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text_classification/lvwerra/distilbert-imdb/2024-10-01-21-09-41/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-classification
+  model: lvwerra/distilbert-imdb
+  processor: lvwerra/distilbert-imdb
+  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/text_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: text_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

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-09-41/.hydra/hydra.yaml

@@ -0,0 +1,173 @@
+hydra:
+  run:
+    dir: /data/runs/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/data/runs/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    - hydra.mode=RUN
+    task: []
+  job:
+    name: cli
+    chdir: true
+    override_dirname: ''
+    id: ???
+    num: ???
+    config_name: text_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: /data/runs/text_classification/lvwerra/distilbert-imdb/2024-10-01-21-09-41
+    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_classification/lvwerra/distilbert-imdb/2024-10-01-21-09-41/.hydra/overrides.yaml

@@ -0,0 +1 @@
+[]

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-09-41/benchmark_report.json

@@ -0,0 +1,107 @@
+{
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+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 78344796.06934798
+        },
+        "measures": null
+    }
+}

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-09-41/cli.log

@@ -0,0 +1,113 @@
+[2024-10-01 21:09:41,569][launcher][INFO] - ََAllocating process launcher
+[2024-10-01 21:09:41,569][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-10-01 21:09:41,583][device-isolation][INFO] - 	+ Launched device(s) isolation process 66
+[2024-10-01 21:09:41,583][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-10-01 21:09:41,590][process][INFO] - 	+ Launched benchmark in isolated process 67.
+[PROC-0][2024-10-01 21:09:44,268][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-10-01 21:09:45,259][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-10-01 21:09:45,259][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-10-01 21:09:45,766][pytorch][INFO] - 	+ Using AutoModel class AutoModelForSequenceClassification
+[PROC-0][2024-10-01 21:09:45,766][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-10-01 21:09:45,766][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-10-01 21:09:45,766][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-10-01 21:09:45,766][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-10-01 21:09:45,767][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-10-01 21:09:45,769][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-10-01 21:09:45,769][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-10-01 21:09:45,770][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-10-01 21:09:45,770][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-10-01 21:09:46,034][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-10-01 21:09:46,040][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-10-01 21:09:46,040][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-10-01 21:09:47,035][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-10-01 21:09:47,036][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-10-01 21:09:51,221][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-10-01 21:09:51,652][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-10-01 21:09:51,654][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-10-01 21:09:51,654][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-10-01 21:09:51,654][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-10-01 21:09:52,180][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-10-01 21:09:52,180][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-10-01 21:09:56,347][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:09:56,349][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-10-01 21:10:00,495][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:10:00,498][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-10-01 21:10:04,568][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:10:04,571][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-10-01 21:10:08,605][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:10:08,607][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-10-01 21:10:12,673][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:10:12,675][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-10-01 21:10:16,827][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:10:16,829][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-10-01 21:10:20,880][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:10:20,882][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-10-01 21:10:24,924][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:10:24,927][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-10-01 21:10:28,977][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:10:28,979][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-10-01 21:10:33,109][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:10:33,111][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 			+ CPU: 0.000043 (kWh)
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 			+ GPU: 0.000170 (kWh)
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 			+ total: 0.000214 (kWh)
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 			+ CPU: 0.000049 (kWh)
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 			+ GPU: 0.000185 (kWh)
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 			+ total: 0.000234 (kWh)
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 			+ CPU: 0.000049 (kWh)
+[PROC-0][2024-10-01 21:10:33,112][energy][INFO] - 			+ GPU: 0.000192 (kWh)
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+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 			+ total: 0.000241 (kWh)
+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 			+ CPU: 0.000048 (kWh)
+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 			+ GPU: 0.000185 (kWh)
+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 			+ total: 0.000233 (kWh)
+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 			+ CPU: 0.000048 (kWh)
+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 			+ GPU: 0.000190 (kWh)
+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:10:33,113][energy][INFO] - 			+ total: 0.000238 (kWh)
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 			+ CPU: 0.000048 (kWh)
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 			+ GPU: 0.000187 (kWh)
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 			+ total: 0.000235 (kWh)
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 			+ CPU: 0.000049 (kWh)
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 			+ GPU: 0.000189 (kWh)
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 			+ total: 0.000238 (kWh)
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-10-01 21:10:33,114][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:10:33,115][energy][INFO] - 			+ GPU: 0.000000 (kWh)
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+[PROC-0][2024-10-01 21:10:33,115][energy][INFO] - 		+ forward_iteration_8 energy consumption:
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+[PROC-0][2024-10-01 21:10:33,115][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-10-01 21:10:33,115][energy][INFO] - 			+ CPU: 0.000048 (kWh)
+[PROC-0][2024-10-01 21:10:33,115][energy][INFO] - 			+ GPU: 0.000193 (kWh)
+[PROC-0][2024-10-01 21:10:33,115][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:10:33,115][energy][INFO] - 			+ total: 0.000241 (kWh)
+[PROC-0][2024-10-01 21:10:33,116][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-10-01 21:10:33,116][energy][INFO] - 			+ CPU: 0.000049 (kWh)
+[PROC-0][2024-10-01 21:10:33,116][energy][INFO] - 			+ GPU: 0.000194 (kWh)
+[PROC-0][2024-10-01 21:10:33,116][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:10:33,116][energy][INFO] - 			+ total: 0.000243 (kWh)
+[PROC-0][2024-10-01 21:10:33,116][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-10-01 21:10:33,116][energy][INFO] - 			+ CPU: 0.000005 (kWh)
+[PROC-0][2024-10-01 21:10:33,116][energy][INFO] - 			+ GPU: 0.000008 (kWh)
+[PROC-0][2024-10-01 21:10:33,116][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:10:33,116][energy][INFO] - 			+ total: 0.000013 (kWh)
+[PROC-0][2024-10-01 21:10:33,117][energy][INFO] - 		+ forward energy efficiency: 4672320.679800 (samples/kWh)
+[PROC-0][2024-10-01 21:10:33,117][energy][INFO] - 		+ preprocess energy efficiency: 78344796.069348 (samples/kWh)
+[2024-10-01 21:10:33,744][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-10-01 21:10:33,800][datasets][INFO] - PyTorch version 2.4.0 available.

