Upload folder using huggingface_hub

automatic_speech_recognition/pyannote/speaker-diarization/2024-12-06-11-54-21/.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: pyannote/speaker-diarization
+  processor: pyannote/speaker-diarization
+  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/pyannote/speaker-diarization/2024-12-06-11-54-21/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/automatic_speech_recognition/pyannote/speaker-diarization/2024-12-06-11-54-21
+  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/pyannote/speaker-diarization/2024-12-06-11-54-21
+    - hydra.mode=RUN
+    task:
+    - backend.model=pyannote/speaker-diarization
+    - backend.processor=pyannote/speaker-diarization
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=pyannote/speaker-diarization,backend.processor=pyannote/speaker-diarization
+    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/pyannote/speaker-diarization/2024-12-06-11-54-21
+    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/pyannote/speaker-diarization/2024-12-06-11-54-21/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=pyannote/speaker-diarization
+- backend.processor=pyannote/speaker-diarization

automatic_speech_recognition/pyannote/speaker-diarization/2024-12-06-11-54-21/error.log

@@ -0,0 +1,7 @@
+Error executing job with overrides: ['backend.model=pyannote/speaker-diarization', 'backend.processor=pyannote/speaker-diarization']
+Traceback (most recent call last):
+  File "/optimum-benchmark/optimum_benchmark/cli.py", line 62, in benchmark_cli
+    experiment_config: ExperimentConfig = OmegaConf.to_object(experiment_config)
+ValueError: `library` must be either `transformers`, `diffusers` or `timm`, but got pyannote-audio
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: sentence-similarity
+  model: sentence-transformers/multi-qa-MiniLM-L6-cos-v1
+  processor: sentence-transformers/multi-qa-MiniLM-L6-cos-v1
+  library: transformers
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/sentence_similarity
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: sentence_similarity_udever-bloom-7b1
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null

sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25
+    - hydra.mode=RUN
+    task:
+    - backend.model=sentence-transformers/multi-qa-MiniLM-L6-cos-v1
+    - backend.processor=sentence-transformers/multi-qa-MiniLM-L6-cos-v1
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=sentence-transformers/multi-qa-MiniLM-L6-cos-v1,backend.processor=sentence-transformers/multi-qa-MiniLM-L6-cos-v1
+    id: ???
+    num: ???
+    config_name: sentence_similarity
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=sentence-transformers/multi-qa-MiniLM-L6-cos-v1
+- backend.processor=sentence-transformers/multi-qa-MiniLM-L6-cos-v1

sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25/benchmark_report.json

@@ -0,0 +1,107 @@
+{
+    "forward": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 3.275373952828685e-05,
+            "ram": 2.625137697894165e-07,
+            "gpu": 6.466513506548921e-05,
+            "total": 9.768138836356548e-05
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 10237364.729891507
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 3.643965493700105e-05,
+                "ram": 2.9199692918469024e-07,
+                "gpu": 7.215922439485212e-05,
+                "total": 0.00010889087626103786
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.628243698783789e-05,
+                "ram": 2.908171471927138e-07,
+                "gpu": 7.23722801190263e-05,
+                "total": 0.0001089455342540569
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.624044489932001e-05,
+                "ram": 2.9046338093741353e-07,
+                "gpu": 7.244672462469737e-05,
+                "total": 0.0001089776329049548
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.694559903071626e-05,
+                "ram": 2.9616714317705344e-07,
+                "gpu": 7.22250577798178e-05,
+                "total": 0.0001094668239537111
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.618578909558387e-05,
+                "ram": 2.8997214067946837e-07,
+                "gpu": 7.248089131728364e-05,
+                "total": 0.00010895665255354701
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.635225530290175e-05,
+                "ram": 2.9141810238539734e-07,
+                "gpu": 7.01256116570903e-05,
+                "total": 0.0001067692850623775
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.680150384397066e-05,
+                "ram": 2.950214029441229e-07,
+                "gpu": 7.227394670827891e-05,
+                "total": 0.00010937047195519359
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.6118197154832575e-05,
+                "ram": 2.894922433755514e-07,
+                "gpu": 7.249589133095924e-05,
+                "total": 0.00010890358072916737
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.6171514030704384e-05,
+                "ram": 2.897892080177542e-07,
+                "gpu": 7.007172272288642e-05,
+                "total": 0.00010653302596160875
+            }
+        ]
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 1.929911376969863e-06,
+            "ram": 1.184183714824478e-08,
+            "gpu": 3.919725356738013e-06,
+            "total": 5.861478570856121e-06
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 170605417.71356183
+        },
+        "measures": null
+    }
+}

sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25/cli.log

@@ -0,0 +1,113 @@
+[2024-12-06 11:54:27,873][launcher][INFO] - ََAllocating process launcher
+[2024-12-06 11:54:27,874][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-06 11:54:27,885][device-isolation][INFO] - 	+ Launched device(s) isolation process 850
+[2024-12-06 11:54:27,886][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-06 11:54:27,892][process][INFO] - 	+ Launched benchmark in isolated process 851.
+[PROC-0][2024-12-06 11:54:30,508][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-06 11:54:31,453][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-06 11:54:31,453][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-06 11:54:31,916][pytorch][INFO] - 	+ Using AutoModel class AutoModel
+[PROC-0][2024-12-06 11:54:31,916][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-06 11:54:31,916][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-06 11:54:31,916][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-06 11:54:31,917][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-06 11:54:31,917][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-06 11:54:31,919][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-06 11:54:31,919][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-06 11:54:31,920][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-06 11:54:31,920][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-06 11:54:32,211][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-06 11:54:32,216][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-06 11:54:32,217][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-06 11:54:32,926][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-06 11:54:32,927][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-06 11:54:37,107][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-06 11:54:37,271][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-06 11:54:37,272][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-06 11:54:37,272][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-06 11:54:37,272][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-06 11:54:37,922][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-06 11:54:37,923][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-06 11:54:41,010][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:54:41,010][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-06 11:54:44,084][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:54:44,085][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-06 11:54:47,155][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:54:47,156][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-06 11:54:50,286][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:54:50,286][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-06 11:54:53,352][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:54:53,352][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-06 11:54:56,432][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:54:56,432][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-06 11:54:59,670][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:54:59,671][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-06 11:55:02,789][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:55:02,789][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-06 11:55:05,849][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:55:05,850][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-06 11:55:08,914][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:55:08,915][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-06 11:55:08,915][energy][INFO] - 			+ CPU: 0.000033 (kWh)
+[PROC-0][2024-12-06 11:55:08,915][energy][INFO] - 			+ GPU: 0.000065 (kWh)
+[PROC-0][2024-12-06 11:55:08,915][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,915][energy][INFO] - 			+ total: 0.000098 (kWh)
+[PROC-0][2024-12-06 11:55:08,915][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-06 11:55:08,915][energy][INFO] - 			+ CPU: 0.000036 (kWh)
+[PROC-0][2024-12-06 11:55:08,915][energy][INFO] - 			+ GPU: 0.000072 (kWh)
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 			+ total: 0.000109 (kWh)
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 			+ CPU: 0.000036 (kWh)
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 			+ GPU: 0.000072 (kWh)
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 			+ total: 0.000109 (kWh)
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 			+ CPU: 0.000036 (kWh)
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 			+ GPU: 0.000072 (kWh)
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,916][energy][INFO] - 			+ total: 0.000109 (kWh)
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 			+ CPU: 0.000037 (kWh)
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 			+ GPU: 0.000072 (kWh)
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 			+ total: 0.000109 (kWh)
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 			+ CPU: 0.000036 (kWh)
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 			+ GPU: 0.000072 (kWh)
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 			+ total: 0.000109 (kWh)
+[PROC-0][2024-12-06 11:55:08,917][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 			+ CPU: 0.000036 (kWh)
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 			+ GPU: 0.000070 (kWh)
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 			+ total: 0.000107 (kWh)
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 			+ CPU: 0.000037 (kWh)
+[PROC-0][2024-12-06 11:55:08,918][energy][INFO] - 			+ GPU: 0.000072 (kWh)
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 			+ total: 0.000109 (kWh)
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 			+ CPU: 0.000036 (kWh)
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 			+ GPU: 0.000072 (kWh)
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 			+ total: 0.000109 (kWh)
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 			+ CPU: 0.000036 (kWh)
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 			+ GPU: 0.000070 (kWh)
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,919][energy][INFO] - 			+ total: 0.000107 (kWh)
+[PROC-0][2024-12-06 11:55:08,920][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-06 11:55:08,920][energy][INFO] - 			+ CPU: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:55:08,920][energy][INFO] - 			+ GPU: 0.000004 (kWh)
+[PROC-0][2024-12-06 11:55:08,920][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:55:08,920][energy][INFO] - 			+ total: 0.000006 (kWh)
+[PROC-0][2024-12-06 11:55:08,920][energy][INFO] - 		+ forward energy efficiency: 10237364.729892 (samples/kWh)
+[PROC-0][2024-12-06 11:55:08,920][energy][INFO] - 		+ preprocess energy efficiency: 170605417.713562 (samples/kWh)
+[2024-12-06 11:55:09,574][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-06 11:55:09,621][datasets][INFO] - PyTorch version 2.4.0 available.

sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25/error.log

@@ -0,0 +1,170 @@
+/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 @ 11:54:32] [setup] RAM Tracking...
+[codecarbon INFO @ 11:54:32] [setup] GPU Tracking...
+[codecarbon INFO @ 11:54:32] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 11:54:32] GPU available. Starting setup
+[codecarbon INFO @ 11:54:32] [setup] CPU Tracking...
+[codecarbon DEBUG @ 11:54:32] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 11:54:32] 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 @ 11:54:32] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 11:54:32] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 11:54:34] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 11:54:34] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 11:54:34] >>> Tracker's metadata:
+[codecarbon INFO @ 11:54:34]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 11:54:34]   Python version: 3.9.20
+[codecarbon INFO @ 11:54:34]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 11:54:34]   Available RAM : 186.705 GB
+[codecarbon INFO @ 11:54:34]   CPU count: 48
+[codecarbon INFO @ 11:54:34]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 11:54:34]   GPU count: 1
+[codecarbon INFO @ 11:54:34]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 11:54:35] Not running on AWS
+[codecarbon DEBUG @ 11:54:36] Not running on Azure
+[codecarbon DEBUG @ 11:54:37] Not running on GCP
+[codecarbon INFO @ 11:54:37] Saving emissions data to file /runs/sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25/codecarbon.csv
+[codecarbon DEBUG @ 11:54:37] EmissionsData(timestamp='2024-12-06T11:54:37', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.0021375500364229083, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
+[codecarbon INFO @ 11:54:37] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.2656216621398926 W
+[codecarbon DEBUG @ 11:54:37] RAM : 0.27 W during 0.16 s [measurement time: 0.0005]
+[codecarbon INFO @ 11:54:37] Energy consumed for all GPUs : 0.000004 kWh. Total GPU Power : 87.50892425306003 W
+[codecarbon DEBUG @ 11:54:37] GPU : 87.51 W during 0.16 s [measurement time: 0.0022]
+[codecarbon INFO @ 11:54:37] Energy consumed for all CPUs : 0.000002 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:54:37] CPU : 42.50 W during 0.16 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:54:37] 0.000006 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:54:37] last_duration=0.1604911790927872
+------------------------
+[codecarbon DEBUG @ 11:54:37] EmissionsData(timestamp='2024-12-06T11:54:37', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.16357881703879684, emissions=2.163673245772878e-06, emissions_rate=1.3227099235347254e-05, cpu_power=42.5, gpu_power=87.50892425306003, ram_power=0.2656216621398926, cpu_energy=1.929911376969863e-06, gpu_energy=3.919725356738013e-06, ram_energy=1.184183714824478e-08, energy_consumed=5.861478570856121e-06, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:54:37] EmissionsData(timestamp='2024-12-06T11:54:37', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.002228492056019604, emissions=2.163673245772878e-06, emissions_rate=0.0009709136004897853, cpu_power=42.5, gpu_power=87.50892425306003, ram_power=0.2656216621398926, cpu_energy=1.929911376969863e-06, gpu_energy=3.919725356738013e-06, ram_energy=1.184183714824478e-08, energy_consumed=5.861478570856121e-06, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 31/1000 [00:00<00:03, 302.75it/s]
  6%|▌         | 62/1000 [00:00<00:03, 306.90it/s]
  9%|▉         | 94/1000 [00:00<00:02, 310.23it/s]
 13%|█▎        | 127/1000 [00:00<00:02, 316.38it/s]
 16%|█▌        | 160/1000 [00:00<00:02, 320.32it/s]
 19%|█▉        | 193/1000 [00:00<00:02, 323.35it/s]
 23%|██▎       | 226/1000 [00:00<00:02, 325.31it/s]
 26%|██▌       | 259/1000 [00:00<00:02, 323.69it/s]
 29%|██▉       | 292/1000 [00:00<00:02, 324.77it/s]
 32%|███▎      | 325/1000 [00:01<00:02, 324.61it/s]
 36%|███▌      | 358/1000 [00:01<00:01, 325.92it/s]
 39%|███▉      | 391/1000 [00:01<00:01, 327.14it/s]
 42%|████▏     | 424/1000 [00:01<00:01, 327.35it/s]
 46%|████▌     | 457/1000 [00:01<00:01, 323.07it/s]
 49%|████▉     | 490/1000 [00:01<00:01, 323.89it/s]
 52%|█████▏    | 523/1000 [00:01<00:01, 325.70it/s]
 56%|█████▌    | 557/1000 [00:01<00:01, 327.08it/s]
 59%|█████▉    | 591/1000 [00:01<00:01, 327.96it/s]
 62%|██████▏   | 624/1000 [00:01<00:01, 328.16it/s]
 66%|██████▌   | 657/1000 [00:02<00:01, 326.97it/s]
 69%|██████▉   | 691/1000 [00:02<00:00, 328.18it/s]
 72%|███████▏  | 724/1000 [00:02<00:00, 328.71it/s]
 76%|███████▌  | 757/1000 [00:02<00:00, 327.26it/s]
 79%|███████▉  | 790/1000 [00:02<00:00, 324.90it/s]
 82%|████████▏ | 823/1000 [00:02<00:00, 323.04it/s]
 86%|████████▌ | 857/1000 [00:02<00:00, 325.26it/s]
 89%|████████▉ | 891/1000 [00:02<00:00, 326.77it/s]
 92%|█████████▏| 924/1000 [00:02<00:00, 327.60it/s]
 96%|█████████▌| 957/1000 [00:02<00:00, 326.58it/s]
 99%|█████████▉| 990/1000 [00:03<00:00, 325.72it/s]
+[codecarbon WARNING @ 11:54:41] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:54:41] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.34089088439941406 W
+[codecarbon DEBUG @ 11:54:41] RAM : 0.34 W during 3.08 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:54:41] Energy consumed for all GPUs : 0.000076 kWh. Total GPU Power : 84.22292964314796 W
+[codecarbon DEBUG @ 11:54:41] GPU : 84.22 W during 3.08 s [measurement time: 0.0023]
+[codecarbon INFO @ 11:54:41] Energy consumed for all CPUs : 0.000038 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:54:41] CPU : 42.50 W during 3.09 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:54:41] 0.000115 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:54:41] last_duration=3.0834458130411804
+------------------------
+[codecarbon DEBUG @ 11:54:41] EmissionsData(timestamp='2024-12-06T11:54:41', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.0867553050629795, emissions=4.2359039112368636e-05, emissions_rate=1.3722836741509829e-05, cpu_power=42.5, gpu_power=84.22292964314796, ram_power=0.34089088439941406, cpu_energy=3.8369566313970915e-05, gpu_energy=7.607894975159013e-05, ram_energy=3.03838766332935e-07, energy_consumed=0.00011475235483189399, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:54:41] EmissionsData(timestamp='2024-12-06T11:54:41', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.002034757984802127, emissions=4.2359039112368636e-05, emissions_rate=0.020817728412299563, cpu_power=42.5, gpu_power=84.22292964314796, ram_power=0.34089088439941406, cpu_energy=3.8369566313970915e-05, gpu_energy=7.607894975159013e-05, ram_energy=3.03838766332935e-07, energy_consumed=0.00011475235483189399, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 33/1000 [00:00<00:02, 324.05it/s]
  7%|▋         | 66/1000 [00:00<00:02, 325.59it/s]
 10%|▉         | 99/1000 [00:00<00:02, 326.55it/s]
 13%|█▎        | 132/1000 [00:00<00:02, 326.44it/s]
 16%|█▋        | 165/1000 [00:00<00:02, 326.36it/s]
 20%|█▉        | 198/1000 [00:00<00:02, 326.33it/s]
 23%|██▎       | 231/1000 [00:00<00:02, 326.59it/s]
 26%|██▋       | 264/1000 [00:00<00:02, 326.58it/s]
 30%|██▉       | 297/1000 [00:00<00:02, 326.71it/s]
 33%|███▎      | 330/1000 [00:01<00:02, 326.74it/s]
 36%|███▋      | 363/1000 [00:01<00:01, 326.64it/s]
 40%|███▉      | 396/1000 [00:01<00:01, 326.67it/s]
 43%|████▎     | 429/1000 [00:01<00:01, 326.86it/s]
 46%|████▌     | 462/1000 [00:01<00:01, 326.92it/s]
 50%|████▉     | 495/1000 [00:01<00:01, 327.68it/s]
 53%|█████▎    | 528/1000 [00:01<00:01, 327.45it/s]
 56%|█████▌    | 561/1000 [00:01<00:01, 327.30it/s]
 59%|█████▉    | 594/1000 [00:01<00:01, 326.96it/s]
 63%|██████▎   | 627/1000 [00:01<00:01, 326.89it/s]
 66%|██████▌   | 660/1000 [00:02<00:01, 327.56it/s]
 69%|██████▉   | 693/1000 [00:02<00:00, 327.55it/s]
 73%|███████▎  | 726/1000 [00:02<00:00, 326.08it/s]
 76%|███████▌  | 759/1000 [00:02<00:00, 323.88it/s]
 79%|███████▉  | 792/1000 [00:02<00:00, 323.71it/s]
 82%|████████▎ | 825/1000 [00:02<00:00, 321.71it/s]
 86%|████████▌ | 858/1000 [00:02<00:00, 323.15it/s]
 89%|████████▉ | 891/1000 [00:02<00:00, 324.34it/s]
 92%|█████████▏| 924/1000 [00:02<00:00, 325.15it/s]
 96%|█████████▌| 957/1000 [00:02<00:00, 325.70it/s]
 99%|█████████▉| 990/1000 [00:03<00:00, 325.56it/s]
+[codecarbon WARNING @ 11:54:44] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:54:44] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.34098529815673834 W
+[codecarbon DEBUG @ 11:54:44] RAM : 0.34 W during 3.07 s [measurement time: 0.0005]
+[codecarbon INFO @ 11:54:44] Energy consumed for all GPUs : 0.000148 kWh. Total GPU Power : 84.83716186589065 W
+[codecarbon DEBUG @ 11:54:44] GPU : 84.84 W during 3.07 s [measurement time: 0.0022]
+[codecarbon INFO @ 11:54:44] Energy consumed for all CPUs : 0.000075 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:54:44] CPU : 42.50 W during 3.07 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:54:44] 0.000224 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:54:44] last_duration=3.0702556839678437
+------------------------
+[codecarbon DEBUG @ 11:54:44] EmissionsData(timestamp='2024-12-06T11:54:44', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.0734386909753084, emissions=8.257458112321423e-05, emissions_rate=2.6867163924786297e-05, cpu_power=42.5, gpu_power=84.83716186589065, ram_power=0.34098529815673834, cpu_energy=7.465200330180881e-05, gpu_energy=0.00014845122987061643, ram_energy=5.946559135256488e-07, energy_consumed=0.00022369788908595088, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:54:44] EmissionsData(timestamp='2024-12-06T11:54:44', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.002029986004345119, emissions=8.257458112321423e-05, emissions_rate=0.04067741400505522, cpu_power=42.5, gpu_power=84.83716186589065, ram_power=0.34098529815673834, cpu_energy=7.465200330180881e-05, gpu_energy=0.00014845122987061643, ram_energy=5.946559135256488e-07, energy_consumed=0.00022369788908595088, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 33/1000 [00:00<00:02, 323.34it/s]
  7%|▋         | 66/1000 [00:00<00:02, 322.81it/s]
 10%|▉         | 99/1000 [00:00<00:02, 324.69it/s]
 13%|█▎        | 132/1000 [00:00<00:02, 322.64it/s]
 16%|█▋        | 165/1000 [00:00<00:02, 323.95it/s]
 20%|█▉        | 198/1000 [00:00<00:02, 325.02it/s]
 23%|██▎       | 231/1000 [00:00<00:02, 325.76it/s]
 26%|██▋       | 264/1000 [00:00<00:02, 326.10it/s]
 30%|██▉       | 297/1000 [00:00<00:02, 325.82it/s]
 33%|███▎      | 330/1000 [00:01<00:02, 326.53it/s]
 36%|███▋      | 363/1000 [00:01<00:01, 326.75it/s]
 40%|███▉      | 396/1000 [00:01<00:01, 326.79it/s]
 43%|████▎     | 429/1000 [00:01<00:01, 326.82it/s]
 46%|████▌     | 462/1000 [00:01<00:01, 326.10it/s]
 50%|████▉     | 495/1000 [00:01<00:01, 326.40it/s]
 53%|█████▎    | 528/1000 [00:01<00:01, 326.82it/s]
 56%|█████▌    | 561/1000 [00:01<00:01, 326.92it/s]
 59%|█████▉    | 594/1000 [00:01<00:01, 327.04it/s]
 63%|██████▎   | 627/1000 [00:01<00:01, 326.93it/s]
 66%|██████▌   | 660/1000 [00:02<00:01, 326.86it/s]
 69%|██████▉   | 693/1000 [00:02<00:00, 325.20it/s]
 73%|███████▎  | 726/1000 [00:02<00:00, 326.35it/s]
 76%|███████▌  | 759/1000 [00:02<00:00, 327.29it/s]
 79%|███████▉  | 792/1000 [00:02<00:00, 327.55it/s]
 83%|████████▎ | 826/1000 [00:02<00:00, 328.32it/s]
 86%|████████▌ | 860/1000 [00:02<00:00, 328.90it/s]
 89%|████████▉ | 894/1000 [00:02<00:00, 329.09it/s]
 93%|█████████▎| 927/1000 [00:02<00:00, 327.79it/s]
 96%|█████████▌| 960/1000 [00:02<00:00, 327.29it/s]
 99%|█████████▉| 993/1000 [00:03<00:00, 325.73it/s]
+[codecarbon WARNING @ 11:54:47] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:54:47] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.3410181999206543 W
+[codecarbon DEBUG @ 11:54:47] RAM : 0.34 W during 3.07 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:54:47] Energy consumed for all GPUs : 0.000221 kWh. Total GPU Power : 85.03675977075001 W
+[codecarbon DEBUG @ 11:54:47] GPU : 85.04 W during 3.07 s [measurement time: 0.0027]
