Upload folder using huggingface_hub

automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-english/2024-12-04-15-35-05/.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-english
+  processor: jonatasgrosman/wav2vec2-large-xlsr-53-english
+  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-english/2024-12-04-15-35-05/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-english/2024-12-04-15-35-05
+  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-english/2024-12-04-15-35-05
+    - hydra.mode=RUN
+    task:
+    - backend.model=jonatasgrosman/wav2vec2-large-xlsr-53-english
+    - backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-english
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=jonatasgrosman/wav2vec2-large-xlsr-53-english,backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-english
+    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-english/2024-12-04-15-35-05
+    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-english/2024-12-04-15-35-05/.hydra/overrides.yaml

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

automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-english/2024-12-04-15-35-05/cli.log

@@ -0,0 +1,25 @@
+[2024-12-04 15:35:08,566][launcher][INFO] - ََAllocating process launcher
+[2024-12-04 15:35:08,566][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-04 15:35:08,576][device-isolation][INFO] - 	+ Launched device(s) isolation process 181
+[2024-12-04 15:35:08,576][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-04 15:35:08,581][process][INFO] - 	+ Launched benchmark in isolated process 182.
+[PROC-0][2024-12-04 15:35:11,345][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-04 15:35:12,266][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-04 15:35:12,266][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-04 15:35:12,688][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCTC
+[PROC-0][2024-12-04 15:35:12,689][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-04 15:35:12,689][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-04 15:35:12,689][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-04 15:35:12,689][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-04 15:35:12,689][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-04 15:35:12,691][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-04 15:35:12,692][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-04 15:35:12,693][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-04 15:35:12,693][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-04 15:35:12,993][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-04 15:35:12,999][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-04 15:35:13,000][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-04 15:35:18,026][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-04 15:35:18,026][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-04 15:35:22,200][energy_star][INFO] - 	+ Preprocessing dataset
+[2024-12-04 15:35:28,653][experiment][ERROR] - Error during experiment

automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-english/2024-12-04-15-35-05/error.log

@@ -0,0 +1,93 @@
+/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 @ 15:35:18] [setup] RAM Tracking...
+[codecarbon INFO @ 15:35:18] [setup] GPU Tracking...
+[codecarbon INFO @ 15:35:18] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 15:35:18] GPU available. Starting setup
+[codecarbon INFO @ 15:35:18] [setup] CPU Tracking...
+[codecarbon DEBUG @ 15:35:18] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 15:35:18] 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 @ 15:35:18] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 15:35:18] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 15:35:19] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 15:35:19] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 15:35:19] >>> Tracker's metadata:
+[codecarbon INFO @ 15:35:19]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 15:35:19]   Python version: 3.9.20
+[codecarbon INFO @ 15:35:19]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 15:35:19]   Available RAM : 186.705 GB
+[codecarbon INFO @ 15:35:19]   CPU count: 48
+[codecarbon INFO @ 15:35:19]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 15:35:19]   GPU count: 1
+[codecarbon INFO @ 15:35:19]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 15:35:20] Not running on AWS
+[codecarbon DEBUG @ 15:35:21] Not running on Azure
+[codecarbon DEBUG @ 15:35:22] Not running on GCP
+[codecarbon INFO @ 15:35:22] Saving emissions data to file /runs/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-english/2024-12-04-15-35-05/codecarbon.csv
+[codecarbon DEBUG @ 15:35:22] EmissionsData(timestamp='2024-12-04T15:35:22', project_name='codecarbon', run_id='4002c2cc-d51d-4713-bce1-ee1ad4edb5ec', duration=0.0021653330040862784, 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-english', 'backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-english']
+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-english/2024-12-04-15-35-05/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-english",
+        "processor": "jonatasgrosman/wav2vec2-large-xlsr-53-english",
+        "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/timm/resnet50.a1_in1k/2024-12-04-17-13-03/.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: timm/resnet50.a1_in1k
+  processor: timm/resnet50.a1_in1k
+  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/timm/resnet50.a1_in1k/2024-12-04-17-13-03/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/image_classification/timm/resnet50.a1_in1k/2024-12-04-17-13-03
+  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:
+    hydra:
+    - hydra.run.dir=/runs/image_classification/timm/resnet50.a1_in1k/2024-12-04-17-13-03
+    - hydra.mode=RUN
+    task:
+    - backend.model=timm/resnet50.a1_in1k
+    - backend.processor=timm/resnet50.a1_in1k
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=timm/resnet50.a1_in1k,backend.processor=timm/resnet50.a1_in1k
+    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/timm/resnet50.a1_in1k/2024-12-04-17-13-03
+    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/timm/resnet50.a1_in1k/2024-12-04-17-13-03/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=timm/resnet50.a1_in1k
+- backend.processor=timm/resnet50.a1_in1k

image_classification/timm/resnet50.a1_in1k/2024-12-04-17-13-03/cli.log

@@ -0,0 +1,9 @@
+[2024-12-04 17:13:06,484][launcher][INFO] - ََAllocating process launcher
+[2024-12-04 17:13:06,484][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-04 17:13:06,497][device-isolation][INFO] - 	+ Launched device(s) isolation process 986
+[2024-12-04 17:13:06,498][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-04 17:13:06,504][process][INFO] - 	+ Launched benchmark in isolated process 987.
+[PROC-0][2024-12-04 17:13:09,182][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-04 17:13:10,172][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-04 17:13:10,172][backend][INFO] - 	+ Setting random seed to 42
+[2024-12-04 17:13:10,706][experiment][ERROR] - Error during experiment

image_classification/timm/resnet50.a1_in1k/2024-12-04-17-13-03/error.log

@@ -0,0 +1,32 @@
+Error executing job with overrides: ['backend.model=timm/resnet50.a1_in1k', 'backend.processor=timm/resnet50.a1_in1k']
+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 55, in run
+    backend: Backend = backend_factory(backend_config)
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 45, in __init__
+    super().__init__(config)
+  File "/optimum-benchmark/optimum_benchmark/backends/base.py", line 54, in __init__
+    self.pretrained_config = get_timm_pretrained_config(self.config.model)
+  File "/optimum-benchmark/optimum_benchmark/backends/timm_utils.py", line 12, in get_timm_pretrained_config
+    model_source, model_name = timm.models.parse_model_name(model_name)
+NameError: name 'timm' is not defined
+
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

image_classification/timm/resnet50.a1_in1k/2024-12-04-17-13-03/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": "timm/resnet50.a1_in1k",
+        "processor": "timm/resnet50.a1_in1k",
+        "library": "timm",
+        "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
+    }
+}

text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24/.hydra/config.yaml

@@ -0,0 +1,96 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-generation
+  model: bigscience/bloomz-560m
+  processor: bigscience/bloomz-560m
+  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: false
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/text_generation
+  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_new_tokens: 10
+    min_new_tokens: 10
+  call_kwargs: {}
+experiment_name: text_generation
+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

text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24
+  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/text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24
+    - hydra.mode=RUN
+    task:
+    - backend.model=bigscience/bloomz-560m
+    - backend.processor=bigscience/bloomz-560m
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=bigscience/bloomz-560m,backend.processor=bigscience/bloomz-560m
+    id: ???
+    num: ???
+    config_name: text_generation
+    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/text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24
+    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

text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=bigscience/bloomz-560m
+- backend.processor=bigscience/bloomz-560m

text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24/benchmark_report.json