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-09-41/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "text_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-classification",
+        "model": "lvwerra/distilbert-imdb",
+        "processor": "lvwerra/distilbert-imdb",
+        "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/text_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_classification/lvwerra/distilbert-imdb/2024-10-01-21-09-41/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-10-01T21:10:33",
+    "project_name": "codecarbon",
+    "run_id": "75ce62d4-cc28-42f9-a817-c1b3aadade45",
+    "duration": -1727749209.1593964,
+    "emissions": 8.967815496656838e-05,
+    "emissions_rate": 2.1740395178211913e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 169.17741289202826,
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+    "cpu_energy": 4.8719858849916714e-05,
+    "gpu_energy": 0.0001938262661720369,
+    "ram_energy": 3.956336920298112e-07,
+    "energy_consumed": 0.00024294175871398312,
+    "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_classification/lvwerra/distilbert-imdb/2024-10-01-21-09-41/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-10-01T21:09:51",
+    "project_name": "codecarbon",
+    "run_id": "75ce62d4-cc28-42f9-a817-c1b3aadade45",
+    "duration": -1727749212.8582268,
+    "emissions": 4.711664289278329e-06,
+    "emissions_rate": 1.1054344333457656e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 64.86775595639516,
+    "ram_power": 0.274709701538086,
+    "cpu_energy": 5.05552379719221e-06,
+    "gpu_energy": 7.676117252053416e-06,
+    "ram_energy": 3.2448592583758865e-08,
+    "energy_consumed": 1.2764089641829385e-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_classification/lvwerra/distilbert-imdb/2024-10-01-21-10-38/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-classification
+  model: lvwerra/distilbert-imdb
+  processor: lvwerra/distilbert-imdb
+  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/text_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: text_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
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+  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_classification/lvwerra/distilbert-imdb/2024-10-01-21-10-38/.hydra/hydra.yaml

@@ -0,0 +1,173 @@
+hydra:
+  run:
+    dir: /data/runs/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/data/runs/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    - hydra.mode=RUN
+    task: []
+  job:
+    name: cli
+    chdir: true
+    override_dirname: ''
+    id: ???
+    num: ???
+    config_name: text_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: /data/runs/text_classification/lvwerra/distilbert-imdb/2024-10-01-21-10-38
+    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_classification/lvwerra/distilbert-imdb/2024-10-01-21-10-38/.hydra/overrides.yaml

@@ -0,0 +1 @@
+[]

