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automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: automatic-speech-recognition
+  model: jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+  processor: jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/ASR
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: automatic_speech_recognition
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null

automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42
+  sweep:
+    dir: runs/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42
+    - hydra.mode=RUN
+    task:
+    - backend.model=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+    - backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese,backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+    id: ???
+    num: ???
+    config_name: automatic_speech_recognition
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+- backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese

automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/cli.log

@@ -0,0 +1,25 @@
+[2024-12-07 06:11:45,176][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:11:45,176][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:11:45,188][device-isolation][INFO] - 	+ Launched device(s) isolation process 1684
+[2024-12-07 06:11:45,189][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:11:45,195][process][INFO] - 	+ Launched benchmark in isolated process 1685.
+[PROC-0][2024-12-07 06:11:47,759][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:11:48,710][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:11:48,710][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCTC
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 06:11:49,098][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 06:11:49,099][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 06:11:49,100][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 06:11:49,100][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:11:49,419][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:11:49,425][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:11:49,425][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:11:55,577][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:11:55,577][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:11:59,770][energy_star][INFO] - 	+ Preprocessing dataset
+[2024-12-07 06:12:06,206][experiment][ERROR] - Error during experiment

automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/error.log

@@ -0,0 +1,95 @@
+/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
+  warnings.warn(
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[codecarbon INFO @ 06:11:55] [setup] RAM Tracking...
+[codecarbon INFO @ 06:11:55] [setup] GPU Tracking...
+[codecarbon INFO @ 06:11:55] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 06:11:55] GPU available. Starting setup
+[codecarbon INFO @ 06:11:55] [setup] CPU Tracking...
+[codecarbon DEBUG @ 06:11:55] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 06:11:55] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 06:11:55] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 06:11:55] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 06:11:56] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 06:11:56] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 06:11:56] >>> Tracker's metadata:
+[codecarbon INFO @ 06:11:56]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 06:11:56]   Python version: 3.9.20
+[codecarbon INFO @ 06:11:56]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 06:11:56]   Available RAM : 186.705 GB
+[codecarbon INFO @ 06:11:56]   CPU count: 48
+[codecarbon INFO @ 06:11:56]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 06:11:56]   GPU count: 1
+[codecarbon INFO @ 06:11:56]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 06:11:57] Not running on AWS
+[codecarbon DEBUG @ 06:11:58] Not running on Azure
+[codecarbon DEBUG @ 06:11:59] Not running on GCP
+[codecarbon INFO @ 06:11:59] Saving emissions data to file /runs/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/codecarbon.csv
+[codecarbon DEBUG @ 06:11:59] EmissionsData(timestamp='2024-12-07T06:11:59', project_name='codecarbon', run_id='a03b476e-f4b5-493a-b12b-aca3f913c3d2', duration=0.0021435300004668534, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
+Error executing job with overrides: ['backend.model=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese', 'backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese']
+Traceback (most recent call last):
+  File "/optimum-benchmark/optimum_benchmark/cli.py", line 65, in benchmark_cli
+    benchmark_report: BenchmarkReport = launch(experiment_config=experiment_config)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch
+    raise error
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch
+    report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch
+    while not process_context.join():
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join
+    raise ProcessRaisedException(msg, error_index, failed_process.pid)
+torch.multiprocessing.spawn.ProcessRaisedException: 
+
+-- Process 0 terminated with the following error:
+Traceback (most recent call last):
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap
+    fn(i, *args)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint
+    worker_output = worker(*worker_args)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 62, in run
+    benchmark.run(backend)
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 122, in run
+    self.dataset = preprocess(
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/preprocessing_utils.py", line 28, in preprocess
+    return task_to_preprocessing[task](dataset, config, preprocessor, pretrained_config)
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/preprocessing_utils.py", line 360, in automatic_speech_recognition_preprocessing
+    if getattr(processor.tokenizer, "pad_token", None) is None:
+AttributeError: 'Wav2Vec2CTCTokenizer' object has no attribute 'tokenizer'
+
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "automatic_speech_recognition",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "automatic-speech-recognition",
+        "model": "jonatasgrosman/wav2vec2-large-xlsr-53-portuguese",
+        "processor": "jonatasgrosman/wav2vec2-large-xlsr-53-portuguese",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/ASR",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}

image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: image-classification
+  model: Falconsai/nsfw_image_detection
+  processor: Falconsai/nsfw_image_detection
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/image_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: image_classification
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null

image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06
+    - hydra.mode=RUN
+    task:
+    - backend.model=Falconsai/nsfw_image_detection
+    - backend.processor=Falconsai/nsfw_image_detection
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=Falconsai/nsfw_image_detection,backend.processor=Falconsai/nsfw_image_detection
+    id: ???
+    num: ???
+    config_name: image_classification
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=Falconsai/nsfw_image_detection
+- backend.processor=Falconsai/nsfw_image_detection