@@ -0,0 +1,203 @@
+{
+    "prefill": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.0003082951182833939,
+            "ram": 3.1850969165582464e-06,
+            "gpu": 0.001811276337908796,
+            "total": 0.0021227565531087484
+        },
+        "efficiency": {
+            "unit": "tokens/kWh",
+            "value": 91065082.2002653
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.0003429987985006948,
+                "ram": 3.542954712246048e-06,
+                "gpu": 0.001997280486711994,
+                "total": 0.002343822239924935
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00034366121815134854,
+                "ram": 3.5501402373248306e-06,
+                "gpu": 0.002026376065544011,
+                "total": 0.002373587423932685
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00034208863734233,
+                "ram": 3.5343963865605078e-06,
+                "gpu": 0.0020103096638020013,
+                "total": 0.0023559326975308914
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00034247366563189535,
+                "ram": 3.538371880745545e-06,
+                "gpu": 0.002014361333710024,
+                "total": 0.0023603733712226653
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00034193711197430185,
+                "ram": 3.5326911277494935e-06,
+                "gpu": 0.0020110554977319506,
+                "total": 0.0023565253008340017
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003427284664014071,
+                "ram": 3.541041700480612e-06,
+                "gpu": 0.0020142532780679234,
+                "total": 0.002360522786169812
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00034183093565275146,
+                "ram": 3.531765329011117e-06,
+                "gpu": 0.0020089163293540713,
+                "total": 0.002354279030335832
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00034218637264447774,
+                "ram": 3.5352872224273327e-06,
+                "gpu": 0.002010571608455969,
+                "total": 0.0023562932683228767
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00034304597653473214,
+                "ram": 3.5443205690369786e-06,
+                "gpu": 0.0020196391157100146,
+                "total": 0.002366229412813784
+            }
+        ]
+    },
+    "decode": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.0015752735088163188,
+            "ram": 1.6288348539985184e-05,
+            "gpu": 0.003964184199122589,
+            "total": 0.005555746056478895
+        },
+        "efficiency": {
+            "unit": "tokens/kWh",
+            "value": 1619944.45183551
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.0017516841623555145,
+                "ram": 1.8112295395436646e-05,
+                "gpu": 0.004435401603874012,
+                "total": 0.006205198061624966
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0017452471201590872,
+                "ram": 1.8046290018650998e-05,
+                "gpu": 0.004403079633571894,
+                "total": 0.006166373043749631
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0017454764441145717,
+                "ram": 1.8048288935674893e-05,
+                "gpu": 0.004411841585026166,
+                "total": 0.006175366318076415
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0017546621838340397,
+                "ram": 1.8143266360687642e-05,
+                "gpu": 0.004420565203115845,
+                "total": 0.006193370653310573
+            },
+            {
+                "unit": "kWh",
+                "cpu": -0.00034193711197430185,
+                "ram": -3.5326911277494935e-06,
+                "gpu": -0.0020110554977319506,
+                "total": -0.0023565253008340017
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0017451369265368472,
+                "ram": 1.804475479899136e-05,
+                "gpu": 0.00441268325236599,
+                "total": 0.006175864933701829
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0020869030950346965,
+                "ram": 2.157583443595883e-05,
+                "gpu": 0.0064130976304739296,
+                "total": 0.008521576559944594
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.001747071537846492,
+                "ram": 1.8064560154956028e-05,
+                "gpu": 0.004382076283436009,
+                "total": 0.006147212381437464
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.001746269038160391,
+                "ram": 1.805659913703533e-05,
+                "gpu": 0.0043722779422640246,
+                "total": 0.006136603579561441
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0017722216920958499,
+                "ram": 1.8324287290209603e-05,
+                "gpu": 0.004401874354829971,
+                "total": 0.00619242033421603
+            }
+        ]
+    },
+    "per_token": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": null,
+        "efficiency": null,
+        "measures": null
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 1.189836183752454e-05,
+            "ram": 8.778073359449114e-08,
+            "gpu": 1.8812515049981826e-05,
+            "total": 3.079865762110086e-05
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 32468947.585393377
+        },
+        "measures": null
+    }
+}