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-10-38/cli.log

@@ -0,0 +1,30 @@
+[2024-10-01 21:10:38,131][launcher][INFO] - ََAllocating process launcher
+[2024-10-01 21:10:38,131][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-10-01 21:10:38,145][device-isolation][INFO] - 	+ Launched device(s) isolation process 66
+[2024-10-01 21:10:38,145][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-10-01 21:10:38,152][process][INFO] - 	+ Launched benchmark in isolated process 67.
+[PROC-0][2024-10-01 21:10:40,783][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-10-01 21:10:41,752][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-10-01 21:10:41,753][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-10-01 21:10:42,048][pytorch][INFO] - 	+ Using AutoModel class AutoModelForSequenceClassification
+[PROC-0][2024-10-01 21:10:42,049][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-10-01 21:10:42,049][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-10-01 21:10:42,049][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-10-01 21:10:42,049][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-10-01 21:10:42,049][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-10-01 21:10:42,051][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-10-01 21:10:42,052][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-10-01 21:10:42,052][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-10-01 21:10:42,052][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-10-01 21:10:42,308][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-10-01 21:10:42,314][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-10-01 21:10:42,314][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-10-01 21:10:42,950][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-10-01 21:10:42,950][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-10-01 21:10:47,140][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-10-01 21:10:47,571][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-10-01 21:10:47,573][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-10-01 21:10:47,573][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-10-01 21:10:47,574][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-10-01 21:10:48,067][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-10-01 21:10:48,067][energy_star][INFO] - 	+ Iteration 1/10

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-10-38/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "text_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-classification",
+        "model": "lvwerra/distilbert-imdb",
+        "processor": "lvwerra/distilbert-imdb",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
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+            "force_download": false,
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+            "trust_remote_code": true
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+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
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+        "torch_compile": false,
+        "torch_compile_config": {},
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+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
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+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/text_classification",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
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+        "sentence1_column_name": "sentence1",
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+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
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+    "environment": {
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+        "peft_commit": null
+    }
+}

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-10-38/preprocess_codecarbon.json

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

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-14-17/.hydra/config.yaml

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+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-classification
+  model: lvwerra/distilbert-imdb
+  processor: lvwerra/distilbert-imdb
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+  device: cuda
+  device_ids: '0'
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+  torch_compile_config: {}
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+  quantization_config: {}
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+  deepspeed_inference_config: {}
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+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/text_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
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+  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: text_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:
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+  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
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+  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_classification/lvwerra/distilbert-imdb/2024-10-01-21-14-17/.hydra/hydra.yaml

@@ -0,0 +1,173 @@
+hydra:
+  run:
+    dir: /data/runs/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
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+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
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+          CRITICAL: red
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+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
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+  overrides:
+    hydra:
+    - hydra.run.dir=/data/runs/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    - hydra.mode=RUN
+    task: []
+  job:
+    name: cli
+    chdir: true
+    override_dirname: ''
+    id: ???
+    num: ???
+    config_name: text_classification
+    env_set:
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+    env_copy: []
+    config:
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+      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: /data/runs/text_classification/lvwerra/distilbert-imdb/2024-10-01-21-14-17
+    choices:
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+      launcher: process
+      backend: pytorch
+      hydra/env: default
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+      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_classification/lvwerra/distilbert-imdb/2024-10-01-21-14-17/.hydra/overrides.yaml

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text_classification/lvwerra/distilbert-imdb/2024-10-01-21-14-17/benchmark_report.json