image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/benchmark_report.json

@@ -0,0 +1,107 @@
+{
+    "forward": {
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+        "latency": null,
+        "throughput": null,
+        "energy": {
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+            "ram": 3.467745284037441e-06,
+            "gpu": 0.0006654816712738266,
+            "total": 0.0009422681639376247
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 1061269.008411704
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.0003119410920825127,
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+                "gpu": 0.0007466994862481702,
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+            },
+            {
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+                "gpu": 0.0007167997401060777,
+                "total": 0.0010229161537196926
+            },
+            {
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+                "ram": 3.8041189763426866e-06,
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+                "total": 0.0010323667098294598
+            },
+            {
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+            {
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+                "ram": 3.835532227298596e-06,
+                "gpu": 0.000752818102254027,
+                "total": 0.001058870065759998
+            },
+            {
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+                "gpu": 0.0007561631049302076,
+                "total": 0.0010640689501330769
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+            {
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+                "ram": 3.915023086995131e-06,
+                "gpu": 0.0007552017152718804,
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+            },
+            {
+                "unit": "kWh",
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+                "ram": 3.909846778875872e-06,
+                "gpu": 0.0007342875318741005,
+                "total": 0.0010462645584772973
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+        ]
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+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
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+            "ram": 4.424616703390787e-07,
+            "gpu": 9.757063361193197e-05,
+            "total": 0.0001606562756330748
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 6224468.954352673
+        },
+        "measures": null
+    }
+}

image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/cli.log

@@ -0,0 +1,113 @@
+[2024-12-07 06:12:09,474][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:12:09,475][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:12:09,488][device-isolation][INFO] - 	+ Launched device(s) isolation process 1929
+[2024-12-07 06:12:09,488][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:12:09,495][process][INFO] - 	+ Launched benchmark in isolated process 1930.
+[PROC-0][2024-12-07 06:12:12,080][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:12:13,006][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:12:13,006][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:12:13,379][pytorch][INFO] - 	+ Using AutoModel class AutoModelForImageClassification
+[PROC-0][2024-12-07 06:12:13,380][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:12:13,380][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:12:13,380][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:12:13,380][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:12:13,380][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 06:12:13,382][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 06:12:13,383][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 06:12:13,383][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 06:12:13,383][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:12:13,648][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:12:13,655][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:12:13,655][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:12:14,284][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:12:14,284][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:12:18,458][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 06:12:23,765][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 06:12:23,765][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 06:12:23,766][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 06:12:23,766][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 06:12:24,022][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 06:12:24,022][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-07 06:12:50,450][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:12:50,451][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-07 06:13:16,056][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:13:16,057][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-07 06:13:41,447][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:13:41,447][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-07 06:14:06,656][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:14:06,656][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-07 06:14:31,969][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:14:31,969][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-07 06:14:57,569][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:14:57,570][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-07 06:15:22,882][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:15:22,882][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-07 06:15:48,638][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:15:48,639][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-07 06:16:14,769][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:16:14,769][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-07 06:16:40,865][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ CPU: 0.000273 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ GPU: 0.000665 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ total: 0.000942 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ CPU: 0.000312 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ GPU: 0.000747 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ total: 0.001063 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ CPU: 0.000302 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ GPU: 0.000717 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ total: 0.001023 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ CPU: 0.000300 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ GPU: 0.000729 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ total: 0.001032 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ CPU: 0.000298 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ GPU: 0.000745 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ total: 0.001046 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ CPU: 0.000299 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ GPU: 0.000719 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ total: 0.001022 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ CPU: 0.000302 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ GPU: 0.000753 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ total: 0.001059 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ GPU: 0.000000 (kWh)
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+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ CPU: 0.000304 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ GPU: 0.000756 (kWh)
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+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ CPU: 0.000308 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ GPU: 0.000755 (kWh)
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+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ total: 0.001068 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ CPU: 0.000308 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ GPU: 0.000734 (kWh)
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+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ CPU: 0.000063 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ GPU: 0.000098 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:16:40,871][energy][INFO] - 			+ total: 0.000161 (kWh)
+[PROC-0][2024-12-07 06:16:40,871][energy][INFO] - 		+ forward energy efficiency: 1061269.008412 (samples/kWh)
+[PROC-0][2024-12-07 06:16:40,871][energy][INFO] - 		+ preprocess energy efficiency: 6224468.954353 (samples/kWh)
+[2024-12-07 06:16:41,595][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-07 06:16:41,643][datasets][INFO] - PyTorch version 2.4.0 available.

image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "image_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "image-classification",
+        "model": "Falconsai/nsfw_image_detection",
+        "processor": "Falconsai/nsfw_image_detection",
+        "library": "transformers",
+        "device": "cuda",
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+        "hub_kwargs": {
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+            "local_files_only": false,
+            "trust_remote_code": true
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+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/image_classification",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
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+        "call_kwargs": {}
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+    "environment": {
+        "cpu": " AMD EPYC 7R32",
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+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
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+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
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+            "NVIDIA A10G"
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+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
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+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
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+}

image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:16:40",
+    "project_name": "codecarbon",
+    "run_id": "1227b6b4-bf23-48a4-ac0a-e6b6f69567eb",
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+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
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+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:12:23",
+    "project_name": "codecarbon",
+    "run_id": "1227b6b4-bf23-48a4-ac0a-e6b6f69567eb",
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+    "emissions": 5.9303754360058324e-05,
+    "emissions_rate": 1.1180630740474825e-05,
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+    "energy_consumed": 0.0001606562756330748,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
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+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
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+}

image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: image-classification
+  model: WinKawaks/vit-tiny-patch16-224
+  processor: WinKawaks/vit-tiny-patch16-224
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
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+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/image_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
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+experiment_name: image_classification
+environment:
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+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
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+  optimum_benchmark_version: 0.2.0
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+  transformers_commit: null
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+  optimum_commit: null
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+  peft_commit: null