text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24/cli.log

@@ -0,0 +1,188 @@
+[2024-12-04 16:38:27,209][launcher][INFO] - ََAllocating process launcher
+[2024-12-04 16:38:27,209][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-04 16:38:27,223][process][INFO] - 	+ Launched benchmark in isolated process 800.
+[PROC-0][2024-12-04 16:38:29,734][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-04 16:38:30,650][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-04 16:38:30,651][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-04 16:38:32,113][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCausalLM
+[PROC-0][2024-12-04 16:38:32,113][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-04 16:38:32,114][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-04 16:38:32,114][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-04 16:38:32,114][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-04 16:38:32,114][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-04 16:38:32,133][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-04 16:38:32,134][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-04 16:38:32,135][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-04 16:38:32,135][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-04 16:38:32,417][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-04 16:38:32,424][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-04 16:38:32,424][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-04 16:38:33,147][energy_star][INFO] - 	+ Updating Text Generation kwargs with default values
+[PROC-0][2024-12-04 16:38:33,147][energy_star][INFO] - 	+ Initializing Text Generation report
+[PROC-0][2024-12-04 16:38:33,147][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-04 16:38:37,332][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-04 16:38:38,341][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-04 16:38:38,341][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-04 16:38:38,341][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-04 16:38:38,341][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-04 16:38:39,395][energy_star][INFO] - 	+ Additional warmup for Text Generation
+[PROC-0][2024-12-04 16:38:39,576][energy_star][INFO] - 	+ Running Text Generation energy tracking for 10 iterations
+[PROC-0][2024-12-04 16:38:39,576][energy_star][INFO] - 	+ Prefill iteration 1/10
+[PROC-0][2024-12-04 16:39:08,631][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:39:08,631][energy_star][INFO] - 	+ Prefill iteration 2/10
+[PROC-0][2024-12-04 16:39:37,742][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:39:37,742][energy_star][INFO] - 	+ Prefill iteration 3/10
+[PROC-0][2024-12-04 16:40:06,720][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:40:06,720][energy_star][INFO] - 	+ Prefill iteration 4/10
+[PROC-0][2024-12-04 16:40:35,730][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:40:35,731][energy_star][INFO] - 	+ Prefill iteration 5/10
+[PROC-0][2024-12-04 16:41:04,696][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:41:04,696][energy_star][INFO] - 	+ Prefill iteration 6/10
+[PROC-0][2024-12-04 16:41:33,728][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:41:33,728][energy_star][INFO] - 	+ Prefill iteration 7/10
+[PROC-0][2024-12-04 16:42:02,696][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:42:02,696][energy_star][INFO] - 	+ Prefill iteration 8/10
+[PROC-0][2024-12-04 16:42:31,652][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:42:31,652][energy_star][INFO] - 	+ Prefill iteration 9/10
+[PROC-0][2024-12-04 16:43:00,638][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:43:00,639][energy_star][INFO] - 	+ Prefill iteration 10/10
+[PROC-0][2024-12-04 16:43:29,697][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:43:29,698][energy_star][INFO] - 	+ Decoding iteration 1/10
+[PROC-0][2024-12-04 16:46:27,130][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:46:27,131][energy_star][INFO] - 	+ Decoding iteration 2/10
+[PROC-0][2024-12-04 16:49:24,074][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:49:24,075][energy_star][INFO] - 	+ Decoding iteration 3/10
+[PROC-0][2024-12-04 16:52:20,904][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:52:20,905][energy_star][INFO] - 	+ Decoding iteration 4/10
+[PROC-0][2024-12-04 16:55:18,545][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:55:18,545][energy_star][INFO] - 	+ Decoding iteration 5/10
+[PROC-0][2024-12-04 16:58:15,309][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:58:15,309][energy_star][INFO] - 	+ Decoding iteration 6/10
+[PROC-0][2024-12-04 17:01:12,164][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 17:01:12,165][energy_star][INFO] - 	+ Decoding iteration 7/10
+[PROC-0][2024-12-04 17:04:08,938][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 17:04:08,939][energy_star][INFO] - 	+ Decoding iteration 8/10
+[PROC-0][2024-12-04 17:07:05,881][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 17:07:05,882][energy_star][INFO] - 	+ Decoding iteration 9/10
+[PROC-0][2024-12-04 17:10:02,787][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 17:10:02,787][energy_star][INFO] - 	+ Decoding iteration 10/10
+[PROC-0][2024-12-04 17:13:01,964][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 17:13:01,964][energy][INFO] - 		+ prefill energy consumption:
+[PROC-0][2024-12-04 17:13:01,964][energy][INFO] - 			+ CPU: 0.000308 (kWh)
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 			+ GPU: 0.001811 (kWh)
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 			+ total: 0.002123 (kWh)
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 		+ prefill_iteration_1 energy consumption:
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 			+ CPU: 0.000343 (kWh)
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 			+ GPU: 0.001997 (kWh)
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 			+ total: 0.002344 (kWh)
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 		+ prefill_iteration_2 energy consumption:
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 			+ CPU: 0.000344 (kWh)
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 			+ GPU: 0.002026 (kWh)
+[PROC-0][2024-12-04 17:13:01,965][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 			+ total: 0.002374 (kWh)
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 		+ prefill_iteration_3 energy consumption:
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 			+ CPU: 0.000342 (kWh)
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 			+ GPU: 0.002010 (kWh)
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 			+ total: 0.002356 (kWh)
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 		+ prefill_iteration_4 energy consumption:
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 			+ CPU: 0.000342 (kWh)
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 			+ GPU: 0.002014 (kWh)
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 			+ total: 0.002360 (kWh)
+[PROC-0][2024-12-04 17:13:01,966][energy][INFO] - 		+ prefill_iteration_5 energy consumption:
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ CPU: 0.000342 (kWh)
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ GPU: 0.002011 (kWh)
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ total: 0.002357 (kWh)
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 		+ prefill_iteration_6 energy consumption:
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ CPU: 0.000343 (kWh)
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ GPU: 0.002014 (kWh)
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ total: 0.002361 (kWh)
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 		+ prefill_iteration_7 energy consumption:
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-04 17:13:01,967][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 		+ prefill_iteration_8 energy consumption:
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 			+ CPU: 0.000342 (kWh)
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 			+ GPU: 0.002009 (kWh)
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 			+ total: 0.002354 (kWh)
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 		+ prefill_iteration_9 energy consumption:
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 			+ CPU: 0.000342 (kWh)
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 			+ GPU: 0.002011 (kWh)
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 			+ total: 0.002356 (kWh)
+[PROC-0][2024-12-04 17:13:01,968][energy][INFO] - 		+ prefill_iteration_10 energy consumption:
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ CPU: 0.000343 (kWh)
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ GPU: 0.002020 (kWh)
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ total: 0.002366 (kWh)
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 		+ decode energy consumption:
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ CPU: 0.001575 (kWh)
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ GPU: 0.003964 (kWh)
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ RAM: 0.000016 (kWh)
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ total: 0.005556 (kWh)
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 		+ decode_iteration_1 energy consumption:
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ CPU: 0.001752 (kWh)
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ GPU: 0.004435 (kWh)
+[PROC-0][2024-12-04 17:13:01,969][energy][INFO] - 			+ RAM: 0.000018 (kWh)
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 			+ total: 0.006205 (kWh)
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 		+ decode_iteration_2 energy consumption:
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 			+ CPU: 0.001745 (kWh)
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 			+ GPU: 0.004403 (kWh)
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 			+ RAM: 0.000018 (kWh)
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 			+ total: 0.006166 (kWh)
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 		+ decode_iteration_3 energy consumption:
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 			+ CPU: 0.001745 (kWh)
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 			+ GPU: 0.004412 (kWh)
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 			+ RAM: 0.000018 (kWh)
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 			+ total: 0.006175 (kWh)
+[PROC-0][2024-12-04 17:13:01,970][energy][INFO] - 		+ decode_iteration_4 energy consumption:
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 			+ CPU: 0.001755 (kWh)
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 			+ GPU: 0.004421 (kWh)
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 			+ RAM: 0.000018 (kWh)
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 			+ total: 0.006193 (kWh)
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 		+ decode_iteration_5 energy consumption:
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 			+ CPU: -0.000342 (kWh)
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 			+ GPU: -0.002011 (kWh)
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 			+ RAM: -0.000004 (kWh)
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 			+ total: -0.002357 (kWh)
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 		+ decode_iteration_6 energy consumption:
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 			+ CPU: 0.001745 (kWh)
+[PROC-0][2024-12-04 17:13:01,971][energy][INFO] - 			+ GPU: 0.004413 (kWh)
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 			+ RAM: 0.000018 (kWh)
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 			+ total: 0.006176 (kWh)
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 		+ decode_iteration_7 energy consumption:
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 			+ CPU: 0.002087 (kWh)
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 			+ GPU: 0.006413 (kWh)
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 			+ RAM: 0.000022 (kWh)
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 			+ total: 0.008522 (kWh)
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 		+ decode_iteration_8 energy consumption:
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 			+ CPU: 0.001747 (kWh)
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 			+ GPU: 0.004382 (kWh)
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 			+ RAM: 0.000018 (kWh)
+[PROC-0][2024-12-04 17:13:01,972][energy][INFO] - 			+ total: 0.006147 (kWh)
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 		+ decode_iteration_9 energy consumption:
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 			+ CPU: 0.001746 (kWh)
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 			+ GPU: 0.004372 (kWh)
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 			+ RAM: 0.000018 (kWh)
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 			+ total: 0.006137 (kWh)
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 		+ decode_iteration_10 energy consumption:
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 			+ CPU: 0.001772 (kWh)
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 			+ GPU: 0.004402 (kWh)
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 			+ RAM: 0.000018 (kWh)
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 			+ total: 0.006192 (kWh)
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-04 17:13:01,973][energy][INFO] - 			+ CPU: 0.000012 (kWh)
+[PROC-0][2024-12-04 17:13:01,974][energy][INFO] - 			+ GPU: 0.000019 (kWh)
+[PROC-0][2024-12-04 17:13:01,974][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-04 17:13:01,974][energy][INFO] - 			+ total: 0.000031 (kWh)
+[PROC-0][2024-12-04 17:13:01,974][energy][INFO] - 		+ prefill energy efficiency: 91065082.200265 (tokens/kWh)
+[PROC-0][2024-12-04 17:13:01,974][energy][INFO] - 		+ decode energy efficiency: 1619944.451836 (tokens/kWh)
+[PROC-0][2024-12-04 17:13:01,974][energy][INFO] - 		+ preprocess energy efficiency: 32468947.585393 (samples/kWh)
+[2024-12-04 17:13:02,662][datasets][INFO] - PyTorch version 2.4.0 available.

text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24/experiment_config.json