+[codecarbon INFO @ 11:54:47] Energy consumed for all CPUs : 0.000111 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:54:47] CPU : 42.50 W during 3.07 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:54:47] 0.000333 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:54:47] last_duration=3.066205707960762
+------------------------
+[codecarbon DEBUG @ 11:54:47] EmissionsData(timestamp='2024-12-06T11:54:47', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.0698766839923337, emissions=0.00012280197184959016, emissions_rate=4.000224910985279e-05, cpu_power=42.5, gpu_power=85.03675977075001, ram_power=0.3410181999206543, cpu_energy=0.00011089244820112882, gpu_energy=0.0002208979544953138, ram_energy=8.851192944630623e-07, energy_consumed=0.0003326755219909057, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:54:47] EmissionsData(timestamp='2024-12-06T11:54:47', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.005458462983369827, emissions=0.00012280197184959016, emissions_rate=0.022497536801793488, cpu_power=42.5, gpu_power=85.03675977075001, ram_power=0.3410181999206543, cpu_energy=0.00011089244820112882, gpu_energy=0.0002208979544953138, ram_energy=8.851192944630623e-07, energy_consumed=0.0003326755219909057, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 33/1000 [00:00<00:02, 326.36it/s]
  7%|▋         | 66/1000 [00:00<00:02, 319.32it/s]
 10%|▉         | 98/1000 [00:00<00:02, 318.16it/s]
 13%|█▎        | 131/1000 [00:00<00:02, 319.01it/s]
 16%|█▋        | 164/1000 [00:00<00:02, 319.73it/s]
 20%|█▉        | 197/1000 [00:00<00:02, 320.14it/s]
 23%|██▎       | 230/1000 [00:00<00:02, 318.02it/s]
 26%|██▌       | 262/1000 [00:00<00:02, 317.41it/s]
 30%|██▉       | 295/1000 [00:00<00:02, 318.40it/s]
 33%|███▎      | 327/1000 [00:01<00:02, 318.88it/s]
 36%|███▌      | 360/1000 [00:01<00:02, 319.35it/s]
 39%|███▉      | 392/1000 [00:01<00:01, 319.26it/s]
 42%|████▏     | 424/1000 [00:01<00:01, 319.43it/s]
 46%|████▌     | 456/1000 [00:01<00:01, 319.41it/s]
 49%|████▉     | 489/1000 [00:01<00:01, 319.94it/s]
 52%|█████▏    | 522/1000 [00:01<00:01, 320.30it/s]
 56%|█████▌    | 555/1000 [00:01<00:01, 320.62it/s]
 59%|█████▉    | 588/1000 [00:01<00:01, 320.43it/s]
 62%|██████▏   | 621/1000 [00:01<00:01, 320.33it/s]
 65%|██████▌   | 654/1000 [00:02<00:01, 319.72it/s]
 69%|██████▊   | 686/1000 [00:02<00:00, 319.08it/s]
 72%|███████▏  | 718/1000 [00:02<00:00, 319.15it/s]
 75%|███████▌  | 750/1000 [00:02<00:00, 319.29it/s]
 78%|███████▊  | 783/1000 [00:02<00:00, 320.01it/s]
 82%|████████▏ | 816/1000 [00:02<00:00, 319.36it/s]
 85%|████████▍ | 849/1000 [00:02<00:00, 319.60it/s]
 88%|████████▊ | 882/1000 [00:02<00:00, 320.21it/s]
 92%|█████████▏| 915/1000 [00:02<00:00, 320.15it/s]
 95%|█████████▍| 949/1000 [00:02<00:00, 323.37it/s]
 98%|█████████▊| 982/1000 [00:03<00:00, 325.28it/s]
+[codecarbon WARNING @ 11:54:50] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:54:50] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.3410196304321289 W
+[codecarbon DEBUG @ 11:54:50] RAM : 0.34 W during 3.13 s [measurement time: 0.0005]
+[codecarbon INFO @ 11:54:50] Energy consumed for all GPUs : 0.000293 kWh. Total GPU Power : 83.1441430170896 W
+[codecarbon DEBUG @ 11:54:50] GPU : 83.14 W during 3.13 s [measurement time: 0.0023]
+[codecarbon INFO @ 11:54:50] Energy consumed for all CPUs : 0.000148 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:54:50] CPU : 42.50 W during 3.13 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:54:50] 0.000442 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:54:50] last_duration=3.1264077610103413
+------------------------
+[codecarbon DEBUG @ 11:54:50] EmissionsData(timestamp='2024-12-06T11:54:50', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.1296109879622236, emissions=0.00016320993980941845, emissions_rate=5.215023222924232e-05, cpu_power=42.5, gpu_power=83.1441430170896, ram_power=0.3410196304321289, cpu_energy=0.00014783804723184508, gpu_energy=0.0002931230122751316, ram_energy=1.1812864376401158e-06, energy_consumed=0.0004421423459446168, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:54:50] EmissionsData(timestamp='2024-12-06T11:54:50', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.0020235819974914193, emissions=0.00016320993980941845, emissions_rate=0.08065397894018897, cpu_power=42.5, gpu_power=83.1441430170896, ram_power=0.3410196304321289, cpu_energy=0.00014783804723184508, gpu_energy=0.0002931230122751316, ram_energy=1.1812864376401158e-06, energy_consumed=0.0004421423459446168, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 33/1000 [00:00<00:02, 327.93it/s]
  7%|▋         | 66/1000 [00:00<00:02, 323.84it/s]
 10%|▉         | 99/1000 [00:00<00:02, 324.73it/s]
 13%|█▎        | 132/1000 [00:00<00:02, 325.68it/s]
 16%|█▋        | 165/1000 [00:00<00:02, 325.75it/s]
 20%|█▉        | 198/1000 [00:00<00:02, 326.45it/s]
 23%|██▎       | 231/1000 [00:00<00:02, 326.83it/s]
 26%|██▋       | 264/1000 [00:00<00:02, 327.11it/s]
 30%|██▉       | 297/1000 [00:00<00:02, 327.03it/s]
 33%|███▎      | 330/1000 [00:01<00:02, 327.11it/s]
 36%|███▋      | 363/1000 [00:01<00:01, 327.22it/s]
 40%|███▉      | 396/1000 [00:01<00:01, 326.96it/s]
 43%|████▎     | 429/1000 [00:01<00:01, 327.79it/s]
 46%|████▌     | 462/1000 [00:01<00:01, 327.68it/s]
 50%|████▉     | 495/1000 [00:01<00:01, 327.71it/s]
 53%|█████▎    | 528/1000 [00:01<00:01, 326.93it/s]
 56%|███���█▌    | 561/1000 [00:01<00:01, 326.89it/s]
 59%|█████▉    | 594/1000 [00:01<00:01, 326.94it/s]
 63%|██████▎   | 627/1000 [00:01<00:01, 326.92it/s]
 66%|██████▌   | 660/1000 [00:02<00:01, 327.35it/s]
 69%|██████▉   | 693/1000 [00:02<00:00, 327.47it/s]
 73%|███████▎  | 726/1000 [00:02<00:00, 327.41it/s]
 76%|███████▌  | 759/1000 [00:02<00:00, 327.50it/s]
 79%|███████▉  | 792/1000 [00:02<00:00, 327.44it/s]
 82%|████████▎ | 825/1000 [00:02<00:00, 326.28it/s]
 86%|████████▌ | 858/1000 [00:02<00:00, 326.65it/s]
 89%|████████▉ | 891/1000 [00:02<00:00, 326.94it/s]
 92%|█████████▏| 924/1000 [00:02<00:00, 327.05it/s]
 96%|█████████▌| 957/1000 [00:02<00:00, 327.27it/s]
 99%|█████████▉| 990/1000 [00:03<00:00, 327.25it/s]
+[codecarbon WARNING @ 11:54:53] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:54:53] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.34102392196655273 W
+[codecarbon DEBUG @ 11:54:53] RAM : 0.34 W during 3.06 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:54:53] Energy consumed for all GPUs : 0.000366 kWh. Total GPU Power : 85.22262567481995 W
+[codecarbon DEBUG @ 11:54:53] GPU : 85.22 W during 3.06 s [measurement time: 0.0034]
+[codecarbon INFO @ 11:54:53] Energy consumed for all CPUs : 0.000184 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:54:53] CPU : 42.50 W during 3.07 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:54:53] 0.000551 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:54:53] last_duration=3.0609874590300024
+------------------------
+[codecarbon DEBUG @ 11:54:53] EmissionsData(timestamp='2024-12-06T11:54:53', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.06525030604098, emissions=0.00020342958596682954, emissions_rate=6.636638631628599e-05, cpu_power=42.5, gpu_power=85.22262567481995, ram_power=0.34102392196655273, cpu_energy=0.00018402383632742895, gpu_energy=0.00036560390359241524, ram_energy=1.4712585783195841e-06, energy_consumed=0.0005510989984981638, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:54:53] EmissionsData(timestamp='2024-12-06T11:54:53', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.006924876011908054, emissions=0.00020342958596682954, emissions_rate=0.029376639468636105, cpu_power=42.5, gpu_power=85.22262567481995, ram_power=0.34102392196655273, cpu_energy=0.00018402383632742895, gpu_energy=0.00036560390359241524, ram_energy=1.4712585783195841e-06, energy_consumed=0.0005510989984981638, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 33/1000 [00:00<00:02, 325.98it/s]
  7%|▋         | 66/1000 [00:00<00:02, 326.73it/s]
 10%|▉         | 99/1000 [00:00<00:02, 327.17it/s]
 13%|█▎        | 132/1000 [00:00<00:02, 327.32it/s]
 16%|█▋        | 165/1000 [00:00<00:02, 327.19it/s]
 20%|█▉        | 198/1000 [00:00<00:02, 327.14it/s]
 23%|██▎       | 231/1000 [00:00<00:02, 325.95it/s]
 26%|██▋       | 264/1000 [00:00<00:02, 326.41it/s]
 30%|██▉       | 297/1000 [00:00<00:02, 326.52it/s]
 33%|███▎      | 330/1000 [00:01<00:02, 326.60it/s]
 36%|███▋      | 363/1000 [00:01<00:01, 326.00it/s]
 40%|███▉      | 396/1000 [00:01<00:01, 326.26it/s]
 43%|████▎     | 429/1000 [00:01<00:01, 326.40it/s]
 46%|████▌     | 462/1000 [00:01<00:01, 326.64it/s]
 50%|████▉     | 495/1000 [00:01<00:01, 326.91it/s]
 53%|█████▎    | 528/1000 [00:01<00:01, 327.02it/s]
 56%|█████▌    | 561/1000 [00:01<00:01, 326.70it/s]
 59%|█████▉    | 594/1000 [00:01<00:01, 325.71it/s]
 63%|██████▎   | 627/1000 [00:01<00:01, 325.87it/s]
 66%|██████▌   | 660/1000 [00:02<00:01, 324.38it/s]
 69%|██████▉   | 693/1000 [00:02<00:00, 325.23it/s]
 73%|███████▎  | 726/1000 [00:02<00:00, 325.63it/s]
 76%|███████▌  | 760/1000 [00:02<00:00, 327.25it/s]
 79%|███████▉  | 793/1000 [00:02<00:00, 325.87it/s]
 83%|████████▎ | 826/1000 [00:02<00:00, 326.15it/s]
 86%|████████▌ | 859/1000 [00:02<00:00, 326.42it/s]
 89%|████████▉ | 892/1000 [00:02<00:00, 326.59it/s]
 92%|█████████▎| 925/1000 [00:02<00:00, 326.71it/s]
 96%|█████████▌| 958/1000 [00:02<00:00, 326.80it/s]
 99%|█████████▉| 991/1000 [00:03<00:00, 322.46it/s]
+[codecarbon WARNING @ 11:54:56] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:54:56] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34102964401245117 W
+[codecarbon DEBUG @ 11:54:56] RAM : 0.34 W during 3.08 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:54:56] Energy consumed for all GPUs : 0.000436 kWh. Total GPU Power : 82.04566114201081 W
+[codecarbon DEBUG @ 11:54:56] GPU : 82.05 W during 3.08 s [measurement time: 0.0023]
+[codecarbon INFO @ 11:54:56] Energy consumed for all CPUs : 0.000220 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:54:56] CPU : 42.50 W during 3.08 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:54:56] 0.000658 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:54:56] last_duration=3.0761995050124824
+------------------------
+[codecarbon DEBUG @ 11:54:56] EmissionsData(timestamp='2024-12-06T11:54:56', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.0793501819716766, emissions=0.00024284179958616934, emissions_rate=7.886137828945463e-05, cpu_power=42.5, gpu_power=82.04566114201081, ram_power=0.34102964401245117, cpu_energy=0.0002203760916303307, gpu_energy=0.00043572951524950554, ram_energy=1.7626766807049815e-06, energy_consumed=0.0006578682835605413, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:54:56] EmissionsData(timestamp='2024-12-06T11:54:56', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.005169034004211426, emissions=0.00024284179958616934, emissions_rate=0.046980112606788055, cpu_power=42.5, gpu_power=82.04566114201081, ram_power=0.34102964401245117, cpu_energy=0.0002203760916303307, gpu_energy=0.00043572951524950554, ram_energy=1.7626766807049815e-06, energy_consumed=0.0006578682835605413, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 33/1000 [00:00<00:02, 325.92it/s]
  7%|▋         | 66/1000 [00:00<00:02, 326.72it/s]
 10%|▉         | 99/1000 [00:00<00:02, 327.75it/s]
 13%|█▎        | 132/1000 [00:00<00:02, 327.44it/s]
 16%|█▋        | 165/1000 [00:00<00:02, 320.79it/s]
 20%|█▉        | 198/1000 [00:00<00:02, 320.00it/s]
 23%|██▎       | 231/1000 [00:00<00:02, 315.45it/s]
 26%|██▋       | 263/1000 [00:00<00:02, 313.36it/s]
 30%|██▉       | 295/1000 [00:00<00:02, 309.30it/s]
 33%|███▎      | 326/1000 [00:01<00:02, 307.50it/s]
 36%|███▌      | 357/1000 [00:01<00:02, 306.98it/s]
 39%|███▉      | 388/1000 [00:01<00:01, 307.23it/s]
 42%|████▏     | 419/1000 [00:01<00:01, 306.67it/s]
 45%|████▌     | 450/1000 [00:01<00:01, 306.88it/s]
 48%|████▊     | 481/1000 [00:01<00:01, 305.78it/s]
 51%|█████     | 512/1000 [00:01<00:01, 305.73it/s]
 54%|█████▍    | 543/1000 [00:01<00:01, 306.05it/s]
 57%|█████▋    | 574/1000 [00:01<00:01, 306.76it/s]
 61%|██████    | 606/1000 [00:01<00:01, 307.81it/s]
 64%|██████▎   | 637/1000 [00:02<00:01, 307.53it/s]
 67%|██████▋   | 669/1000 [00:02<00:01, 308.34it/s]