image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
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+    - hydra.mode=RUN
+    task:
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+    - backend.processor=WinKawaks/vit-tiny-patch16-224
+  job:
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+    chdir: true
+    override_dirname: backend.model=WinKawaks/vit-tiny-patch16-224,backend.processor=WinKawaks/vit-tiny-patch16-224
+    id: ???
+    num: ???
+    config_name: image_classification
+    env_set:
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+    env_copy: []
+    config:
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+        item_sep: ','
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+  runtime:
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+    version_base: '1.3'
+    cwd: /
+    config_sources:
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+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=WinKawaks/vit-tiny-patch16-224
+- backend.processor=WinKawaks/vit-tiny-patch16-224

image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/benchmark_report.json

@@ -0,0 +1,107 @@
+{
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+}

image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/cli.log

@@ -0,0 +1,113 @@
+[2024-12-07 06:05:06,630][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:05:06,630][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:05:06,642][device-isolation][INFO] - 	+ Launched device(s) isolation process 674
+[2024-12-07 06:05:06,643][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:05:06,649][process][INFO] - 	+ Launched benchmark in isolated process 675.
+[PROC-0][2024-12-07 06:05:09,305][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:05:10,208][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:05:10,208][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:05:10,688][pytorch][INFO] - 	+ Using AutoModel class AutoModelForImageClassification
+[PROC-0][2024-12-07 06:05:10,688][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:05:10,689][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:05:10,689][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:05:10,689][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:05:10,689][pytorch][INFO] - 	+ Creating no weights model state dict
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+[PROC-0][2024-12-07 06:05:10,691][pytorch][INFO] - 	+ Saving no weights model pretrained config
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+[PROC-0][2024-12-07 06:05:10,695][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:05:10,863][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:05:10,869][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:05:10,869][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:05:13,479][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:05:13,479][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:05:17,649][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 06:05:24,134][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 06:05:24,135][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 06:05:24,135][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 06:05:24,135][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 06:05:24,427][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 06:05:24,428][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-07 06:05:51,735][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:05:51,736][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-07 06:06:17,976][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:06:17,976][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-07 06:06:44,367][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:06:44,368][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-07 06:07:10,544][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:07:10,545][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-07 06:07:36,838][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:07:36,839][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-07 06:08:07,345][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:08:07,345][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-07 06:08:35,256][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:08:35,257][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-07 06:09:01,743][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:09:01,744][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-07 06:09:29,241][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:09:29,242][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-07 06:09:56,638][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ CPU: 0.000288 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ GPU: 0.000479 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ total: 0.000772 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ CPU: 0.000322 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ GPU: 0.000552 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ total: 0.000880 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ CPU: 0.000310 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ GPU: 0.000521 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ total: 0.000837 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ CPU: 0.000312 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ GPU: 0.000520 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ total: 0.000837 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ CPU: 0.000309 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ GPU: 0.000508 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ total: 0.000823 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ CPU: 0.000310 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ GPU: 0.000512 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ total: 0.000828 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ CPU: 0.000360 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ GPU: 0.000592 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ total: 0.000958 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ CPU: 0.000313 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ GPU: 0.000516 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ total: 0.000834 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ CPU: 0.000325 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ GPU: 0.000532 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ total: 0.000863 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ CPU: 0.000323 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ GPU: 0.000533 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ total: 0.000862 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 			+ CPU: 0.000077 (kWh)
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 			+ GPU: 0.000128 (kWh)
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 			+ total: 0.000205 (kWh)
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 		+ forward energy efficiency: 1294989.406415 (samples/kWh)
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 		+ preprocess energy efficiency: 4866682.610703 (samples/kWh)
+[2024-12-07 06:09:57,358][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-07 06:09:57,404][datasets][INFO] - PyTorch version 2.4.0 available.

image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "image_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "image-classification",
+        "model": "WinKawaks/vit-tiny-patch16-224",
+        "processor": "WinKawaks/vit-tiny-patch16-224",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/image_classification",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}

image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:09:56",
+    "project_name": "codecarbon",
+    "run_id": "b311f965-506c-43d6-9dbb-d13cb8595e0d",
+    "duration": -1733393392.9414692,
+    "emissions": 0.00031829046416117406,
+    "emissions_rate": 1.1619229671186078e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 70.06460857296656,
+    "ram_power": 0.751798152923584,
+    "cpu_energy": 0.0003234175212748799,
+    "gpu_energy": 0.0005331348709518569,
+    "ram_energy": 5.709383498157549e-06,
+    "energy_consumed": 0.0008622617757248954,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:05:24",
+    "project_name": "codecarbon",
+    "run_id": "b311f965-506c-43d6-9dbb-d13cb8595e0d",
+    "duration": -1733393413.8530831,
+    "emissions": 7.584928120829092e-05,
+    "emissions_rate": 1.1701695823980396e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 71.0711882800841,
+    "ram_power": 0.5384030342102051,
+    "cpu_energy": 7.654690115844764e-05,
+    "gpu_energy": 0.00012796260237002421,
+    "ram_energy": 9.692753425157112e-07,
+    "energy_consumed": 0.00020547877887098755,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: image-classification
+  model: google/vit-base-patch16-224
+  processor: google/vit-base-patch16-224
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/image_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: image_classification
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null

image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
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image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/overrides.yaml

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+- backend.processor=google/vit-base-patch16-224

image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/benchmark_report.json

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image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/cli.log

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image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/experiment_config.json