@@ -0,0 +1,110 @@
+{
+    "experiment_name": "text_generation",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-generation",
+        "model": "bigscience/bloomz-560m",
+        "processor": "bigscience/bloomz-560m",
+        "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": false,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/text_generation",
+        "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_new_tokens": 10,
+            "min_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
+    }
+}

text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24/generate_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-04T17:13:01",
+    "project_name": "codecarbon",
+    "run_id": "5b242a91-3197-41b3-9253-d34861798546",
+    "duration": -1733284414.1146047,
+    "emissions": 0.0031592918499545944,
+    "emissions_rate": 1.763256415979793e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 129.02572657389157,
+    "ram_power": 0.4394016265869141,
+    "cpu_energy": 0.002115267668630582,
+    "gpu_energy": 0.006421513470539986,
+    "ram_energy": 2.186860785924658e-05,
+    "energy_consumed": 0.008558649747029815,
+    "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
+}

text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24/prefill_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-04T16:43:29",
+    "project_name": "codecarbon",
+    "run_id": "5b242a91-3197-41b3-9253-d34861798546",
+    "duration": -1733284564.2325568,
+    "emissions": 0.0008734566222457878,
+    "emissions_rate": 3.006139127695831e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 250.2334203013918,
+    "ram_power": 0.4391512870788574,
+    "cpu_energy": 0.00034304597653473214,
+    "gpu_energy": 0.0020196391157100146,
+    "ram_energy": 3.5443205690369786e-06,
+    "energy_consumed": 0.002366229412813784,
+    "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
+}

text_generation/bigscience/bloomz-560m/2024-12-04-16-38-24/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-04T16:38:38",
+    "project_name": "codecarbon",
+    "run_id": "5b242a91-3197-41b3-9253-d34861798546",
+    "duration": -1733284592.2829382,
+    "emissions": 1.1368843320834963e-05,
+    "emissions_rate": 1.1307034794637876e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 67.3536754430518,
+    "ram_power": 0.31451940536499023,
+    "cpu_energy": 1.189836183752454e-05,
+    "gpu_energy": 1.8812515049981826e-05,
+    "ram_energy": 8.778073359449114e-08,
+    "energy_consumed": 3.079865762110086e-05,
+    "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
+}

text_generation/facebook/opt-1.3b/2024-12-04-15-35-29/.hydra/config.yaml

@@ -0,0 +1,96 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-generation
+  model: facebook/opt-1.3b
+  processor: facebook/opt-1.3b
+  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: false
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/text_generation
+  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_new_tokens: 10
+    min_new_tokens: 10
+  call_kwargs: {}
+experiment_name: text_generation
+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

text_generation/facebook/opt-1.3b/2024-12-04-15-35-29/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/text_generation/facebook/opt-1.3b/2024-12-04-15-35-29
+  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/text_generation/facebook/opt-1.3b/2024-12-04-15-35-29
+    - hydra.mode=RUN
+    task:
+    - backend.model=facebook/opt-1.3b
+    - backend.processor=facebook/opt-1.3b
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=facebook/opt-1.3b,backend.processor=facebook/opt-1.3b
+    id: ???
+    num: ???
+    config_name: text_generation
+    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/text_generation/facebook/opt-1.3b/2024-12-04-15-35-29
+    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

text_generation/facebook/opt-1.3b/2024-12-04-15-35-29/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=facebook/opt-1.3b
+- backend.processor=facebook/opt-1.3b

text_generation/facebook/opt-1.3b/2024-12-04-15-35-29/benchmark_report.json

@@ -0,0 +1,203 @@
+{
+    "prefill": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.0008514253416934658,
+            "ram": 7.867963273444184e-06,
+            "gpu": 0.0057380391182053955,
+            "total": 0.006597332423172309
+        },
+        "efficiency": {
+            "unit": "tokens/kWh",
+            "value": 45599945.66036175
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.0009420541374506937,
+                "ram": 8.704100682712942e-06,
+                "gpu": 0.0063278192289179525,
+                "total": 0.007278577467051359
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.000944713068940953,
+                "ram": 8.730216552006652e-06,
+                "gpu": 0.006389016222320076,
+                "total": 0.007342459507813036
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.000945915997960396,
+                "ram": 8.74128147129218e-06,
+                "gpu": 0.0063994151195279625,
+                "total": 0.00735407239895965
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0009464871018867345,
+                "ram": 8.745973796001767e-06,
+                "gpu": 0.006413208463895981,
+                "total": 0.007368441539578718
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0009467335027201289,
+                "ram": 8.748670999265155e-06,
+                "gpu": 0.006408340404445989,
+                "total": 0.007363822578165386
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0009467267385145986,
+                "ram": 8.748809905354579e-06,
+                "gpu": 0.006411111517774015,
+                "total": 0.007366587066193968
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0009472711554750681,
+                "ram": 8.754110904909515e-06,
+                "gpu": 0.006341506184311951,
+                "total": 0.007297531450691931
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0009472746114687711,
+                "ram": 8.754147384568123e-06,
+                "gpu": 0.0063449789648680754,
+                "total": 0.007301007723721421
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0009470771025173134,
+                "ram": 8.75232103833093e-06,
+                "gpu": 0.006344995075991955,
+                "total": 0.007300824499547609
+            }
+        ]
+    },
+    "decode": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.0014949766351097563,
+            "ram": 1.3839823376050235e-05,
+            "gpu": 0.005730950168089817,
+            "total": 0.007239766626575616
+        },
+        "efficiency": {
+            "unit": "tokens/kWh",
+            "value": 1243133.9937067789
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.0016573730981167152,
+                "ram": 1.5343569632938047e-05,
+                "gpu": 0.006264276122528112,
+                "total": 0.007936992790277769
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0016591519767944645,
+                "ram": 1.535895363465579e-05,
+                "gpu": 0.00633461312324185,
+                "total": 0.008009124053670963
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0016632256255590767,
+                "ram": 1.5396708280115472e-05,
+                "gpu": 0.006332735899518049,
+                "total": 0.008011358233357243
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0016589466871556845,
+                "ram": 1.535750031033357e-05,
+                "gpu": 0.006323610892218057,
+                "total": 0.007997915079684073
+            },
+            {
+                "unit": "kWh",
+                "cpu": -0.0009467335027201289,
+                "ram": -8.748670999265155e-06,
+                "gpu": -0.006408340404445989,
+                "total": -0.007363822578165386
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0016625658083840242,
+                "ram": 1.5391710184190226e-05,
+                "gpu": 0.006337731181291939,
+                "total": 0.008015688699860142
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0026131794655145715,
+                "ram": 2.417648965006555e-05,
+                "gpu": 0.012788611619769963,
+                "total": 0.015425967574934585
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0016600494504749718,
+                "ram": 1.536817153908214e-05,
+                "gpu": 0.0064490648814701235,
+                "total": 0.00812448250348418
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.001662433071380592,
+                "ram": 1.5390029146946412e-05,
+                "gpu": 0.006438650428693848,
+                "total": 0.008116473529221367
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0016595746704375896,
+                "ram": 1.536377238144031e-05,
+                "gpu": 0.006448547936612203,
+                "total": 0.008123486379431222
+            }
+        ]
+    },
+    "per_token": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": null,
+        "efficiency": null,
+        "measures": null
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 1.1007535735416243e-05,
+            "ram": 7.318336868205421e-08,
+            "gpu": 1.6262513009956958e-05,
+            "total": 2.7343232114055257e-05
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 36572121.24114506
+        },
+        "measures": null
+    }
+}