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+}

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-14-17/cli.log

@@ -0,0 +1,113 @@
+[2024-10-01 21:14:18,000][launcher][INFO] - ََAllocating process launcher
+[2024-10-01 21:14:18,001][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-10-01 21:14:18,015][device-isolation][INFO] - 	+ Launched device(s) isolation process 66
+[2024-10-01 21:14:18,015][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-10-01 21:14:18,022][process][INFO] - 	+ Launched benchmark in isolated process 67.
+[PROC-0][2024-10-01 21:14:20,788][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-10-01 21:14:21,752][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-10-01 21:14:21,752][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-10-01 21:14:21,996][pytorch][INFO] - 	+ Using AutoModel class AutoModelForSequenceClassification
+[PROC-0][2024-10-01 21:14:21,996][pytorch][INFO] - 	+ Creating backend temporary directory
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+[PROC-0][2024-10-01 21:14:21,996][pytorch][INFO] - 	+ Creating no weights model directory
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+[PROC-0][2024-10-01 21:14:21,998][pytorch][INFO] - 	+ Saving no weights model safetensors
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+[PROC-0][2024-10-01 21:14:22,000][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-10-01 21:14:22,000][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-10-01 21:14:22,260][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-10-01 21:14:22,266][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-10-01 21:14:22,266][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-10-01 21:14:23,029][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-10-01 21:14:23,029][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-10-01 21:14:27,213][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-10-01 21:14:27,642][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-10-01 21:14:27,644][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-10-01 21:14:27,644][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-10-01 21:14:27,645][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-10-01 21:14:28,278][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-10-01 21:14:28,278][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-10-01 21:14:32,358][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:14:32,360][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-10-01 21:14:36,414][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:14:36,416][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-10-01 21:14:40,512][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:14:40,514][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-10-01 21:14:44,540][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:14:44,542][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-10-01 21:14:48,617][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:14:48,620][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-10-01 21:14:52,752][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:14:52,754][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-10-01 21:14:56,909][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:14:56,911][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-10-01 21:15:01,056][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:15:01,058][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-10-01 21:15:05,217][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:15:05,219][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-10-01 21:15:09,369][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-01 21:15:09,371][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-10-01 21:15:09,371][energy][INFO] - 			+ CPU: 0.000044 (kWh)
+[PROC-0][2024-10-01 21:15:09,371][energy][INFO] - 			+ GPU: 0.000171 (kWh)
+[PROC-0][2024-10-01 21:15:09,371][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 			+ total: 0.000215 (kWh)
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 			+ CPU: 0.000048 (kWh)
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 			+ GPU: 0.000186 (kWh)
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 			+ total: 0.000235 (kWh)
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 			+ CPU: 0.000048 (kWh)
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 			+ GPU: 0.000189 (kWh)
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 			+ total: 0.000237 (kWh)
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-10-01 21:15:09,372][energy][INFO] - 			+ CPU: 0.000048 (kWh)
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 			+ GPU: 0.000188 (kWh)
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 			+ total: 0.000237 (kWh)
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 			+ CPU: 0.000047 (kWh)
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 			+ GPU: 0.000186 (kWh)
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 			+ total: 0.000234 (kWh)
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 			+ CPU: 0.000048 (kWh)
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 			+ GPU: 0.000192 (kWh)
+[PROC-0][2024-10-01 21:15:09,373][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 			+ total: 0.000240 (kWh)
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 			+ CPU: 0.000049 (kWh)
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 			+ GPU: 0.000191 (kWh)
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 			+ total: 0.000240 (kWh)
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-10-01 21:15:09,374][energy][INFO] - 			+ CPU: 0.000049 (kWh)
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 			+ GPU: 0.000192 (kWh)
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 			+ total: 0.000241 (kWh)
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 			+ CPU: 0.000049 (kWh)
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 			+ GPU: 0.000195 (kWh)
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 			+ total: 0.000245 (kWh)
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 			+ CPU: 0.000049 (kWh)
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 			+ GPU: 0.000194 (kWh)
+[PROC-0][2024-10-01 21:15:09,375][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,376][energy][INFO] - 			+ total: 0.000244 (kWh)
+[PROC-0][2024-10-01 21:15:09,376][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-10-01 21:15:09,376][energy][INFO] - 			+ CPU: 0.000005 (kWh)
+[PROC-0][2024-10-01 21:15:09,376][energy][INFO] - 			+ GPU: 0.000008 (kWh)
+[PROC-0][2024-10-01 21:15:09,376][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-01 21:15:09,376][energy][INFO] - 			+ total: 0.000013 (kWh)
+[PROC-0][2024-10-01 21:15:09,376][energy][INFO] - 		+ forward energy efficiency: 4645424.325616 (samples/kWh)
+[PROC-0][2024-10-01 21:15:09,376][energy][INFO] - 		+ preprocess energy efficiency: 77670022.957253 (samples/kWh)
+[2024-10-01 21:15:10,016][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-10-01 21:15:10,071][datasets][INFO] - PyTorch version 2.4.0 available.