@@ -0,0 +1,107 @@
+{
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+}

image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:21:26",
+    "project_name": "codecarbon",
+    "run_id": "46d0333d-2e22-48c6-971d-c3bac025b79e",
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+    "codecarbon_version": "2.5.1",
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+    "cpu_model": "AMD EPYC 7R32",
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+    "gpu_model": "1 x NVIDIA A10G",
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+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:16:54",
+    "project_name": "codecarbon",
+    "run_id": "46d0333d-2e22-48c6-971d-c3bac025b79e",
+    "duration": -1733393420.3251574,
+    "emissions": 5.2276560675210465e-08,
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+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
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+    "cpu_model": "AMD EPYC 7R32",
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+    "gpu_model": "1 x NVIDIA A10G",
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+}

sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: sentence-similarity
+  model: sentence-transformers/bert-base-nli-mean-tokens
+  processor: sentence-transformers/bert-base-nli-mean-tokens
+  library: transformers
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/sentence_similarity
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: sentence_similarity_udever-bloom-7b1
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null

sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58
+    - hydra.mode=RUN
+    task:
+    - backend.model=sentence-transformers/bert-base-nli-mean-tokens
+    - backend.processor=sentence-transformers/bert-base-nli-mean-tokens
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=sentence-transformers/bert-base-nli-mean-tokens,backend.processor=sentence-transformers/bert-base-nli-mean-tokens
+    id: ???
+    num: ???
+    config_name: sentence_similarity
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=sentence-transformers/bert-base-nli-mean-tokens
+- backend.processor=sentence-transformers/bert-base-nli-mean-tokens

sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/benchmark_report.json

@@ -0,0 +1,107 @@
+{
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sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/cli.log

@@ -0,0 +1,113 @@
+[2024-12-07 06:10:01,230][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:10:01,231][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:10:01,243][device-isolation][INFO] - 	+ Launched device(s) isolation process 944
+[2024-12-07 06:10:01,243][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:10:01,250][process][INFO] - 	+ Launched benchmark in isolated process 945.
+[PROC-0][2024-12-07 06:10:03,983][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:10:04,904][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:10:04,904][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:10:05,544][pytorch][INFO] - 	+ Using AutoModel class AutoModel
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+[PROC-0][2024-12-07 06:10:05,545][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:10:05,545][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:10:05,545][pytorch][INFO] - 	+ Creating no weights model directory
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+[PROC-0][2024-12-07 06:10:05,844][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:10:05,850][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:10:05,850][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:10:07,912][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:10:07,912][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:10:12,092][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 06:10:12,259][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 06:10:12,259][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 06:10:12,259][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 06:10:12,260][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 06:10:12,927][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 06:10:12,927][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-07 06:10:18,320][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:18,320][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-07 06:10:23,849][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:23,850][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-07 06:10:29,379][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:29,379][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-07 06:10:34,973][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:34,974][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-07 06:10:40,562][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:40,562][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-07 06:10:46,099][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:46,099][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-07 06:10:51,489][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:51,489][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-07 06:10:56,932][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:56,932][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-07 06:11:02,353][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:11:02,354][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-07 06:11:07,783][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:11:07,783][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-07 06:11:07,783][energy][INFO] - 			+ CPU: 0.000058 (kWh)
+[PROC-0][2024-12-07 06:11:07,783][energy][INFO] - 			+ GPU: 0.000159 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ total: 0.000218 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ CPU: 0.000064 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ GPU: 0.000173 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ total: 0.000237 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ CPU: 0.000065 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ GPU: 0.000175 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ total: 0.000241 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ CPU: 0.000065 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ GPU: 0.000176 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ total: 0.000242 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ CPU: 0.000066 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ GPU: 0.000178 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ total: 0.000245 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ CPU: 0.000066 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ GPU: 0.000179 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ total: 0.000245 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ CPU: 0.000065 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ GPU: 0.000179 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ total: 0.000245 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ CPU: 0.000064 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ GPU: 0.000175 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ total: 0.000239 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ CPU: 0.000064 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ GPU: 0.000175 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ total: 0.000240 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ CPU: 0.000064 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ GPU: 0.000179 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ total: 0.000243 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ CPU: 0.000002 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ GPU: 0.000002 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ total: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 		+ forward energy efficiency: 4595131.105743 (samples/kWh)
+[PROC-0][2024-12-07 06:11:07,789][energy][INFO] - 		+ preprocess energy efficiency: 262354251.383482 (samples/kWh)
+[2024-12-07 06:11:08,433][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-07 06:11:08,479][datasets][INFO] - PyTorch version 2.4.0 available.

sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/error.log

@@ -0,0 +1,178 @@
+/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
+  warnings.warn(
+
+
+
+
+
+
+
+[codecarbon INFO @ 06:10:07] [setup] RAM Tracking...
+[codecarbon INFO @ 06:10:07] [setup] GPU Tracking...
+[codecarbon INFO @ 06:10:07] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 06:10:07] GPU available. Starting setup
+[codecarbon INFO @ 06:10:07] [setup] CPU Tracking...
+[codecarbon DEBUG @ 06:10:07] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 06:10:07] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 06:10:07] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 06:10:07] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 06:10:09] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 06:10:09] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 06:10:09] >>> Tracker's metadata:
+[codecarbon INFO @ 06:10:09]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 06:10:09]   Python version: 3.9.20
+[codecarbon INFO @ 06:10:09]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 06:10:09]   Available RAM : 186.705 GB
+[codecarbon INFO @ 06:10:09]   CPU count: 48
+[codecarbon INFO @ 06:10:09]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 06:10:09]   GPU count: 1
+[codecarbon INFO @ 06:10:09]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 06:10:10] Not running on AWS
+[codecarbon DEBUG @ 06:10:11] Not running on Azure
+[codecarbon DEBUG @ 06:10:12] Not running on GCP
+[codecarbon INFO @ 06:10:12] Saving emissions data to file /runs/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/codecarbon.csv
+[codecarbon DEBUG @ 06:10:12] EmissionsData(timestamp='2024-12-07T06:10:12', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.002482334995875135, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
+
+[codecarbon INFO @ 06:10:12] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.2677788734436035 W
+[codecarbon DEBUG @ 06:10:12] RAM : 0.27 W during 0.16 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:10:12] Energy consumed for all GPUs : 0.000002 kWh. Total GPU Power : 40.61219768306994 W
+[codecarbon DEBUG @ 06:10:12] GPU : 40.61 W during 0.16 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:10:12] Energy consumed for all CPUs : 0.000002 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:12] CPU : 42.50 W during 0.17 s [measurement time: 0.0001]
+[codecarbon INFO @ 06:10:12] 0.000004 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:12] last_duration=0.16266650799661875
+------------------------
+[codecarbon DEBUG @ 06:10:12] EmissionsData(timestamp='2024-12-07T06:10:12', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.1657926649786532, emissions=1.4070074181918935e-06, emissions_rate=8.486548053094231e-06, cpu_power=42.5, gpu_power=40.61219768306994, ram_power=0.2677788734436035, cpu_energy=1.9556499311066647e-06, gpu_energy=1.8438903641726512e-06, ram_energy=1.2099861976244407e-08, energy_consumed=3.81164015725556e-06, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:12] EmissionsData(timestamp='2024-12-07T06:10:12', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.00221453100675717, emissions=1.4070074181918935e-06, emissions_rate=0.0006353523224098963, cpu_power=42.5, gpu_power=40.61219768306994, ram_power=0.2677788734436035, cpu_energy=1.9556499311066647e-06, gpu_energy=1.8438903641726512e-06, ram_energy=1.2099861976244407e-08, energy_consumed=3.81164015725556e-06, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:18] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:18] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.3415718078613281 W
+[codecarbon DEBUG @ 06:10:18] RAM : 0.34 W during 5.39 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:18] Energy consumed for all GPUs : 0.000174 kWh. Total GPU Power : 115.30912870229479 W
+[codecarbon DEBUG @ 06:10:18] GPU : 115.31 W during 5.39 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:10:18] Energy consumed for all CPUs : 0.000066 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:18] CPU : 42.50 W during 5.39 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:18] 0.000241 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:18] last_duration=5.38887751600123
+------------------------
+[codecarbon DEBUG @ 06:10:18] EmissionsData(timestamp='2024-12-07T06:10:18', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.3921635360165965, emissions=8.881931964789958e-05, emissions_rate=1.6471926167416264e-05, cpu_power=42.5, gpu_power=115.30912870229479, ram_power=0.3415718078613281, cpu_energy=6.561185483967872e-05, gpu_energy=0.00017447986180618713, ram_energy=5.234223596623469e-07, energy_consumed=0.0002406151390055282, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:18] EmissionsData(timestamp='2024-12-07T06:10:18', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.0020258680160623044, emissions=8.881931964789958e-05, emissions_rate=0.04384259929259281, cpu_power=42.5, gpu_power=115.30912870229479, ram_power=0.3415718078613281, cpu_energy=6.561185483967872e-05, gpu_energy=0.00017447986180618713, ram_energy=5.234223596623469e-07, energy_consumed=0.0002406151390055282, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:23] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:23] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.3416590690612793 W
+[codecarbon DEBUG @ 06:10:23] RAM : 0.34 W during 5.53 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:23] Energy consumed for all GPUs : 0.000350 kWh. Total GPU Power : 114.08938471435098 W
+[codecarbon DEBUG @ 06:10:23] GPU : 114.09 W during 5.53 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:10:23] Energy consumed for all CPUs : 0.000131 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:23] CPU : 42.50 W during 5.53 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:23] 0.000482 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:23] last_duration=5.525269418023527
+------------------------
+[codecarbon DEBUG @ 06:10:23] EmissionsData(timestamp='2024-12-07T06:10:23', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.528453146020183, emissions=0.00017775119321401719, emissions_rate=3.215206650380614e-05, cpu_power=42.5, gpu_power=114.08938471435098, ram_power=0.3416590690612793, cpu_energy=0.00013087710362120157, gpu_energy=0.0003496102796880507, ram_energy=1.047807830895976e-06, energy_consumed=0.00048153519114014825, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:23] EmissionsData(timestamp='2024-12-07T06:10:23', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.006460198987042531, emissions=0.00017775119321401719, emissions_rate=0.027514817046741063, cpu_power=42.5, gpu_power=114.08938471435098, ram_power=0.3416590690612793, cpu_energy=0.00013087710362120157, gpu_energy=0.0003496102796880507, ram_energy=1.047807830895976e-06, energy_consumed=0.00048153519114014825, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:29] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:29] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:29] RAM : 0.34 W during 5.53 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:29] Energy consumed for all GPUs : 0.000525 kWh. Total GPU Power : 114.50733413763714 W