text_generation/facebook/opt-1.3b/2024-12-04-15-35-29/cli.log

@@ -0,0 +1,188 @@
+[2024-12-04 15:35:31,908][launcher][INFO] - ََAllocating process launcher
+[2024-12-04 15:35:31,908][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-04 15:35:31,921][process][INFO] - 	+ Launched benchmark in isolated process 426.
+[PROC-0][2024-12-04 15:35:34,474][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-04 15:35:35,364][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-04 15:35:35,365][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-04 15:35:36,180][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCausalLM
+[PROC-0][2024-12-04 15:35:36,181][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-04 15:35:36,181][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-04 15:35:36,181][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-04 15:35:36,181][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-04 15:35:36,181][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-04 15:35:36,201][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-04 15:35:36,202][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-04 15:35:36,203][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-04 15:35:36,203][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-04 15:35:36,402][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-04 15:35:36,409][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-04 15:35:36,409][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-04 15:35:37,584][energy_star][INFO] - 	+ Updating Text Generation kwargs with default values
+[PROC-0][2024-12-04 15:35:37,584][energy_star][INFO] - 	+ Initializing Text Generation report
+[PROC-0][2024-12-04 15:35:37,584][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-04 15:35:41,777][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-04 15:35:42,710][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-04 15:35:42,711][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-04 15:35:42,711][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-04 15:35:42,711][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-04 15:35:43,974][energy_star][INFO] - 	+ Additional warmup for Text Generation
+[PROC-0][2024-12-04 15:35:44,172][energy_star][INFO] - 	+ Running Text Generation energy tracking for 10 iterations
+[PROC-0][2024-12-04 15:35:44,172][energy_star][INFO] - 	+ Prefill iteration 1/10
+[PROC-0][2024-12-04 15:37:03,971][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 15:37:03,971][energy_star][INFO] - 	+ Prefill iteration 2/10
+[PROC-0][2024-12-04 15:38:23,994][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 15:38:23,995][energy_star][INFO] - 	+ Prefill iteration 3/10
+[PROC-0][2024-12-04 15:39:44,120][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 15:39:44,120][energy_star][INFO] - 	+ Prefill iteration 4/10
+[PROC-0][2024-12-04 15:41:04,294][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 15:41:04,294][energy_star][INFO] - 	+ Prefill iteration 5/10
+[PROC-0][2024-12-04 15:42:24,489][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 15:42:24,489][energy_star][INFO] - 	+ Prefill iteration 6/10
+[PROC-0][2024-12-04 15:43:44,683][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 15:43:44,684][energy_star][INFO] - 	+ Prefill iteration 7/10
+[PROC-0][2024-12-04 15:45:04,899][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 15:45:04,899][energy_star][INFO] - 	+ Prefill iteration 8/10
+[PROC-0][2024-12-04 15:46:25,139][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 15:46:25,139][energy_star][INFO] - 	+ Prefill iteration 9/10
+[PROC-0][2024-12-04 15:47:45,380][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 15:47:45,380][energy_star][INFO] - 	+ Prefill iteration 10/10
+[PROC-0][2024-12-04 15:49:05,604][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 15:49:05,604][energy_star][INFO] - 	+ Decoding iteration 1/10
+[PROC-0][2024-12-04 15:52:45,792][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 15:52:45,792][energy_star][INFO] - 	+ Decoding iteration 2/10
+[PROC-0][2024-12-04 15:56:26,355][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 15:56:26,356][energy_star][INFO] - 	+ Decoding iteration 3/10
+[PROC-0][2024-12-04 16:00:07,366][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:00:07,366][energy_star][INFO] - 	+ Decoding iteration 4/10
+[PROC-0][2024-12-04 16:03:48,063][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:03:48,063][energy_star][INFO] - 	+ Decoding iteration 5/10
+[PROC-0][2024-12-04 16:07:28,762][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:07:28,762][energy_star][INFO] - 	+ Decoding iteration 6/10
+[PROC-0][2024-12-04 16:11:09,785][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:11:09,786][energy_star][INFO] - 	+ Decoding iteration 7/10
+[PROC-0][2024-12-04 16:14:51,138][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:14:51,138][energy_star][INFO] - 	+ Decoding iteration 8/10
+[PROC-0][2024-12-04 16:18:31,994][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:18:31,995][energy_star][INFO] - 	+ Decoding iteration 9/10
+[PROC-0][2024-12-04 16:22:13,053][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:22:13,053][energy_star][INFO] - 	+ Decoding iteration 10/10
+[PROC-0][2024-12-04 16:25:53,853][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:25:53,853][energy][INFO] - 		+ prefill energy consumption:
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 			+ CPU: 0.000851 (kWh)
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 			+ GPU: 0.005738 (kWh)
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 			+ RAM: 0.000008 (kWh)
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 			+ total: 0.006597 (kWh)
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 		+ prefill_iteration_1 energy consumption:
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 			+ CPU: 0.000942 (kWh)
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 			+ GPU: 0.006328 (kWh)
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 			+ RAM: 0.000009 (kWh)
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 			+ total: 0.007279 (kWh)
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 		+ prefill_iteration_2 energy consumption:
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 			+ CPU: 0.000945 (kWh)
+[PROC-0][2024-12-04 16:25:53,854][energy][INFO] - 			+ GPU: 0.006389 (kWh)
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 			+ RAM: 0.000009 (kWh)
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 			+ total: 0.007342 (kWh)
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 		+ prefill_iteration_3 energy consumption:
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 			+ CPU: 0.000946 (kWh)
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 			+ GPU: 0.006399 (kWh)
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 			+ RAM: 0.000009 (kWh)
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 			+ total: 0.007354 (kWh)
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 		+ prefill_iteration_4 energy consumption:
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 			+ CPU: 0.000946 (kWh)
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 			+ GPU: 0.006413 (kWh)
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 			+ RAM: 0.000009 (kWh)
+[PROC-0][2024-12-04 16:25:53,855][energy][INFO] - 			+ total: 0.007368 (kWh)
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 		+ prefill_iteration_5 energy consumption:
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 			+ CPU: 0.000947 (kWh)
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 			+ GPU: 0.006408 (kWh)
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 			+ RAM: 0.000009 (kWh)
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 			+ total: 0.007364 (kWh)
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 		+ prefill_iteration_6 energy consumption:
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 			+ CPU: 0.000947 (kWh)
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 			+ GPU: 0.006411 (kWh)
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 			+ RAM: 0.000009 (kWh)
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 			+ total: 0.007367 (kWh)
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 		+ prefill_iteration_7 energy consumption:
+[PROC-0][2024-12-04 16:25:53,856][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 		+ prefill_iteration_8 energy consumption:
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 			+ CPU: 0.000947 (kWh)
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 			+ GPU: 0.006342 (kWh)
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 			+ RAM: 0.000009 (kWh)
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 			+ total: 0.007298 (kWh)
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 		+ prefill_iteration_9 energy consumption:
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 			+ CPU: 0.000947 (kWh)
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 			+ GPU: 0.006345 (kWh)
+[PROC-0][2024-12-04 16:25:53,857][energy][INFO] - 			+ RAM: 0.000009 (kWh)
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 			+ total: 0.007301 (kWh)
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 		+ prefill_iteration_10 energy consumption:
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 			+ CPU: 0.000947 (kWh)
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 			+ GPU: 0.006345 (kWh)
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 			+ RAM: 0.000009 (kWh)
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 			+ total: 0.007301 (kWh)
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 		+ decode energy consumption:
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 			+ CPU: 0.001495 (kWh)
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 			+ GPU: 0.005731 (kWh)
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 			+ RAM: 0.000014 (kWh)
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 			+ total: 0.007240 (kWh)
+[PROC-0][2024-12-04 16:25:53,858][energy][INFO] - 		+ decode_iteration_1 energy consumption:
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 			+ CPU: 0.001657 (kWh)
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 			+ GPU: 0.006264 (kWh)
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 			+ RAM: 0.000015 (kWh)
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 			+ total: 0.007937 (kWh)
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 		+ decode_iteration_2 energy consumption:
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 			+ CPU: 0.001659 (kWh)
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 			+ GPU: 0.006335 (kWh)
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 			+ RAM: 0.000015 (kWh)
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 			+ total: 0.008009 (kWh)
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 		+ decode_iteration_3 energy consumption:
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 			+ CPU: 0.001663 (kWh)
+[PROC-0][2024-12-04 16:25:53,859][energy][INFO] - 			+ GPU: 0.006333 (kWh)
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 			+ RAM: 0.000015 (kWh)
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 			+ total: 0.008011 (kWh)
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 		+ decode_iteration_4 energy consumption:
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 			+ CPU: 0.001659 (kWh)
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 			+ GPU: 0.006324 (kWh)
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 			+ RAM: 0.000015 (kWh)
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 			+ total: 0.007998 (kWh)
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 		+ decode_iteration_5 energy consumption:
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 			+ CPU: -0.000947 (kWh)
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 			+ GPU: -0.006408 (kWh)
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 			+ RAM: -0.000009 (kWh)
+[PROC-0][2024-12-04 16:25:53,860][energy][INFO] - 			+ total: -0.007364 (kWh)
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 		+ decode_iteration_6 energy consumption:
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 			+ CPU: 0.001663 (kWh)
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 			+ GPU: 0.006338 (kWh)
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 			+ RAM: 0.000015 (kWh)
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 			+ total: 0.008016 (kWh)
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 		+ decode_iteration_7 energy consumption:
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 			+ CPU: 0.002613 (kWh)
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 			+ GPU: 0.012789 (kWh)
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 			+ RAM: 0.000024 (kWh)
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 			+ total: 0.015426 (kWh)
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 		+ decode_iteration_8 energy consumption:
+[PROC-0][2024-12-04 16:25:53,861][energy][INFO] - 			+ CPU: 0.001660 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ GPU: 0.006449 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ RAM: 0.000015 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ total: 0.008124 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 		+ decode_iteration_9 energy consumption:
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ CPU: 0.001662 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ GPU: 0.006439 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ RAM: 0.000015 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ total: 0.008116 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 		+ decode_iteration_10 energy consumption:
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ CPU: 0.001660 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ GPU: 0.006449 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ RAM: 0.000015 (kWh)
+[PROC-0][2024-12-04 16:25:53,862][energy][INFO] - 			+ total: 0.008123 (kWh)
+[PROC-0][2024-12-04 16:25:53,863][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-04 16:25:53,863][energy][INFO] - 			+ CPU: 0.000011 (kWh)
+[PROC-0][2024-12-04 16:25:53,863][energy][INFO] - 			+ GPU: 0.000016 (kWh)
+[PROC-0][2024-12-04 16:25:53,863][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-04 16:25:53,863][energy][INFO] - 			+ total: 0.000027 (kWh)
+[PROC-0][2024-12-04 16:25:53,863][energy][INFO] - 		+ prefill energy efficiency: 45599945.660362 (tokens/kWh)
+[PROC-0][2024-12-04 16:25:53,863][energy][INFO] - 		+ decode energy efficiency: 1243133.993707 (tokens/kWh)
+[PROC-0][2024-12-04 16:25:53,863][energy][INFO] - 		+ preprocess energy efficiency: 36572121.241145 (samples/kWh)
+[2024-12-04 16:25:54,519][datasets][INFO] - PyTorch version 2.4.0 available.

