |
from videogen_hub.infermodels import OpenSora | |
model = OpenSora() | |
assert model is not None | |
out_video = model.infer_one_video(dummy_prompts[0]) | |
assert out_video is not None | |
# check if out_video is a tensor or not | |
assert isinstance(out_video, torch.Tensor) | |
print(out_video.shape) | |
def test_ShowOne(): | |
from videogen_hub.infermodels import ShowOne | |
model = ShowOne() | |
assert model is not None | |
out_video = model.infer_one_video(dummy_prompts[0]) | |
assert out_video is not None | |
# check if out_video is a tensor or not | |
assert isinstance(out_video, torch.Tensor) | |
print(out_video.shape) | |
if __name__ == "__main__": | |
test_ShowOne() | |
print("Everything passed") | |
pass |