+[codecarbon DEBUG @ 06:10:29] GPU : 114.51 W during 5.53 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:10:29] Energy consumed for all CPUs : 0.000196 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:29] CPU : 42.50 W during 5.53 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:29] 0.000723 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:29] last_duration=5.525112133997027
+------------------------
+[codecarbon DEBUG @ 06:10:29] EmissionsData(timestamp='2024-12-07T06:10:29', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.528263721993426, emissions=0.0002669166395736923, emissions_rate=4.8282182796707346e-05, cpu_power=42.5, gpu_power=114.50733413763714, ram_power=0.34168338775634766, cpu_energy=0.00019614008756557776, gpu_energy=0.0005253756980780899, ram_energy=1.572215801423746e-06, energy_consumed=0.0007230880014450914, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:29] EmissionsData(timestamp='2024-12-07T06:10:29', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.0020149170013610274, emissions=0.0002669166395736923, emissions_rate=0.13247029003844657, cpu_power=42.5, gpu_power=114.50733413763714, ram_power=0.34168338775634766, cpu_energy=0.00019614008756557776, gpu_energy=0.0005253756980780899, ram_energy=1.572215801423746e-06, energy_consumed=0.0007230880014450914, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:34] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:34] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:34] RAM : 0.34 W during 5.59 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:34] Energy consumed for all GPUs : 0.000703 kWh. Total GPU Power : 114.66394570645916 W
+[codecarbon DEBUG @ 06:10:34] GPU : 114.66 W during 5.59 s [measurement time: 0.0059]
+[codecarbon INFO @ 06:10:34] Energy consumed for all CPUs : 0.000262 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:34] CPU : 42.50 W during 5.59 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:34] 0.000968 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:34] last_duration=5.586633354017977
+------------------------
+[codecarbon DEBUG @ 06:10:34] EmissionsData(timestamp='2024-12-07T06:10:34', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.593534631014336, emissions=0.00035718139983907714, emissions_rate=6.385611664199272e-05, cpu_power=42.5, gpu_power=114.66394570645916, ram_power=0.34168338775634766, cpu_energy=0.0002621736499776388, gpu_energy=0.0007033427848961438, ram_energy=2.102462829641687e-06, energy_consumed=0.0009676188977034244, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:34] EmissionsData(timestamp='2024-12-07T06:10:34', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.0020358879992272705, emissions=0.00035718139983907714, emissions_rate=0.17544255871376363, cpu_power=42.5, gpu_power=114.66394570645916, ram_power=0.34168338775634766, cpu_energy=0.0002621736499776388, gpu_energy=0.0007033427848961438, ram_energy=2.102462829641687e-06, energy_consumed=0.0009676188977034244, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:40] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:40] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:40] RAM : 0.34 W during 5.58 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:10:40] Energy consumed for all GPUs : 0.000882 kWh. Total GPU Power : 115.10660681789726 W
+[codecarbon DEBUG @ 06:10:40] GPU : 115.11 W during 5.59 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:10:40] Energy consumed for all CPUs : 0.000328 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:40] CPU : 42.50 W during 5.59 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:40] 0.001213 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:40] last_duration=5.584514144982677
+------------------------
+[codecarbon DEBUG @ 06:10:40] EmissionsData(timestamp='2024-12-07T06:10:40', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.587722925003618, emissions=0.0004476491120165557, emissions_rate=8.01129758981859e-05, cpu_power=42.5, gpu_power=115.10660681789726, ram_power=0.34168338775634766, cpu_energy=0.00032813860704767044, gpu_energy=0.00088192848332036, ram_energy=2.632508554330701e-06, energy_consumed=0.0012126995989223612, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:40] EmissionsData(timestamp='2024-12-07T06:10:40', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.0020298569870647043, emissions=0.0004476491120165557, emissions_rate=0.2205323403910752, cpu_power=42.5, gpu_power=115.10660681789726, ram_power=0.34168338775634766, cpu_energy=0.00032813860704767044, gpu_energy=0.00088192848332036, ram_energy=2.632508554330701e-06, energy_consumed=0.0012126995989223612, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:46] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:46] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:46] RAM : 0.34 W during 5.53 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:46] Energy consumed for all GPUs : 0.001061 kWh. Total GPU Power : 116.62129331846901 W
+[codecarbon DEBUG @ 06:10:46] GPU : 116.62 W during 5.53 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:10:46] Energy consumed for all CPUs : 0.000393 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:46] CPU : 42.50 W during 5.54 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:46] 0.001458 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:46] last_duration=5.532675098977052
+------------------------
+[codecarbon DEBUG @ 06:10:46] EmissionsData(timestamp='2024-12-07T06:10:46', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.535838896990754, emissions=0.0005381359093476812, emissions_rate=9.720945991405356e-05, cpu_power=42.5, gpu_power=116.62129331846901, ram_power=0.34168338775634766, cpu_energy=0.00039349101955103835, gpu_energy=0.0010611833489462263, ram_energy=3.1576340992636036e-06, energy_consumed=0.0014578320025965283, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:46] EmissionsData(timestamp='2024-12-07T06:10:46', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.002027657988946885, emissions=0.0005381359093476812, emissions_rate=0.2653977703740736, cpu_power=42.5, gpu_power=116.62129331846901, ram_power=0.34168338775634766, cpu_energy=0.00039349101955103835, gpu_energy=0.0010611833489462263, ram_energy=3.1576340992636036e-06, energy_consumed=0.0014578320025965283, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:51] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:51] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:51] RAM : 0.34 W during 5.38 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:51] Energy consumed for all GPUs : 0.001236 kWh. Total GPU Power : 117.18411053858756 W