text_generation/facebook/opt-1.3b/2024-12-04-15-35-29/experiment_config.json

@@ -0,0 +1,110 @@
+{
+    "experiment_name": "text_generation",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-generation",
+        "model": "facebook/opt-1.3b",
+        "processor": "facebook/opt-1.3b",
+        "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": false,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/text_generation",
+        "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_new_tokens": 10,
+            "min_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
+    }
+}

text_generation/facebook/opt-1.3b/2024-12-04-15-35-29/generate_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-04T16:25:53",
+    "project_name": "codecarbon",
+    "run_id": "11b39f4a-102b-4ccd-a4e2-10220e0cac0d",
+    "duration": -1733284372.491492,
+    "emissions": 0.005693643400705231,
+    "emissions_rate": 2.5786799656597985e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 208.5937464054236,
+    "ram_power": 0.3932046890258789,
+    "cpu_energy": 0.002606651772954903,
+    "gpu_energy": 0.012793543012604158,
+    "ram_energy": 2.4116093419771238e-05,
+    "energy_consumed": 0.01542431087897883,
+    "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
+}

text_generation/facebook/opt-1.3b/2024-12-04-15-35-29/prefill_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-04T15:49:05",
+    "project_name": "codecarbon",
+    "run_id": "11b39f4a-102b-4ccd-a4e2-10220e0cac0d",
+    "duration": -1733284513.0719962,
+    "emissions": 0.002694985309729978,
+    "emissions_rate": 3.3596470904941724e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 284.73932067551607,
+    "ram_power": 0.3927741050720215,
+    "cpu_energy": 0.0009470771025173134,
+    "gpu_energy": 0.006344995075991955,
+    "ram_energy": 8.75232103833093e-06,
+    "energy_consumed": 0.007300824499547609,
+    "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
+}

text_generation/facebook/opt-1.3b/2024-12-04-15-35-29/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-04T15:35:42",
+    "project_name": "codecarbon",
+    "run_id": "11b39f4a-102b-4ccd-a4e2-10220e0cac0d",
+    "duration": -1733284592.358094,
+    "emissions": 1.0093326975943891e-05,
+    "emissions_rate": 1.0849407214254869e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 62.94082925267726,
+    "ram_power": 0.283480167388916,
+    "cpu_energy": 1.1007535735416243e-05,
+    "gpu_energy": 1.6262513009956958e-05,
+    "ram_energy": 7.318336868205421e-08,
+    "energy_consumed": 2.7343232114055257e-05,
+    "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
+}

text_generation/openai-community/gpt2/2024-12-04-16-25-55/.hydra/config.yaml

@@ -0,0 +1,96 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-generation
+  model: openai-community/gpt2
+  processor: openai-community/gpt2
+  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: false
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/text_generation
+  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_new_tokens: 10
+    min_new_tokens: 10
+  call_kwargs: {}
+experiment_name: text_generation
+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

text_generation/openai-community/gpt2/2024-12-04-16-25-55/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/text_generation/openai-community/gpt2/2024-12-04-16-25-55
+  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/text_generation/openai-community/gpt2/2024-12-04-16-25-55
+    - hydra.mode=RUN
+    task:
+    - backend.model=openai-community/gpt2
+    - backend.processor=openai-community/gpt2
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=openai-community/gpt2,backend.processor=openai-community/gpt2
+    id: ???
+    num: ???
+    config_name: text_generation
+    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/text_generation/openai-community/gpt2/2024-12-04-16-25-55
+    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

text_generation/openai-community/gpt2/2024-12-04-16-25-55/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=openai-community/gpt2
+- backend.processor=openai-community/gpt2