 70%|███████   | 701/1000 [00:02<00:00, 308.94it/s]
 73%|███████▎  | 732/1000 [00:02<00:00, 308.72it/s]
 76%|███████▋  | 763/1000 [00:02<00:00, 307.97it/s]
 79%|███████▉  | 794/1000 [00:02<00:00, 307.11it/s]
 82%|████████▎ | 825/1000 [00:02<00:00, 306.59it/s]
 86%|████████▌ | 856/1000 [00:02<00:00, 306.58it/s]
 89%|████████▊ | 887/1000 [00:02<00:00, 306.47it/s]
 92%|█████████▏| 918/1000 [00:02<00:00, 306.92it/s]
 95%|█████████▍| 949/1000 [00:03<00:00, 306.27it/s]
 98%|█████████▊| 980/1000 [00:03<00:00, 306.93it/s]
+[codecarbon WARNING @ 11:54:59] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:54:59] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34102964401245117 W
+[codecarbon DEBUG @ 11:54:59] RAM : 0.34 W during 3.23 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:54:59] Energy consumed for all GPUs : 0.000512 kWh. Total GPU Power : 85.16727616836089 W
+[codecarbon DEBUG @ 11:54:59] GPU : 85.17 W during 3.23 s [measurement time: 0.0023]
+[codecarbon INFO @ 11:54:59] Energy consumed for all CPUs : 0.000259 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:54:59] CPU : 42.50 W during 3.24 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:54:59] 0.000773 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:54:59] EmissionsData(timestamp='2024-12-06T11:54:59', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.2372844429919496, emissions=0.000285311941280839, emissions_rate=8.81331085683497e-05, cpu_power=42.5, gpu_power=85.16727616836089, ram_power=0.34102964401245117, cpu_energy=0.00025859298852204426, gpu_energy=0.0005122595764728288, ram_energy=2.0690547987955964e-06, energy_consumed=0.0007729216197936687, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon INFO @ 11:54:59] 0.013140 g.CO2eq/s mean an estimation of 414.38445692833943 kg.CO2eq/year
+[codecarbon DEBUG @ 11:54:59] last_duration=3.2341102859936655
+------------------------
+[codecarbon DEBUG @ 11:54:59] EmissionsData(timestamp='2024-12-06T11:54:59', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.237630599993281, emissions=0.000285311941280839, emissions_rate=8.812368566118416e-05, cpu_power=42.5, gpu_power=85.16727616836089, ram_power=0.34102964401245117, cpu_energy=0.00025859298852204426, gpu_energy=0.0005122595764728288, ram_energy=2.0690547987955964e-06, energy_consumed=0.0007729216197936687, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:54:59] EmissionsData(timestamp='2024-12-06T11:54:59', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.005460618995130062, emissions=0.000285311941280839, emissions_rate=0.05224901087867299, cpu_power=42.5, gpu_power=85.16727616836089, ram_power=0.34102964401245117, cpu_energy=0.00025859298852204426, gpu_energy=0.0005122595764728288, ram_energy=2.0690547987955964e-06, energy_consumed=0.0007729216197936687, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 31/1000 [00:00<00:03, 307.34it/s]
  6%|▌         | 62/1000 [00:00<00:03, 308.89it/s]
  9%|▉         | 93/1000 [00:00<00:02, 305.80it/s]
 13%|█▎        | 126/1000 [00:00<00:02, 313.60it/s]
 16%|█▌        | 159/1000 [00:00<00:02, 318.74it/s]
 19%|█▉        | 192/1000 [00:00<00:02, 322.43it/s]
 22%|██▎       | 225/1000 [00:00<00:02, 324.85it/s]
 26%|██▌       | 258/1000 [00:00<00:02, 325.70it/s]
 29%|██▉       | 291/1000 [00:00<00:02, 325.78it/s]
 32%|███▏      | 324/1000 [00:01<00:02, 326.71it/s]
 36%|███▌      | 357/1000 [00:01<00:01, 327.65it/s]
 39%|███▉      | 391/1000 [00:01<00:01, 328.41it/s]
 42%|████▏     | 424/1000 [00:01<00:01, 326.39it/s]
 46%|████▌     | 457/1000 [00:01<00:01, 322.39it/s]
 49%|████▉     | 490/1000 [00:01<00:01, 320.61it/s]
 52%|█████▏    | 523/1000 [00:01<00:01, 319.54it/s]
 56%|█████▌    | 555/1000 [00:01<00:01, 317.62it/s]
 59%|█████▊    | 587/1000 [00:01<00:01, 317.53it/s]
 62%|██████▏   | 620/1000 [00:01<00:01, 319.20it/s]
 65%|██████▌   | 653/1000 [00:02<00:01, 321.46it/s]
 69%|██████▊   | 686/1000 [00:02<00:00, 322.83it/s]
 72%|███████▏  | 719/1000 [00:02<00:00, 322.78it/s]
 75%|███████▌  | 752/1000 [00:02<00:00, 318.29it/s]
 78%|███████▊  | 784/1000 [00:02<00:00, 316.84it/s]
 82%|████████▏ | 816/1000 [00:02<00:00, 316.92it/s]
 85%|████████▍ | 849/1000 [00:02<00:00, 319.96it/s]
 88%|████████▊ | 882/1000 [00:02<00:00, 321.79it/s]
 92%|█████████▏| 915/1000 [00:02<00:00, 322.97it/s]
 95%|█████████▍| 949/1000 [00:02<00:00, 325.17it/s]
 98%|█████████▊| 982/1000 [00:03<00:00, 326.10it/s]
+[codecarbon WARNING @ 11:55:02] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:55:02] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34102964401245117 W
+[codecarbon DEBUG @ 11:55:02] RAM : 0.34 W during 3.11 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:55:02] Energy consumed for all GPUs : 0.000585 kWh. Total GPU Power : 83.52648371244042 W
+[codecarbon DEBUG @ 11:55:02] GPU : 83.53 W during 3.12 s [measurement time: 0.0023]
+[codecarbon INFO @ 11:55:02] Energy consumed for all CPUs : 0.000295 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:55:02] CPU : 42.50 W during 3.12 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:55:02] 0.000882 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:55:02] last_duration=3.1142306780675426
+------------------------
+[codecarbon DEBUG @ 11:55:02] EmissionsData(timestamp='2024-12-06T11:55:02', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.117404957069084, emissions=0.000325684342405636, emissions_rate=0.00010447290194593046, cpu_power=42.5, gpu_power=83.52648371244042, ram_power=0.34102964401245117, cpu_energy=0.0002953944923660149, gpu_energy=0.0005845335231811077, ram_energy=2.3640762017397193e-06, energy_consumed=0.0008822920917488623, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:55:02] EmissionsData(timestamp='2024-12-06T11:55:02', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.0061563539784401655, emissions=0.000325684342405636, emissions_rate=0.052902146878850295, cpu_power=42.5, gpu_power=83.52648371244042, ram_power=0.34102964401245117, cpu_energy=0.0002953944923660149, gpu_energy=0.0005845335231811077, ram_energy=2.3640762017397193e-06, energy_consumed=0.0008822920917488623, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 33/1000 [00:00<00:02, 327.90it/s]
  7%|▋         | 66/1000 [00:00<00:02, 324.40it/s]
 10%|▉         | 99/1000 [00:00<00:02, 324.89it/s]
 13%|█▎        | 132/1000 [00:00<00:02, 325.79it/s]
 16%|█▋        | 165/1000 [00:00<00:02, 326.63it/s]
 20%|█▉        | 198/1000 [00:00<00:02, 326.90it/s]
 23%|██▎       | 232/1000 [00:00<00:02, 328.78it/s]
 27%|██▋       | 266/1000 [00:00<00:02, 329.70it/s]
 30%|███       | 300/1000 [00:00<00:02, 330.30it/s]
 33%|███▎      | 334/1000 [00:01<00:02, 330.54it/s]
 37%|███▋      | 368/1000 [00:01<00:01, 330.89it/s]
 40%|████      | 402/1000 [00:01<00:01, 330.98it/s]
 44%|████▎     | 436/1000 [00:01<00:01, 330.48it/s]
 47%|████▋     | 470/1000 [00:01<00:01, 330.53it/s]
 50%|█████     | 504/1000 [00:01<00:01, 328.75it/s]
 54%|█████▍    | 538/1000 [00:01<00:01, 329.19it/s]
 57%|█████▋    | 571/1000 [00:01<00:01, 328.53it/s]
 60%|██████    | 604/1000 [00:01<00:01, 328.59it/s]
 64%|██████▍   | 638/1000 [00:01<00:01, 329.11it/s]
 67%|██████▋   | 671/1000 [00:02<00:01, 328.50it/s]
 70%|███████   | 704/1000 [00:02<00:00, 327.31it/s]
 74%|███████▎  | 737/1000 [00:02<00:00, 327.66it/s]
 77%|███████▋  | 770/1000 [00:02<00:00, 325.85it/s]
 80%|████████  | 803/1000 [00:02<00:00, 325.77it/s]
 84%|████████▎ | 836/1000 [00:02<00:00, 326.69it/s]
 87%|████████▋ | 870/1000 [00:02<00:00, 327.75it/s]
 90%|█████████ | 903/1000 [00:02<00:00, 328.17it/s]
 94%|████���████▎| 936/1000 [00:02<00:00, 328.22it/s]
 97%|█████████▋| 969/1000 [00:02<00:00, 324.66it/s]
+[codecarbon WARNING @ 11:55:05] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:55:05] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.34102964401245117 W
+[codecarbon DEBUG @ 11:55:05] RAM : 0.34 W during 3.06 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:55:05] Energy consumed for all GPUs : 0.000657 kWh. Total GPU Power : 85.38302340193269 W
+[codecarbon DEBUG @ 11:55:05] GPU : 85.38 W during 3.06 s [measurement time: 0.0028]
+[codecarbon INFO @ 11:55:05] Energy consumed for all CPUs : 0.000332 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:55:05] CPU : 42.50 W during 3.06 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:55:05] 0.000991 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:55:05] last_duration=3.0558626130223274
+------------------------
+[codecarbon DEBUG @ 11:55:05] EmissionsData(timestamp='2024-12-06T11:55:05', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.059523609932512, emissions=0.0003658843979281712, emissions_rate=0.0001195886826107029, cpu_power=42.5, gpu_power=85.38302340193269, ram_power=0.34102964401245117, cpu_energy=0.0003315126895208475, gpu_energy=0.000657029414512067, ram_energy=2.6535684451152707e-06, energy_consumed=0.0009911956724780297, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:55:05] EmissionsData(timestamp='2024-12-06T11:55:05', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=0.005146795068867505, emissions=0.0003658843979281712, emissions_rate=0.0710897545039966, cpu_power=42.5, gpu_power=85.38302340193269, ram_power=0.34102964401245117, cpu_energy=0.0003315126895208475, gpu_energy=0.000657029414512067, ram_energy=2.6535684451152707e-06, energy_consumed=0.0009911956724780297, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 33/1000 [00:00<00:02, 327.82it/s]
  7%|▋         | 66/1000 [00:00<00:02, 327.31it/s]
 10%|▉         | 99/1000 [00:00<00:02, 328.39it/s]
 13%|█▎        | 132/1000 [00:00<00:02, 328.29it/s]
 16%|█▋        | 165/1000 [00:00<00:02, 327.43it/s]
 20%|█▉        | 198/1000 [00:00<00:02, 328.12it/s]
 23%|██▎       | 231/1000 [00:00<00:02, 328.55it/s]
 26%|██▋       | 265/1000 [00:00<00:02, 329.40it/s]
 30%|██▉       | 299/1000 [00:00<00:02, 330.27it/s]
 33%|███▎      | 333/1000 [00:01<00:02, 330.64it/s]
 37%|███▋      | 367/1000 [00:01<00:01, 329.99it/s]
 40%|████      | 400/1000 [00:01<00:01, 326.81it/s]
 43%|████▎     | 433/1000 [00:01<00:01, 326.22it/s]
 47%|████▋     | 466/1000 [00:01<00:01, 324.07it/s]
 50%|████▉     | 499/1000 [00:01<00:01, 322.23it/s]
 53%|█████▎    | 532/1000 [00:01<00:01, 324.08it/s]
 56%|█████▋    | 565/1000 [00:01<00:01, 324.52it/s]
 60%|█████▉    | 598/1000 [00:01<00:01, 325.06it/s]
 63%|██████▎   | 631/1000 [00:01<00:01, 325.58it/s]
 66%|██████▋   | 665/1000 [00:02<00:01, 326.98it/s]
 70%|██████▉   | 699/1000 [00:02<00:00, 328.33it/s]
 73%|███████▎  | 733/1000 [00:02<00:00, 328.89it/s]
 77%|███████▋  | 767/1000 [00:02<00:00, 329.89it/s]
 80%|████████  | 800/1000 [00:02<00:00, 329.60it/s]
 83%|████████▎ | 833/1000 [00:02<00:00, 329.66it/s]
 87%|████████▋ | 867/1000 [00:02<00:00, 330.47it/s]
 90%|█████████ | 901/1000 [00:02<00:00, 329.36it/s]
 93%|█████████▎| 934/1000 [00:02<00:00, 328.30it/s]
 97%|█████████▋| 967/1000 [00:02<00:00, 326.14it/s]
+[codecarbon WARNING @ 11:55:08] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:55:08] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.34102964401245117 W
+[codecarbon DEBUG @ 11:55:08] RAM : 0.34 W during 3.06 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:55:08] Energy consumed for all GPUs : 0.000727 kWh. Total GPU Power : 82.44288426325188 W
+[codecarbon DEBUG @ 11:55:08] GPU : 82.44 W during 3.06 s [measurement time: 0.0041]
+[codecarbon INFO @ 11:55:08] Energy consumed for all CPUs : 0.000368 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:55:08] CPU : 42.50 W during 3.06 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:55:08] 0.001098 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:55:08] last_duration=3.0590055210050195
+------------------------
+[codecarbon DEBUG @ 11:55:08] EmissionsData(timestamp='2024-12-06T11:55:08', project_name='codecarbon', run_id='50f18221-7dc0-46e0-bca5-bfe7b7700d1e', duration=3.0640405940357596, emissions=0.0004052094001913277, emissions_rate=0.00013224674665866996, cpu_power=42.5, gpu_power=82.44288426325188, ram_power=0.34102964401245117, cpu_energy=0.0003676842035515519, gpu_energy=0.0007271011372349534, ram_energy=2.943357653133025e-06, energy_consumed=0.0010977286984396384, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)

sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "sentence_similarity_udever-bloom-7b1",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "sentence-similarity",
+        "model": "sentence-transformers/multi-qa-MiniLM-L6-cos-v1",
+        "processor": "sentence-transformers/multi-qa-MiniLM-L6-cos-v1",
+        "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/sentence_similarity",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}

sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-06T11:55:08",
+    "project_name": "codecarbon",
+    "run_id": "50f18221-7dc0-46e0-bca5-bfe7b7700d1e",
+    "duration": -1732784632.2426775,
+    "emissions": 3.932500226315651e-05,
+    "emissions_rate": 1.2855955403367746e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 82.44288426325188,
+    "ram_power": 0.34102964401245117,
+    "cpu_energy": 3.6171514030704384e-05,
+    "gpu_energy": 7.007172272288642e-05,
+    "ram_energy": 2.897892080177542e-07,
+    "energy_consumed": 0.00010653302596160875,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

sentence_similarity/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/2024-12-06-11-54-25/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-06T11:54:37",
+    "project_name": "codecarbon",
+    "run_id": "50f18221-7dc0-46e0-bca5-bfe7b7700d1e",
+    "duration": -1732784635.1402123,
+    "emissions": 2.163673245772878e-06,
+    "emissions_rate": 1.3402231572805124e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 87.50892425306003,
+    "ram_power": 0.2656216621398926,
+    "cpu_energy": 1.929911376969863e-06,
+    "gpu_energy": 3.919725356738013e-06,
+    "ram_energy": 1.184183714824478e-08,
+    "energy_consumed": 5.861478570856121e-06,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: sentence-similarity
+  model: sentence-transformers/paraphrase-MiniLM-L6-v2
+  processor: sentence-transformers/paraphrase-MiniLM-L6-v2
+  library: transformers
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/sentence_similarity
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: sentence_similarity_udever-bloom-7b1
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null

sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40
+    - hydra.mode=RUN
+    task:
+    - backend.model=sentence-transformers/paraphrase-MiniLM-L6-v2
+    - backend.processor=sentence-transformers/paraphrase-MiniLM-L6-v2
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=sentence-transformers/paraphrase-MiniLM-L6-v2,backend.processor=sentence-transformers/paraphrase-MiniLM-L6-v2
+    id: ???
+    num: ???
+    config_name: sentence_similarity
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=sentence-transformers/paraphrase-MiniLM-L6-v2
+- backend.processor=sentence-transformers/paraphrase-MiniLM-L6-v2

sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40/benchmark_report.json

@@ -0,0 +1,107 @@
+{
+    "forward": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 3.4468999509513705e-05,
+            "ram": 2.763694540518881e-07,
+            "gpu": 6.661883107277334e-05,
+            "total": 0.00010136420003633896
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 9865415.991459519
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 3.927416051309491e-05,
+                "ram": 3.1454335409563166e-07,
+                "gpu": 7.55081159606874e-05,
+                "total": 0.00011509681982787795
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.8126175777061784e-05,
+                "ram": 3.057966867990314e-07,
+                "gpu": 7.268783592984107e-05,
+                "total": 0.00011111980839370186
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.9340533294873444e-05,
+                "ram": 3.1546451760772435e-07,
+                "gpu": 7.464255971356692e-05,
+                "total": 0.0001142985575260481
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.8453094514099786e-05,
+                "ram": 3.084379334984966e-07,
+                "gpu": 7.504700448102142e-05,
+                "total": 0.0001138085369286197
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.7455039672123456e-05,
+                "ram": 3.0013881302259415e-07,
+                "gpu": 7.31953363342086e-05,
+                "total": 0.00011095051481935475
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.709253746904628e-05,
+                "ram": 2.9751805022184296e-07,
+                "gpu": 7.10145012572383e-05,
+                "total": 0.0001084045567765064
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.8820853530584546e-05,
+                "ram": 3.111883252272314e-07,
+                "gpu": 7.524200463748798e-05,
+                "total": 0.00011437404649329976
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.7991226943348794e-05,
+                "ram": 3.047267319411077e-07,
+                "gpu": 7.328005862383691e-05,
+                "total": 0.00011157601229912694
+            },
+            {
+                "unit": "kWh",
+                "cpu": 3.8136373380904024e-05,
+                "ram": 3.0588012810522036e-07,
+                "gpu": 7.557089378984472e-05,
+                "total": 0.00011401314729885415
+            }
+        ]
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 1.9664361006612634e-06,
+            "ram": 1.2095510410428298e-08,
+            "gpu": 3.7922252573707738e-06,
+            "total": 5.770756868442466e-06
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 173287494.6557749
+        },
+        "measures": null
+    }
+}

sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40/cli.log

@@ -0,0 +1,113 @@
+[2024-12-06 11:37:43,622][launcher][INFO] - ََAllocating process launcher
+[2024-12-06 11:37:43,623][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-06 11:37:43,634][device-isolation][INFO] - 	+ Launched device(s) isolation process 181
+[2024-12-06 11:37:43,634][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-06 11:37:43,639][process][INFO] - 	+ Launched benchmark in isolated process 182.
+[PROC-0][2024-12-06 11:37:46,360][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-06 11:37:47,287][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-06 11:37:47,288][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-06 11:37:47,799][pytorch][INFO] - 	+ Using AutoModel class AutoModel
+[PROC-0][2024-12-06 11:37:47,799][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-06 11:37:47,799][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-06 11:37:47,799][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-06 11:37:47,799][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-06 11:37:47,799][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-06 11:37:47,801][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-06 11:37:47,802][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-06 11:37:47,803][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-06 11:37:47,803][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-06 11:37:48,127][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-06 11:37:48,133][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-06 11:37:48,133][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-06 11:37:49,331][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-06 11:37:49,331][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-06 11:37:53,510][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-06 11:37:53,677][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-06 11:37:53,677][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-06 11:37:53,678][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-06 11:37:53,678][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-06 11:37:54,356][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-06 11:37:54,356][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-06 11:37:57,683][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:37:57,684][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-06 11:38:00,914][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:38:00,914][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-06 11:38:04,247][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:38:04,248][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-06 11:38:07,506][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:38:07,506][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-06 11:38:10,679][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:38:10,680][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-06 11:38:13,822][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:38:13,823][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-06 11:38:17,027][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:38:17,027][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-06 11:38:20,316][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:38:20,316][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-06 11:38:23,535][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:38:23,535][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-06 11:38:26,766][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-06 11:38:26,767][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-06 11:38:26,767][energy][INFO] - 			+ CPU: 0.000034 (kWh)
+[PROC-0][2024-12-06 11:38:26,767][energy][INFO] - 			+ GPU: 0.000067 (kWh)
+[PROC-0][2024-12-06 11:38:26,767][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,767][energy][INFO] - 			+ total: 0.000101 (kWh)
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 			+ CPU: 0.000039 (kWh)
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 			+ GPU: 0.000076 (kWh)
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 			+ total: 0.000115 (kWh)
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 			+ GPU: 0.000073 (kWh)
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 			+ total: 0.000111 (kWh)
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-06 11:38:26,768][energy][INFO] - 			+ CPU: 0.000039 (kWh)
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 			+ GPU: 0.000075 (kWh)
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 			+ total: 0.000114 (kWh)
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 			+ GPU: 0.000075 (kWh)
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 			+ total: 0.000114 (kWh)
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 			+ CPU: 0.000037 (kWh)
+[PROC-0][2024-12-06 11:38:26,769][energy][INFO] - 			+ GPU: 0.000073 (kWh)
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 			+ total: 0.000111 (kWh)
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 			+ CPU: 0.000037 (kWh)
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 			+ GPU: 0.000071 (kWh)
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 			+ total: 0.000108 (kWh)
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,770][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 			+ CPU: 0.000039 (kWh)
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 			+ GPU: 0.000075 (kWh)
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 			+ total: 0.000114 (kWh)
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 			+ GPU: 0.000073 (kWh)
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 			+ total: 0.000112 (kWh)
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-06 11:38:26,771][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-06 11:38:26,772][energy][INFO] - 			+ GPU: 0.000076 (kWh)
+[PROC-0][2024-12-06 11:38:26,772][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,772][energy][INFO] - 			+ total: 0.000114 (kWh)
+[PROC-0][2024-12-06 11:38:26,772][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-06 11:38:26,772][energy][INFO] - 			+ CPU: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:38:26,772][energy][INFO] - 			+ GPU: 0.000004 (kWh)
+[PROC-0][2024-12-06 11:38:26,772][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:38:26,772][energy][INFO] - 			+ total: 0.000006 (kWh)
+[PROC-0][2024-12-06 11:38:26,772][energy][INFO] - 		+ forward energy efficiency: 9865415.991460 (samples/kWh)
+[PROC-0][2024-12-06 11:38:26,772][energy][INFO] - 		+ preprocess energy efficiency: 173287494.655775 (samples/kWh)
+[2024-12-06 11:38:27,430][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-06 11:38:27,482][datasets][INFO] - PyTorch version 2.4.0 available.

sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40/error.log

@@ -0,0 +1,178 @@
+/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
+  warnings.warn(
+
+
+
+
+
+
+
+[codecarbon INFO @ 11:37:49] [setup] RAM Tracking...
+[codecarbon INFO @ 11:37:49] [setup] GPU Tracking...
+[codecarbon INFO @ 11:37:49] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 11:37:49] GPU available. Starting setup
+[codecarbon INFO @ 11:37:49] [setup] CPU Tracking...
+[codecarbon DEBUG @ 11:37:49] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 11:37:49] 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 @ 11:37:49] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 11:37:49] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 11:37:50] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 11:37:50] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 11:37:50] >>> Tracker's metadata:
+[codecarbon INFO @ 11:37:50]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 11:37:50]   Python version: 3.9.20
+[codecarbon INFO @ 11:37:50]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 11:37:50]   Available RAM : 186.705 GB
+[codecarbon INFO @ 11:37:50]   CPU count: 48
+[codecarbon INFO @ 11:37:50]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 11:37:50]   GPU count: 1
+[codecarbon INFO @ 11:37:50]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 11:37:51] Not running on AWS
+[codecarbon DEBUG @ 11:37:52] Not running on Azure
+[codecarbon DEBUG @ 11:37:53] Not running on GCP
+[codecarbon INFO @ 11:37:53] Saving emissions data to file /runs/sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40/codecarbon.csv
+[codecarbon DEBUG @ 11:37:53] EmissionsData(timestamp='2024-12-06T11:37:53', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.0021536439890041947, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
+
+[codecarbon INFO @ 11:37:53] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.26796913146972656 W
+[codecarbon DEBUG @ 11:37:53] RAM : 0.27 W during 0.16 s [measurement time: 0.0005]
+[codecarbon INFO @ 11:37:53] Energy consumed for all GPUs : 0.000004 kWh. Total GPU Power : 83.59350259699416 W
+[codecarbon DEBUG @ 11:37:53] GPU : 83.59 W during 0.16 s [measurement time: 0.0032]
+[codecarbon INFO @ 11:37:53] Energy consumed for all CPUs : 0.000002 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:37:53] CPU : 42.50 W during 0.17 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:37:53] 0.000006 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:37:53] last_duration=0.1624931920086965
+------------------------
+[codecarbon DEBUG @ 11:37:53] EmissionsData(timestamp='2024-12-06T11:37:53', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.16667619696818292, emissions=2.1301847465912246e-06, emissions_rate=1.2780377674430974e-05, cpu_power=42.5, gpu_power=83.59350259699416, ram_power=0.26796913146972656, cpu_energy=1.9664361006612634e-06, gpu_energy=3.7922252573707738e-06, ram_energy=1.2095510410428298e-08, energy_consumed=5.770756868442466e-06, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:37:54] EmissionsData(timestamp='2024-12-06T11:37:54', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.0022446849616244435, emissions=2.1301847465912246e-06, emissions_rate=0.0009489905189410825, cpu_power=42.5, gpu_power=83.59350259699416, ram_power=0.26796913146972656, cpu_energy=1.9664361006612634e-06, gpu_energy=3.7922252573707738e-06, ram_energy=1.2095510410428298e-08, energy_consumed=5.770756868442466e-06, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 31/1000 [00:00<00:03, 309.49it/s]
  6%|▋         | 63/1000 [00:00<00:02, 313.68it/s]
 10%|▉         | 95/1000 [00:00<00:02, 308.36it/s]
 13%|█▎        | 126/1000 [00:00<00:02, 304.98it/s]
 16%|█▌        | 157/1000 [00:00<00:02, 303.16it/s]
 19%|█▉        | 188/1000 [00:00<00:02, 299.69it/s]
 22%|██▏       | 219/1000 [00:00<00:02, 299.91it/s]
 25%|██▌       | 250/1000 [00:00<00:02, 301.14it/s]
 28%|██▊       | 282/1000 [00:00<00:02, 306.70it/s]
 31%|███▏      | 313/1000 [00:01<00:02, 306.52it/s]
 34%|███▍      | 344/1000 [00:01<00:02, 304.79it/s]
 38%|███▊      | 375/1000 [00:01<00:02, 302.86it/s]
 41%|████      | 406/1000 [00:01<00:01, 302.18it/s]
 44%|████▎     | 437/1000 [00:01<00:01, 301.68it/s]
 47%|████▋     | 468/1000 [00:01<00:01, 301.42it/s]
 50%|████▉     | 499/1000 [00:01<00:01, 300.60it/s]
 53%|█████▎    | 530/1000 [00:01<00:01, 300.53it/s]
 56%|█████▌    | 561/1000 [00:01<00:01, 300.65it/s]
 59%|█████▉    | 592/1000 [00:01<00:01, 300.56it/s]
 62%|██████▏   | 623/1000 [00:02<00:01, 300.65it/s]
 65%|██████▌   | 654/1000 [00:02<00:01, 299.96it/s]
 68%|██████▊   | 685/1000 [00:02<00:01, 300.40it/s]
 72%|███████▏  | 716/1000 [00:02<00:00, 300.62it/s]
 75%|███████▍  | 747/1000 [00:02<00:00, 300.69it/s]
 78%|███████▊  | 778/1000 [00:02<00:00, 300.43it/s]
 81%|████████  | 809/1000 [00:02<00:00, 299.94it/s]
 84%|████████▍ | 839/1000 [00:02<00:00, 299.74it/s]
 87%|████████▋ | 870/1000 [00:02<00:00, 300.09it/s]
 90%|█████████ | 901/1000 [00:02<00:00, 299.09it/s]
 93%|█████████▎| 932/1000 [00:03<00:00, 299.45it/s]
 96%|█████████▌| 962/1000 [00:03<00:00, 299.13it/s]
 99%|█████████▉| 993/1000 [00:03<00:00, 299.59it/s]
+[codecarbon WARNING @ 11:37:57] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:37:57] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.34110689163208013 W
+[codecarbon DEBUG @ 11:37:57] RAM : 0.34 W during 3.32 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:37:57] Energy consumed for all GPUs : 0.000079 kWh. Total GPU Power : 81.8685446170856 W
+[codecarbon DEBUG @ 11:37:57] GPU : 81.87 W during 3.32 s [measurement time: 0.0064]
+[codecarbon INFO @ 11:37:57] Energy consumed for all CPUs : 0.000041 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:37:57] CPU : 42.50 W during 3.33 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:37:57] 0.000121 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:37:57] last_duration=3.319424900924787
+------------------------
+[codecarbon DEBUG @ 11:37:57] EmissionsData(timestamp='2024-12-06T11:37:57', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.326852821977809, emissions=4.4616377730957537e-05, emissions_rate=1.3410986334055248e-05, cpu_power=42.5, gpu_power=81.8685446170856, ram_power=0.34110689163208013, cpu_energy=4.124059661375617e-05, gpu_energy=7.930034121805818e-05, ram_energy=3.2663886450605997e-07, energy_consumed=0.00012086757669632041, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:37:57] EmissionsData(timestamp='2024-12-06T11:37:57', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.00204054091591388, emissions=4.4616377730957537e-05, emissions_rate=0.021864975792938498, cpu_power=42.5, gpu_power=81.8685446170856, ram_power=0.34110689163208013, cpu_energy=4.124059661375617e-05, gpu_energy=7.930034121805818e-05, ram_energy=3.2663886450605997e-07, energy_consumed=0.00012086757669632041, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 32/1000 [00:00<00:03, 318.82it/s]
  6%|▋         | 64/1000 [00:00<00:02, 319.51it/s]
 10%|▉         | 96/1000 [00:00<00:02, 318.95it/s]
 13%|█▎        | 128/1000 [00:00<00:02, 319.34it/s]
 16%|█▌        | 161/1000 [00:00<00:02, 319.72it/s]
 19%|█▉        | 194/1000 [00:00<00:02, 320.15it/s]
 23%|██▎       | 227/1000 [00:00<00:02, 320.13it/s]
 26%|██▌       | 260/1000 [00:00<00:02, 321.57it/s]
 29%|██▉       | 293/1000 [00:00<00:02, 320.50it/s]
 33%|███▎      | 326/1000 [00:01<00:02, 320.31it/s]
 36%|███▌      | 359/1000 [00:01<00:02, 320.38it/s]
 39%|███▉      | 392/1000 [00:01<00:01, 319.48it/s]
 42%|████▎     | 425/1000 [00:01<00:01, 319.71it/s]
 46%|████▌     | 457/1000 [00:01<00:01, 319.69it/s]
 49%|████▉     | 490/1000 [00:01<00:01, 319.95it/s]
 52%|█████▏    | 522/1000 [00:01<00:01, 314.02it/s]
 55%|█████▌    | 554/1000 [00:01<00:01, 310.47it/s]
 59%|█████▊    | 586/1000 [00:01<00:01, 307.91it/s]
 62%|██████▏   | 617/1000 [00:01<00:01, 305.31it/s]
 65%|██████▍   | 648/1000 [00:02<00:01, 304.22it/s]
 68%|██████▊   | 679/1000 [00:02<00:01, 303.44it/s]
 71%|███████   | 710/1000 [00:02<00:00, 302.68it/s]
 74%|███████▍  | 741/1000 [00:02<00:00, 302.41it/s]
 77%|███████▋  | 772/1000 [00:02<00:00, 302.14it/s]
 80%|████████  | 803/1000 [00:02<00:00, 302.12it/s]
 83%|████████▎ | 834/1000 [00:02<00:00, 302.00it/s]
 86%|████████▋ | 865/1000 [00:02<00:00, 302.03it/s]
 90%|████████▉ | 896/1000 [00:02<00:00, 303.48it/s]
 93%|█████████▎| 927/1000 [00:02<00:00, 302.29it/s]
 96%|█████████▌| 958/1000 [00:03<00:00, 301.99it/s]
 99%|█████████▉| 989/1000 [00:03<00:00, 300.76it/s]
+[codecarbon WARNING @ 11:38:00] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:38:00] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.34119415283203125 W
+[codecarbon DEBUG @ 11:38:00] RAM : 0.34 W during 3.23 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:38:00] Energy consumed for all GPUs : 0.000152 kWh. Total GPU Power : 81.08423268913981 W
+[codecarbon DEBUG @ 11:38:00] GPU : 81.08 W during 3.23 s [measurement time: 0.0023]
+[codecarbon INFO @ 11:38:00] Energy consumed for all CPUs : 0.000079 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:38:00] CPU : 42.50 W during 3.23 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:38:00] 0.000232 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:38:00] last_duration=3.2264235879993066
+------------------------
+[codecarbon DEBUG @ 11:38:00] EmissionsData(timestamp='2024-12-06T11:38:00', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.2296128219459206, emissions=8.56345190737049e-05, emissions_rate=2.6515413393147238e-05, cpu_power=42.5, gpu_power=81.08423268913981, ram_power=0.34119415283203125, cpu_energy=7.936677239081796e-05, gpu_energy=0.00015198817714789925, ram_energy=6.324355513050914e-07, energy_consumed=0.00023198738509002228, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:38:00] EmissionsData(timestamp='2024-12-06T11:38:00', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.002107362961396575, emissions=8.56345190737049e-05, emissions_rate=0.04063586607641328, cpu_power=42.5, gpu_power=81.08423268913981, ram_power=0.34119415283203125, cpu_energy=7.936677239081796e-05, gpu_energy=0.00015198817714789925, ram_energy=6.324355513050914e-07, energy_consumed=0.00023198738509002228, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 30/1000 [00:00<00:03, 299.65it/s]
  6%|▌         | 61/1000 [00:00<00:03, 300.89it/s]
  9%|▉         | 92/1000 [00:00<00:03, 301.43it/s]
 12%|█▏        | 123/1000 [00:00<00:02, 301.48it/s]
 15%|█▌        | 154/1000 [00:00<00:02, 301.18it/s]
 18%|█▊        | 185/1000 [00:00<00:02, 301.42it/s]
 22%|██▏       | 216/1000 [00:00<00:02, 300.81it/s]
 25%|██▍       | 247/1000 [00:00<00:02, 301.23it/s]
 28%|██▊       | 278/1000 [00:00<00:02, 301.44it/s]
 31%|███       | 309/1000 [00:01<00:02, 300.91it/s]
 34%|███▍      | 340/1000 [00:01<00:02, 301.04it/s]
 37%|███▋      | 371/1000 [00:01<00:02, 300.97it/s]
 40%|████      | 402/1000 [00:01<00:01, 301.08it/s]
 43%|████▎     | 433/1000 [00:01<00:01, 300.96it/s]
 46%|████▋     | 464/1000 [00:01<00:01, 301.07it/s]
 50%|████▉     | 495/1000 [00:01<00:01, 300.87it/s]
 53%|█████▎    | 526/1000 [00:01<00:01, 301.19it/s]
 56%|█████▌    | 557/1000 [00:01<00:01, 300.68it/s]
 59%|█████▉    | 588/1000 [00:01<00:01, 300.80it/s]
 62%|██████▏   | 619/1000 [00:02<00:01, 299.93it/s]
 65%|██████▌   | 650/1000 [00:02<00:01, 300.22it/s]
 68%|██████▊   | 681/1000 [00:02<00:01, 300.75it/s]
 71%|███████   | 712/1000 [00:02<00:00, 300.95it/s]
 74%|███████▍  | 743/1000 [00:02<00:00, 300.98it/s]
 77%|███████▋  | 774/1000 [00:02<00:00, 301.15it/s]
 80%|████████  | 805/1000 [00:02<00:00, 301.30it/s]