+[codecarbon DEBUG @ 06:10:51] GPU : 117.18 W during 5.39 s [measurement time: 0.0037]
+[codecarbon INFO @ 06:10:51] Energy consumed for all CPUs : 0.000457 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:51] CPU : 42.50 W during 5.39 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:51] 0.001697 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:51] EmissionsData(timestamp='2024-12-07T06:10:51', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.389227389008738, emissions=0.0006265187749095551, emissions_rate=0.00011625391353635075, cpu_power=42.5, gpu_power=117.18411053858756, ram_power=0.34168338775634766, cpu_energy=0.00045711285309183347, gpu_energy=0.0012364832114082347, ram_energy=3.6687052824912656e-06, energy_consumed=0.0016972647697825593, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon INFO @ 06:10:51] 0.016406 g.CO2eq/s mean an estimation of 517.3823484416522 kg.CO2eq/year
+[codecarbon DEBUG @ 06:10:51] last_duration=5.384598153992556
+------------------------
+[codecarbon DEBUG @ 06:10:51] EmissionsData(timestamp='2024-12-07T06:10:51', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.389564844983397, emissions=0.0006265187749095551, emissions_rate=0.00011624663454837515, cpu_power=42.5, gpu_power=117.18411053858756, ram_power=0.34168338775634766, cpu_energy=0.00045711285309183347, gpu_energy=0.0012364832114082347, ram_energy=3.6687052824912656e-06, energy_consumed=0.0016972647697825593, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:51] EmissionsData(timestamp='2024-12-07T06:10:51', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.003103366994764656, emissions=0.0006265187749095551, emissions_rate=0.20188355936197203, cpu_power=42.5, gpu_power=117.18411053858756, ram_power=0.34168338775634766, cpu_energy=0.00045711285309183347, gpu_energy=0.0012364832114082347, ram_energy=3.6687052824912656e-06, energy_consumed=0.0016972647697825593, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:56] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:56] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:56] RAM : 0.34 W during 5.44 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:56] Energy consumed for all GPUs : 0.001411 kWh. Total GPU Power : 115.58506166044792 W
+[codecarbon DEBUG @ 06:10:56] GPU : 115.59 W during 5.44 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:10:56] Energy consumed for all CPUs : 0.000521 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:56] CPU : 42.50 W during 5.44 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:56] 0.001937 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:56] last_duration=5.4391074090090115
+------------------------
+[codecarbon DEBUG @ 06:10:56] EmissionsData(timestamp='2024-12-07T06:10:56', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.442248937004479, emissions=0.0007148973439093629, emissions_rate=0.00013136064744271998, cpu_power=42.5, gpu_power=115.58506166044792, ram_power=0.34168338775634766, cpu_energy=0.0005213603739701487, gpu_energy=0.0014111405733561178, ram_energy=4.184950081439409e-06, energy_consumed=0.0019366858974077057, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:56] EmissionsData(timestamp='2024-12-07T06:10:56', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.002036777004832402, emissions=0.0007148973439093629, emissions_rate=0.3509944103911311, cpu_power=42.5, gpu_power=115.58506166044792, ram_power=0.34168338775634766, cpu_energy=0.0005213603739701487, gpu_energy=0.0014111405733561178, ram_energy=4.184950081439409e-06, energy_consumed=0.0019366858974077057, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:11:02] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:11:02] Energy consumed for RAM : 0.000005 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:11:02] RAM : 0.34 W during 5.42 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:11:02] Energy consumed for all GPUs : 0.001586 kWh. Total GPU Power : 116.33827522121558 W
+[codecarbon DEBUG @ 06:11:02] GPU : 116.34 W during 5.42 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:11:02] Energy consumed for all CPUs : 0.000585 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:11:02] CPU : 42.50 W during 5.42 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:11:02] 0.002176 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:11:02] last_duration=5.4171664439782035
+------------------------
+[codecarbon DEBUG @ 06:11:02] EmissionsData(timestamp='2024-12-07T06:11:02', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.420353812980466, emissions=0.000803338674124654, emissions_rate=0.0001482077926722879, cpu_power=42.5, gpu_power=116.33827522121558, ram_power=0.34168338775634766, cpu_energy=0.0005853494442736418, gpu_energy=0.0015862284912040447, ram_energy=4.69911223319916e-06, energy_consumed=0.0021762770477108855, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:11:02] EmissionsData(timestamp='2024-12-07T06:11:02', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.0020206469926051795, emissions=0.000803338674124654, emissions_rate=0.39756507547561565, cpu_power=42.5, gpu_power=116.33827522121558, ram_power=0.34168338775634766, cpu_energy=0.0005853494442736418, gpu_energy=0.0015862284912040447, ram_energy=4.69911223319916e-06, energy_consumed=0.0021762770477108855, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:11:07] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:11:07] Energy consumed for RAM : 0.000005 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:11:07] RAM : 0.34 W during 5.42 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:11:07] Energy consumed for all GPUs : 0.001765 kWh. Total GPU Power : 118.55366026700273 W
+[codecarbon DEBUG @ 06:11:07] GPU : 118.55 W during 5.42 s [measurement time: 0.0053]
+[codecarbon INFO @ 06:11:07] Energy consumed for all CPUs : 0.000649 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:11:07] CPU : 42.50 W during 5.43 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:11:07] 0.002419 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:11:07] last_duration=5.422210680990247
+------------------------
+[codecarbon DEBUG @ 06:11:07] EmissionsData(timestamp='2024-12-07T06:11:07', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.428357224009233, emissions=0.0008931061862608407, emissions_rate=0.00016452605261693104, cpu_power=42.5, gpu_power=118.55366026700273, ram_power=0.34168338775634766, cpu_energy=0.0006494329356583775, gpu_energy=0.001764814189628261, ram_energy=5.213753334618298e-06, energy_consumed=0.0024194608786212565, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)

sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "sentence_similarity_udever-bloom-7b1",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "sentence-similarity",
+        "model": "sentence-transformers/bert-base-nli-mean-tokens",
+        "processor": "sentence-transformers/bert-base-nli-mean-tokens",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
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+}

sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
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+}

sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
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+    "project_name": "codecarbon",
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+}

summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/config.yaml

@@ -0,0 +1,96 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: summarization
+  model: facebook/bart-large-cnn
+  processor: facebook/bart-large-cnn
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
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+  peft_config: {}
+launcher:
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+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/summarization
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
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+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
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+  system: Linux
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+  optimum_commit: null
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summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
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+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
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+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
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+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
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+    override_dirname: backend.model=facebook/bart-large-cnn,backend.processor=facebook/bart-large-cnn
+    id: ???
+    num: ???
+    config_name: summarization
+    env_set:
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+    env_copy: []
+    config:
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+    version_base: '1.3'
+    cwd: /
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+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14
+    choices:
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+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=facebook/bart-large-cnn
+- backend.processor=facebook/bart-large-cnn

summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/benchmark_report.json

@@ -0,0 +1,107 @@
+{
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summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/cli.log

@@ -0,0 +1,114 @@
+[2024-12-07 05:59:17,596][energy_star][WARNING] - Setting `min_new_tokens` without `max_new_tokens` results in non-deterministic behavior. Setting `max_new_tokens` to `min_new_tokens`.
+[2024-12-07 05:59:17,599][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 05:59:17,599][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 05:59:17,609][device-isolation][INFO] - 	+ Launched device(s) isolation process 181
+[2024-12-07 05:59:17,609][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 05:59:17,614][process][INFO] - 	+ Launched benchmark in isolated process 182.
+[PROC-0][2024-12-07 05:59:20,266][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 05:59:21,219][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 05:59:21,219][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Using AutoModel class AutoModelForSeq2SeqLM
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 05:59:22,013][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 05:59:22,014][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 05:59:22,015][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 05:59:22,015][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 05:59:22,209][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 05:59:22,215][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 05:59:22,215][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 05:59:23,693][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 05:59:23,693][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 05:59:27,876][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 05:59:28,829][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 05:59:28,830][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 05:59:28,830][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 05:59:28,830][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 05:59:29,771][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 05:59:29,771][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-07 06:00:01,298][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:00:01,311][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-07 06:00:33,050][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:00:33,065][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-07 06:01:04,724][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:01:04,740][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-07 06:01:36,455][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:01:36,470][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-07 06:02:08,244][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:02:08,260][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-07 06:02:40,066][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:02:40,078][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-07 06:03:11,897][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:03:11,911][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-07 06:03:43,727][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:03:43,740][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-07 06:04:15,557][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:04:15,571][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-07 06:04:47,411][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 			+ CPU: 0.000337 (kWh)
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 			+ GPU: 0.002303 (kWh)
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 			+ total: 0.002643 (kWh)
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ CPU: 0.000372 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ GPU: 0.002520 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ total: 0.002895 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ CPU: 0.000375 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ GPU: 0.002548 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ total: 0.002926 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ CPU: 0.000374 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ GPU: 0.002556 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ total: 0.002932 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ CPU: 0.000374 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ GPU: 0.002555 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ total: 0.002932 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ CPU: 0.000375 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ GPU: 0.002562 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ total: 0.002940 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ CPU: 0.000375 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ GPU: 0.002571 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ total: 0.002949 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ CPU: 0.000376 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ GPU: 0.002578 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ total: 0.002957 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ CPU: 0.000376 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ GPU: 0.002569 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ total: 0.002948 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ CPU: 0.000376 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ GPU: 0.002575 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 			+ total: 0.002954 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 			+ CPU: 0.000011 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 			+ GPU: 0.000018 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 			+ total: 0.000030 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 		+ forward energy efficiency: 378295.517969 (samples/kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 		+ preprocess energy efficiency: 33838645.810365 (samples/kWh)
+[2024-12-07 06:04:48,082][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-07 06:04:48,132][datasets][INFO] - PyTorch version 2.4.0 available.

summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/experiment_config.json

@@ -0,0 +1,111 @@
+{
+    "experiment_name": "summarization",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "summarization",
+        "model": "facebook/bart-large-cnn",
+        "processor": "facebook/bart-large-cnn",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/summarization",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {
+            "max_length": 10,
+            "min_new_tokens": 10,
+            "max_new_tokens": 10
+        },
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}

summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:04:47",
+    "project_name": "codecarbon",
+    "run_id": "d9969f35-5239-46e5-99c5-b3063a70b123",
+    "duration": -1733393388.4993432,
+    "emissions": 0.0010904398446305794,
+    "emissions_rate": 3.4252272054628185e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 291.16559529099845,
+    "ram_power": 0.3577909469604492,
+    "cpu_energy": 0.00037588733435677544,
+    "gpu_energy": 0.00257499428221597,
+    "ram_energy": 3.1641454649935176e-06,
+    "energy_consumed": 0.002954045762037741,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}