text_generation/openai-community/gpt2/2024-12-04-16-25-55/benchmark_report.json

@@ -0,0 +1,203 @@
+{
+    "prefill": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.00010681085390979409,
+            "ram": 1.0297819029295639e-06,
+            "gpu": 0.0005602429481940008,
+            "total": 0.0006680835840067245
+        },
+        "efficiency": {
+            "unit": "tokens/kWh",
+            "value": 376223882.78510684
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.00011892353653820971,
+                "ram": 1.146182340068226e-06,
+                "gpu": 0.000611663822663977,
+                "total": 0.000731733541542255
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00011834202891877291,
+                "ram": 1.1408746650941389e-06,
+                "gpu": 0.0006136460464720717,
+                "total": 0.0007331289500559388
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00011868103943603878,
+                "ram": 1.1442912318482203e-06,
+                "gpu": 0.0006243707772740636,
+                "total": 0.0007441961079419509
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00011849597172222274,
+                "ram": 1.1424885480380128e-06,
+                "gpu": 0.0006210666079640159,
+                "total": 0.0007407050682342767
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00011872881676738167,
+                "ram": 1.1447441446528026e-06,
+                "gpu": 0.0006302155041718605,
+                "total": 0.0007500890650838951
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00011865041948475562,
+                "ram": 1.1439717885187163e-06,
+                "gpu": 0.0006199085514820846,
+                "total": 0.0007397029427553595
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00011862063215556493,
+                "ram": 1.143727828368652e-06,
+                "gpu": 0.000625526055975989,
+                "total": 0.0007452904159599228
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00011873292297564662,
+                "ram": 1.1448061300214643e-06,
+                "gpu": 0.0006323510614358874,
+                "total": 0.0007522287905415547
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0001189331710993479,
+                "ram": 1.1467323526854064e-06,
+                "gpu": 0.0006236810545000582,
+                "total": 0.0007437609579520913
+            }
+        ]
+    },
+    "decode": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.0005650565983572258,
+            "ram": 5.450526864520907e-06,
+            "gpu": 0.0012151225554306033,
+            "total": 0.0017856296806523508
+        },
+        "efficiency": {
+            "unit": "tokens/kWh",
+            "value": 5040238.800640902
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.0006368191074999889,
+                "ram": 6.142777259528393e-06,
+                "gpu": 0.0014249425288420658,
+                "total": 0.002067904413601583
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0006249990986270203,
+                "ram": 6.028900507407003e-06,
+                "gpu": 0.0013758658229138243,
+                "total": 0.0020068938220482507
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0006283337551250499,
+                "ram": 6.060942308998227e-06,
+                "gpu": 0.0013661177595599705,
+                "total": 0.002000512456994019
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0006280304214923487,
+                "ram": 6.057771480830845e-06,
+                "gpu": 0.0013490144125440917,
+                "total": 0.0019831026055172726
+            },
+            {
+                "unit": "kWh",
+                "cpu": -0.00011872881676738167,
+                "ram": -1.1447441446528026e-06,
+                "gpu": -0.0006302155041718605,
+                "total": -0.0007500890650838951
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0006244352388493348,
+                "ram": 6.023390549229008e-06,
+                "gpu": 0.001313566606407801,
+                "total": 0.0019440252358063647
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0007459197505402847,
+                "ram": 7.1942984685488865e-06,
+                "gpu": 0.0019516298946361532,
+                "total": 0.0027047439436449876
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0006257280835250589,
+                "ram": 6.035812423349825e-06,
+                "gpu": 0.0013290538410198893,
+                "total": 0.001960817736968298
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0006308752698229713,
+                "ram": 6.085473057879209e-06,
+                "gpu": 0.001338571626412155,
+                "total": 0.0019755323692930097
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0006241540748575822,
+                "ram": 6.020646734090474e-06,
+                "gpu": 0.0013326785661419427,
+                "total": 0.0019628532877336196
+            }
+        ]
+    },
+    "per_token": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": null,
+        "efficiency": null,
+        "measures": null
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 1.0390234946579667e-05,
+            "ram": 6.987208991124449e-08,
+            "gpu": 1.754223625605178e-05,
+            "total": 2.800234329254269e-05
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 35711297.070853
+        },
+        "measures": null
+    }
+}

text_generation/openai-community/gpt2/2024-12-04-16-25-55/cli.log

@@ -0,0 +1,188 @@
+[2024-12-04 16:25:58,357][launcher][INFO] - ََAllocating process launcher
+[2024-12-04 16:25:58,357][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-04 16:25:58,371][process][INFO] - 	+ Launched benchmark in isolated process 614.
+[PROC-0][2024-12-04 16:26:00,920][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-04 16:26:01,844][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-04 16:26:01,844][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-04 16:26:02,751][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCausalLM
+[PROC-0][2024-12-04 16:26:02,751][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-04 16:26:02,752][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-04 16:26:02,752][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-04 16:26:02,752][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-04 16:26:02,752][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-04 16:26:02,773][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-04 16:26:02,774][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-04 16:26:02,775][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-04 16:26:02,775][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-04 16:26:02,932][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-04 16:26:02,938][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-04 16:26:02,938][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-04 16:26:04,437][energy_star][INFO] - 	+ Updating Text Generation kwargs with default values
+[PROC-0][2024-12-04 16:26:04,437][energy_star][INFO] - 	+ Initializing Text Generation report
+[PROC-0][2024-12-04 16:26:04,437][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-04 16:26:08,638][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-04 16:26:09,519][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-04 16:26:09,520][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-04 16:26:09,520][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-04 16:26:09,520][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-04 16:26:10,457][energy_star][INFO] - 	+ Additional warmup for Text Generation
+[PROC-0][2024-12-04 16:26:10,522][energy_star][INFO] - 	+ Running Text Generation energy tracking for 10 iterations
+[PROC-0][2024-12-04 16:26:10,522][energy_star][INFO] - 	+ Prefill iteration 1/10
+[PROC-0][2024-12-04 16:26:20,596][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:26:20,597][energy_star][INFO] - 	+ Prefill iteration 2/10
+[PROC-0][2024-12-04 16:26:30,622][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:26:30,622][energy_star][INFO] - 	+ Prefill iteration 3/10
+[PROC-0][2024-12-04 16:26:40,676][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:26:40,676][energy_star][INFO] - 	+ Prefill iteration 4/10
+[PROC-0][2024-12-04 16:26:50,714][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:26:50,714][energy_star][INFO] - 	+ Prefill iteration 5/10
+[PROC-0][2024-12-04 16:27:00,772][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:27:00,773][energy_star][INFO] - 	+ Prefill iteration 6/10
+[PROC-0][2024-12-04 16:27:10,823][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:27:10,824][energy_star][INFO] - 	+ Prefill iteration 7/10
+[PROC-0][2024-12-04 16:27:20,845][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:27:20,845][energy_star][INFO] - 	+ Prefill iteration 8/10
+[PROC-0][2024-12-04 16:27:30,893][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:27:30,894][energy_star][INFO] - 	+ Prefill iteration 9/10
+[PROC-0][2024-12-04 16:27:40,952][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:27:40,952][energy_star][INFO] - 	+ Prefill iteration 10/10
+[PROC-0][2024-12-04 16:27:51,027][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-04 16:27:51,028][energy_star][INFO] - 	+ Decoding iteration 1/10
+[PROC-0][2024-12-04 16:28:55,044][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:28:55,045][energy_star][INFO] - 	+ Decoding iteration 2/10
+[PROC-0][2024-12-04 16:29:58,011][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:29:58,011][energy_star][INFO] - 	+ Decoding iteration 3/10
+[PROC-0][2024-12-04 16:31:01,288][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:31:01,289][energy_star][INFO] - 	+ Decoding iteration 4/10
+[PROC-0][2024-12-04 16:32:04,524][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:32:04,525][energy_star][INFO] - 	+ Decoding iteration 5/10
+[PROC-0][2024-12-04 16:33:07,035][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:33:07,035][energy_star][INFO] - 	+ Decoding iteration 6/10
+[PROC-0][2024-12-04 16:34:09,979][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:34:09,980][energy_star][INFO] - 	+ Decoding iteration 7/10
+[PROC-0][2024-12-04 16:35:13,164][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:35:13,165][energy_star][INFO] - 	+ Decoding iteration 8/10
+[PROC-0][2024-12-04 16:36:16,216][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:36:16,216][energy_star][INFO] - 	+ Decoding iteration 9/10
+[PROC-0][2024-12-04 16:37:19,713][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:37:19,714][energy_star][INFO] - 	+ Decoding iteration 10/10
+[PROC-0][2024-12-04 16:38:22,658][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-04 16:38:22,659][energy][INFO] - 		+ prefill energy consumption:
+[PROC-0][2024-12-04 16:38:22,659][energy][INFO] - 			+ CPU: 0.000107 (kWh)
+[PROC-0][2024-12-04 16:38:22,659][energy][INFO] - 			+ GPU: 0.000560 (kWh)
+[PROC-0][2024-12-04 16:38:22,659][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,659][energy][INFO] - 			+ total: 0.000668 (kWh)
+[PROC-0][2024-12-04 16:38:22,659][energy][INFO] - 		+ prefill_iteration_1 energy consumption:
+[PROC-0][2024-12-04 16:38:22,659][energy][INFO] - 			+ CPU: 0.000119 (kWh)
+[PROC-0][2024-12-04 16:38:22,659][energy][INFO] - 			+ GPU: 0.000612 (kWh)
+[PROC-0][2024-12-04 16:38:22,659][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 			+ total: 0.000732 (kWh)
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 		+ prefill_iteration_2 energy consumption:
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 			+ CPU: 0.000118 (kWh)
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 			+ GPU: 0.000614 (kWh)
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 			+ total: 0.000733 (kWh)
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 		+ prefill_iteration_3 energy consumption:
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 			+ CPU: 0.000119 (kWh)
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 			+ GPU: 0.000624 (kWh)
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 			+ total: 0.000744 (kWh)
+[PROC-0][2024-12-04 16:38:22,660][energy][INFO] - 		+ prefill_iteration_4 energy consumption:
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 			+ CPU: 0.000118 (kWh)
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 			+ GPU: 0.000621 (kWh)
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 			+ total: 0.000741 (kWh)
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 		+ prefill_iteration_5 energy consumption:
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 			+ CPU: 0.000119 (kWh)
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 			+ GPU: 0.000630 (kWh)
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 			+ total: 0.000750 (kWh)
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 		+ prefill_iteration_6 energy consumption:
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 			+ CPU: 0.000119 (kWh)
+[PROC-0][2024-12-04 16:38:22,661][energy][INFO] - 			+ GPU: 0.000620 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 			+ total: 0.000740 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 		+ prefill_iteration_7 energy consumption:
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 		+ prefill_iteration_8 energy consumption:
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 			+ CPU: 0.000119 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 			+ GPU: 0.000626 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 			+ total: 0.000745 (kWh)
+[PROC-0][2024-12-04 16:38:22,662][energy][INFO] - 		+ prefill_iteration_9 energy consumption:
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 			+ CPU: 0.000119 (kWh)
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 			+ GPU: 0.000632 (kWh)
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 			+ total: 0.000752 (kWh)
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 		+ prefill_iteration_10 energy consumption:
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 			+ CPU: 0.000119 (kWh)
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 			+ GPU: 0.000624 (kWh)
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 			+ total: 0.000744 (kWh)
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 		+ decode energy consumption:
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 			+ CPU: 0.000565 (kWh)
+[PROC-0][2024-12-04 16:38:22,663][energy][INFO] - 			+ GPU: 0.001215 (kWh)
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 			+ total: 0.001786 (kWh)
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 		+ decode_iteration_1 energy consumption:
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 			+ CPU: 0.000637 (kWh)
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 			+ GPU: 0.001425 (kWh)
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 			+ total: 0.002068 (kWh)
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 		+ decode_iteration_2 energy consumption:
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 			+ CPU: 0.000625 (kWh)
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 			+ GPU: 0.001376 (kWh)
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-04 16:38:22,664][energy][INFO] - 			+ total: 0.002007 (kWh)
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 		+ decode_iteration_3 energy consumption:
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 			+ CPU: 0.000628 (kWh)
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 			+ GPU: 0.001366 (kWh)
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 			+ total: 0.002001 (kWh)
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 		+ decode_iteration_4 energy consumption:
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 			+ CPU: 0.000628 (kWh)
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 			+ GPU: 0.001349 (kWh)
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 			+ total: 0.001983 (kWh)
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 		+ decode_iteration_5 energy consumption:
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 			+ CPU: -0.000119 (kWh)
+[PROC-0][2024-12-04 16:38:22,665][energy][INFO] - 			+ GPU: -0.000630 (kWh)
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 			+ RAM: -0.000001 (kWh)
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 			+ total: -0.000750 (kWh)
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 		+ decode_iteration_6 energy consumption:
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 			+ CPU: 0.000624 (kWh)
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 			+ GPU: 0.001314 (kWh)
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 			+ total: 0.001944 (kWh)
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 		+ decode_iteration_7 energy consumption:
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 			+ CPU: 0.000746 (kWh)
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 			+ GPU: 0.001952 (kWh)
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 			+ RAM: 0.000007 (kWh)
+[PROC-0][2024-12-04 16:38:22,666][energy][INFO] - 			+ total: 0.002705 (kWh)
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 		+ decode_iteration_8 energy consumption:
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 			+ CPU: 0.000626 (kWh)
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 			+ GPU: 0.001329 (kWh)
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 			+ total: 0.001961 (kWh)
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 		+ decode_iteration_9 energy consumption:
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 			+ CPU: 0.000631 (kWh)
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 			+ GPU: 0.001339 (kWh)
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 			+ total: 0.001976 (kWh)
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 		+ decode_iteration_10 energy consumption:
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 			+ CPU: 0.000624 (kWh)
+[PROC-0][2024-12-04 16:38:22,667][energy][INFO] - 			+ GPU: 0.001333 (kWh)
+[PROC-0][2024-12-04 16:38:22,668][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-04 16:38:22,668][energy][INFO] - 			+ total: 0.001963 (kWh)
+[PROC-0][2024-12-04 16:38:22,668][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-04 16:38:22,668][energy][INFO] - 			+ CPU: 0.000010 (kWh)
+[PROC-0][2024-12-04 16:38:22,668][energy][INFO] - 			+ GPU: 0.000018 (kWh)
+[PROC-0][2024-12-04 16:38:22,668][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-04 16:38:22,668][energy][INFO] - 			+ total: 0.000028 (kWh)
+[PROC-0][2024-12-04 16:38:22,668][energy][INFO] - 		+ prefill energy efficiency: 376223882.785107 (tokens/kWh)
+[PROC-0][2024-12-04 16:38:22,669][energy][INFO] - 		+ decode energy efficiency: 5040238.800641 (tokens/kWh)
+[PROC-0][2024-12-04 16:38:22,669][energy][INFO] - 		+ preprocess energy efficiency: 35711297.070853 (samples/kWh)
+[2024-12-04 16:38:23,359][datasets][INFO] - PyTorch version 2.4.0 available.