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-14-17/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "text_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-classification",
+        "model": "lvwerra/distilbert-imdb",
+        "processor": "lvwerra/distilbert-imdb",
+        "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/text_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_classification/lvwerra/distilbert-imdb/2024-10-01-21-14-17/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-10-01T21:15:09",
+    "project_name": "codecarbon",
+    "run_id": "62571789-e33c-4aa9-8938-1dccac1b80ae",
+    "duration": -1727749209.1388986,
+    "emissions": 8.991535859172444e-05,
+    "emissions_rate": 2.169014157580518e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 168.68108366185925,
+    "ram_power": 0.34534549713134766,
+    "cpu_energy": 4.896273474520662e-05,
+    "gpu_energy": 0.00019422404426805429,
+    "ram_energy": 3.9757394109469705e-07,
+    "energy_consumed": 0.00024358435295435566,
+    "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_classification/lvwerra/distilbert-imdb/2024-10-01-21-14-17/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-10-01T21:14:27",
+    "project_name": "codecarbon",
+    "run_id": "62571789-e33c-4aa9-8938-1dccac1b80ae",
+    "duration": -1727749212.8599434,
+    "emissions": 4.7525977698487455e-06,
+    "emissions_rate": 1.119615391187917e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 66.26954645159809,
+    "ram_power": 0.27468109130859375,
+    "cpu_energy": 5.0351720819384764e-06,
+    "gpu_energy": 7.807506245960383e-06,
+    "ram_energy": 3.2301772858555534e-08,
+    "energy_consumed": 1.2874980100757415e-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_classification/lvwerra/distilbert-imdb/2024-10-01-21-15-14/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-classification
+  model: lvwerra/distilbert-imdb
+  processor: lvwerra/distilbert-imdb
+  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/text_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: text_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

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-15-14/.hydra/hydra.yaml

@@ -0,0 +1,173 @@
+hydra:
+  run:
+    dir: /data/runs/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/data/runs/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    - hydra.mode=RUN
+    task: []
+  job:
+    name: cli
+    chdir: true
+    override_dirname: ''
+    id: ???
+    num: ???
+    config_name: text_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: /data/runs/text_classification/lvwerra/distilbert-imdb/2024-10-01-21-15-14
+    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_classification/lvwerra/distilbert-imdb/2024-10-01-21-15-14/.hydra/overrides.yaml

@@ -0,0 +1 @@
+[]

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-15-14/cli.log

@@ -0,0 +1,30 @@
+[2024-10-01 21:15:14,724][launcher][INFO] - ََAllocating process launcher
+[2024-10-01 21:15:14,724][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-10-01 21:15:14,738][device-isolation][INFO] - 	+ Launched device(s) isolation process 66
+[2024-10-01 21:15:14,738][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-10-01 21:15:14,745][process][INFO] - 	+ Launched benchmark in isolated process 67.
+[PROC-0][2024-10-01 21:15:17,313][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-10-01 21:15:18,249][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-10-01 21:15:18,249][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-10-01 21:15:18,543][pytorch][INFO] - 	+ Using AutoModel class AutoModelForSequenceClassification
+[PROC-0][2024-10-01 21:15:18,543][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-10-01 21:15:18,543][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-10-01 21:15:18,543][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-10-01 21:15:18,543][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-10-01 21:15:18,544][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-10-01 21:15:18,546][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-10-01 21:15:18,546][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-10-01 21:15:18,547][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-10-01 21:15:18,547][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-10-01 21:15:18,810][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-10-01 21:15:18,816][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-10-01 21:15:18,816][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-10-01 21:15:19,320][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-10-01 21:15:19,320][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-10-01 21:15:23,511][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-10-01 21:15:23,943][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-10-01 21:15:23,945][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-10-01 21:15:23,945][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-10-01 21:15:23,946][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-10-01 21:15:24,433][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-10-01 21:15:24,434][energy_star][INFO] - 	+ Iteration 1/10

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-15-14/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "text_classification",
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+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-classification",
+        "model": "lvwerra/distilbert-imdb",
+        "processor": "lvwerra/distilbert-imdb",
+        "library": "transformers",
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+        "deepspeed_inference_config": {},
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+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
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+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/text_classification",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
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+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
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+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
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+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
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+        "peft_commit": null
+    }
+}

text_classification/lvwerra/distilbert-imdb/2024-10-01-21-15-14/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-10-01T21:15:23",
+    "project_name": "codecarbon",
+    "run_id": "65f7cffa-58dc-44e2-b73b-9318c4a3d1e6",
+    "duration": -1727749212.8575919,
+    "emissions": 4.865202615390215e-06,
+    "emissions_rate": 1.1398218104190734e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 68.217578741548,
+    "ram_power": 0.2742791175842285,
+    "cpu_energy": 5.062855885363307e-06,
+    "gpu_energy": 8.084728689961018e-06,
+    "ram_energy": 3.2446618709477586e-08,
+    "energy_consumed": 1.3180031194033802e-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
+}