text_generation/openai-community/gpt2/2024-12-04-16-25-55/experiment_config.json

@@ -0,0 +1,110 @@
+{
+    "experiment_name": "text_generation",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-generation",
+        "model": "openai-community/gpt2",
+        "processor": "openai-community/gpt2",
+        "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": false,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/text_generation",
+        "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_new_tokens": 10,
+            "min_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
+    }
+}

text_generation/openai-community/gpt2/2024-12-04-16-25-55/generate_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-04T16:38:22",
+    "project_name": "codecarbon",
+    "run_id": "afde1576-ebf9-460b-b8e2-a655a80c078d",
+    "duration": -1733284530.346387,
+    "emissions": 0.0009991043657714086,
+    "emissions_rate": 1.5873427648203317e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 111.89574880758785,
+    "ram_power": 0.40994882583618164,
+    "cpu_energy": 0.0007430872459569301,
+    "gpu_energy": 0.001956359620642001,
+    "ram_energy": 7.16737908677588e-06,
+    "energy_consumed": 0.002706614245685711,
+    "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
+}

text_generation/openai-community/gpt2/2024-12-04-16-25-55/prefill_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-04T16:27:51",
+    "project_name": "codecarbon",
+    "run_id": "afde1576-ebf9-460b-b8e2-a655a80c078d",
+    "duration": -1733284583.215868,
+    "emissions": 0.0002745477385130662,
+    "emissions_rate": 2.7257328036196253e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 222.9195650721471,
+    "ram_power": 0.4099001884460449,
+    "cpu_energy": 0.0001189331710993479,
+    "gpu_energy": 0.0006236810545000582,
+    "ram_energy": 1.1467323526854064e-06,
+    "energy_consumed": 0.0007437609579520913,
+    "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
+}

text_generation/openai-community/gpt2/2024-12-04-16-25-55/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-04T16:26:09",
+    "project_name": "codecarbon",
+    "run_id": "afde1576-ebf9-460b-b8e2-a655a80c078d",
+    "duration": -1733284592.4103684,
+    "emissions": 1.0336627570775682e-05,
+    "emissions_rate": 1.1772892293402276e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 71.93685272733893,
+    "ram_power": 0.2868003845214844,
+    "cpu_energy": 1.0390234946579667e-05,
+    "gpu_energy": 1.754223625605178e-05,
+    "ram_energy": 6.987208991124449e-08,
+    "energy_consumed": 2.800234329254269e-05,
+    "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
+}