 84%|████████▎ | 836/1000 [00:02<00:00, 301.24it/s]
 87%|████████▋ | 867/1000 [00:02<00:00, 300.83it/s]
 90%|████████▉ | 898/1000 [00:02<00:00, 300.97it/s]
 93%|█████████▎| 929/1000 [00:03<00:00, 298.19it/s]
 96%|█████████▌| 960/1000 [00:03<00:00, 299.24it/s]
 99%|█████████▉| 991/1000 [00:03<00:00, 299.77it/s]
+[codecarbon WARNING @ 11:38:04] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:38:04] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.34121274948120117 W
+[codecarbon DEBUG @ 11:38:04] RAM : 0.34 W during 3.33 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:38:04] Energy consumed for all GPUs : 0.000227 kWh. Total GPU Power : 80.71816098274648 W
+[codecarbon DEBUG @ 11:38:04] GPU : 80.72 W during 3.33 s [measurement time: 0.0033]
+[codecarbon INFO @ 11:38:04] Energy consumed for all CPUs : 0.000119 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:38:04] CPU : 42.50 W during 3.33 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:38:04] 0.000346 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:38:04] last_duration=3.328249695012346
+------------------------
+[codecarbon DEBUG @ 11:38:04] EmissionsData(timestamp='2024-12-06T11:38:04', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.332475626957603, emissions=0.00012782604599989163, emissions_rate=3.8357683688924965e-05, cpu_power=42.5, gpu_power=80.71816098274648, ram_power=0.34121274948120117, cpu_energy=0.0001187073056856914, gpu_energy=0.00022663073686146618, ram_energy=9.479000689128157e-07, energy_consumed=0.00034628594261607037, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:38:04] EmissionsData(timestamp='2024-12-06T11:38:04', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.0020879600197076797, emissions=0.00012782604599989163, emissions_rate=0.0612205429191061, cpu_power=42.5, gpu_power=80.71816098274648, ram_power=0.34121274948120117, cpu_energy=0.0001187073056856914, gpu_energy=0.00022663073686146618, ram_energy=9.479000689128157e-07, energy_consumed=0.00034628594261607037, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 31/1000 [00:00<00:03, 300.92it/s]
  6%|▌         | 62/1000 [00:00<00:03, 301.05it/s]
  9%|▉         | 93/1000 [00:00<00:03, 301.30it/s]
 12%|█▏        | 124/1000 [00:00<00:02, 301.70it/s]
 16%|█▌        | 155/1000 [00:00<00:02, 301.46it/s]
 19%|█▊        | 186/1000 [00:00<00:02, 301.39it/s]
 22%|██▏       | 217/1000 [00:00<00:02, 300.91it/s]
 25%|██▍       | 248/1000 [00:00<00:02, 301.46it/s]
 28%|██▊       | 279/1000 [00:00<00:02, 302.22it/s]
 31%|███       | 312/1000 [00:01<00:02, 307.83it/s]
 34%|███▍      | 343/1000 [00:01<00:02, 307.77it/s]
 38%|███▊      | 375/1000 [00:01<00:02, 308.92it/s]
 41%|████      | 407/1000 [00:01<00:01, 311.25it/s]
 44%|████▍     | 439/1000 [00:01<00:01, 313.59it/s]
 47%|████▋     | 471/1000 [00:01<00:01, 308.26it/s]
 50%|█████     | 502/1000 [00:01<00:01, 307.50it/s]
 53%|█████▎    | 533/1000 [00:01<00:01, 306.51it/s]
 56%|█████▋    | 564/1000 [00:01<00:01, 306.36it/s]
 60%|█████▉    | 595/1000 [00:01<00:01, 306.37it/s]
 63%|██████▎   | 627/1000 [00:02<00:01, 308.76it/s]
 66%|██████▌   | 659/1000 [00:02<00:01, 309.80it/s]
 69%|██████▉   | 690/1000 [00:02<00:01, 308.39it/s]
 72%|███████▏  | 721/1000 [00:02<00:00, 308.40it/s]
 75%|███████▌  | 754/1000 [00:02<00:00, 312.79it/s]
 79%|███████▊  | 786/1000 [00:02<00:00, 314.83it/s]
 82%|████████▏ | 818/1000 [00:02<00:00, 316.29it/s]
 85%|████████▌ | 850/1000 [00:02<00:00, 312.59it/s]
 88%|████████▊ | 882/1000 [00:02<00:00, 309.20it/s]
 91%|█████████▏| 913/1000 [00:02<00:00, 308.16it/s]
 94%|█████████▍| 944/1000 [00:03<00:00, 305.09it/s]
 98%|█████████▊| 975/1000 [00:03<00:00, 305.34it/s]
+[codecarbon WARNING @ 11:38:07] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:38:07] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.34121274948120117 W
+[codecarbon DEBUG @ 11:38:07] RAM : 0.34 W during 3.25 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:38:07] Energy consumed for all GPUs : 0.000302 kWh. Total GPU Power : 83.0039928170427 W
+[codecarbon DEBUG @ 11:38:07] GPU : 83.00 W during 3.25 s [measurement time: 0.0023]
+[codecarbon INFO @ 11:38:07] Energy consumed for all CPUs : 0.000157 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:38:07] CPU : 42.50 W during 3.26 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:38:07] 0.000460 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:38:07] last_duration=3.2541191610507667
+------------------------
+[codecarbon DEBUG @ 11:38:07] EmissionsData(timestamp='2024-12-06T11:38:07', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.2573046219768003, emissions=0.00016983668947769296, emissions_rate=5.214025373365973e-05, cpu_power=42.5, gpu_power=83.0039928170427, ram_power=0.34121274948120117, cpu_energy=0.00015716040019979119, gpu_energy=0.0003016777413424876, ram_energy=1.2563380024113124e-06, energy_consumed=0.00046009447954469007, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:38:07] EmissionsData(timestamp='2024-12-06T11:38:07', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.0020206179469823837, emissions=0.00016983668947769296, emissions_rate=0.08405185637954429, cpu_power=42.5, gpu_power=83.0039928170427, ram_power=0.34121274948120117, cpu_energy=0.00015716040019979119, gpu_energy=0.0003016777413424876, ram_energy=1.2563380024113124e-06, energy_consumed=0.00046009447954469007, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 32/1000 [00:00<00:03, 310.56it/s]
  6%|▋         | 64/1000 [00:00<00:02, 312.28it/s]
 10%|▉         | 97/1000 [00:00<00:02, 315.90it/s]
 13%|█▎        | 129/1000 [00:00<00:02, 313.15it/s]
 16%|█▌        | 161/1000 [00:00<00:02, 314.73it/s]
 19%|█▉        | 193/1000 [00:00<00:02, 313.98it/s]
 22%|██▎       | 225/1000 [00:00<00:02, 315.61it/s]
 26%|██▌       | 257/1000 [00:00<00:02, 316.63it/s]
 29%|██▉       | 289/1000 [00:00<00:02, 314.63it/s]
 32%|███▏      | 321/1000 [00:01<00:02, 315.27it/s]
 35%|███▌      | 353/1000 [00:01<00:02, 313.30it/s]
 38%|███▊      | 385/1000 [00:01<00:01, 313.75it/s]
 42%|████▏     | 417/1000 [00:01<00:01, 315.47it/s]
 45%|████▌     | 450/1000 [00:01<00:01, 317.02it/s]
 48%|████▊     | 483/1000 [00:01<00:01, 318.10it/s]
 52%|█████▏    | 515/1000 [00:01<00:01, 315.25it/s]
 55%|█████▍    | 547/1000 [00:01<00:01, 313.24it/s]
 58%|█████▊    | 579/1000 [00:01<00:01, 311.85it/s]
 61%|██████    | 611/1000 [00:01<00:01, 312.11it/s]
 64%|██████▍   | 643/1000 [00:02<00:01, 312.39it/s]
 68%|██████▊   | 675/1000 [00:02<00:01, 311.98it/s]
 71%|███████   | 708/1000 [00:02<00:00, 314.76it/s]
 74%|███████▍  | 741/1000 [00:02<00:00, 317.65it/s]
 77%|███████▋  | 774/1000 [00:02<00:00, 319.52it/s]
 81%|████████  | 807/1000 [00:02<00:00, 320.22it/s]
 84%|████████▍ | 840/1000 [00:02<00:00, 321.30it/s]
 87%|████████▋ | 873/1000 [00:02<00:00, 321.69it/s]
 91%|█████████ | 906/1000 [00:02<00:00, 321.62it/s]
 94%|█████████▍| 939/1000 [00:02<00:00, 320.89it/s]
 97%|█████████▋| 972/1000 [00:03<00:00, 318.08it/s]
+[codecarbon WARNING @ 11:38:10] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:38:10] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.3412141799926758 W
+[codecarbon DEBUG @ 11:38:10] RAM : 0.34 W during 3.17 s [measurement time: 0.0005]
+[codecarbon INFO @ 11:38:10] Energy consumed for all GPUs : 0.000375 kWh. Total GPU Power : 83.19250468085731 W
+[codecarbon DEBUG @ 11:38:10] GPU : 83.19 W during 3.17 s [measurement time: 0.0052]
+[codecarbon INFO @ 11:38:10] Energy consumed for all CPUs : 0.000195 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:38:10] CPU : 42.50 W during 3.17 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:38:10] 0.000571 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:38:10] last_duration=3.1665348659735173
+------------------------
+[codecarbon DEBUG @ 11:38:10] EmissionsData(timestamp='2024-12-06T11:38:10', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.1727622859179974, emissions=0.0002107923387421928, emissions_rate=6.643811283239671e-05, cpu_power=42.5, gpu_power=83.19250468085731, ram_power=0.3412141799926758, cpu_energy=0.00019461543987191464, gpu_energy=0.0003748730776766962, ram_energy=1.5564768154339065e-06, energy_consumed=0.0005710449943640448, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:38:10] EmissionsData(timestamp='2024-12-06T11:38:10', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.002038248931057751, emissions=0.0002107923387421928, emissions_rate=0.10341834872583593, cpu_power=42.5, gpu_power=83.19250468085731, ram_power=0.3412141799926758, cpu_energy=0.00019461543987191464, gpu_energy=0.0003748730776766962, ram_energy=1.5564768154339065e-06, energy_consumed=0.0005710449943640448, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 33/1000 [00:00<00:03, 322.23it/s]
  7%|▋         | 66/1000 [00:00<00:02, 323.08it/s]
 10%|▉         | 99/1000 [00:00<00:02, 323.18it/s]
 13%|█▎        | 132/1000 [00:00<00:02, 322.58it/s]
 16%|█▋        | 165/1000 [00:00<00:02, 321.36it/s]
 20%|��▉        | 198/1000 [00:00<00:02, 322.22it/s]
 23%|██▎       | 231/1000 [00:00<00:02, 321.27it/s]
 26%|██▋       | 264/1000 [00:00<00:02, 321.12it/s]
 30%|██▉       | 297/1000 [00:00<00:02, 321.83it/s]
 33%|███▎      | 330/1000 [00:01<00:02, 322.17it/s]
 36%|███▋      | 363/1000 [00:01<00:01, 322.68it/s]
 40%|███▉      | 396/1000 [00:01<00:01, 322.60it/s]
 43%|████▎     | 429/1000 [00:01<00:01, 322.27it/s]
 46%|████▌     | 462/1000 [00:01<00:01, 318.68it/s]
 49%|████▉     | 494/1000 [00:01<00:01, 316.95it/s]
 53%|█████▎    | 526/1000 [00:01<00:01, 314.89it/s]
 56%|█████▌    | 558/1000 [00:01<00:01, 314.08it/s]
 59%|█████▉    | 590/1000 [00:01<00:01, 313.05it/s]
 62%|██████▏   | 622/1000 [00:01<00:01, 312.73it/s]
 65%|██████▌   | 654/1000 [00:02<00:01, 312.57it/s]
 69%|██████▊   | 686/1000 [00:02<00:01, 312.58it/s]
 72%|███████▏  | 718/1000 [00:02<00:00, 312.21it/s]
 75%|███████▌  | 751/1000 [00:02<00:00, 315.20it/s]
 78%|███████▊  | 784/1000 [00:02<00:00, 317.37it/s]
 82%|████████▏ | 817/1000 [00:02<00:00, 319.12it/s]
 85%|████████▌ | 850/1000 [00:02<00:00, 320.60it/s]
 88%|████████▊ | 883/1000 [00:02<00:00, 321.67it/s]
 92%|█████████▏| 916/1000 [00:02<00:00, 322.21it/s]
 95%|█████████▍| 949/1000 [00:02<00:00, 322.53it/s]
 98%|█████████▊| 982/1000 [00:03<00:00, 319.94it/s]
+[codecarbon WARNING @ 11:38:13] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:38:13] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.3412141799926758 W
+[codecarbon DEBUG @ 11:38:13] RAM : 0.34 W during 3.14 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:38:13] Energy consumed for all GPUs : 0.000446 kWh. Total GPU Power : 81.42635799357137 W
+[codecarbon DEBUG @ 11:38:13] GPU : 81.43 W during 3.14 s [measurement time: 0.0022]
+[codecarbon INFO @ 11:38:13] Energy consumed for all CPUs : 0.000232 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:38:13] CPU : 42.50 W during 3.14 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:38:13] 0.000679 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:38:13] last_duration=3.1388846959453076
+------------------------
+[codecarbon DEBUG @ 11:38:13] EmissionsData(timestamp='2024-12-06T11:38:13', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.142057367018424, emissions=0.0002508081873684099, emissions_rate=7.982291793940351e-05, cpu_power=42.5, gpu_power=81.42635799357137, ram_power=0.3412141799926758, cpu_energy=0.00023170797734096092, gpu_energy=0.0004458875789339345, ram_energy=1.8539948656557495e-06, energy_consumed=0.0006794495511405512, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:38:13] EmissionsData(timestamp='2024-12-06T11:38:13', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.0020229590591043234, emissions=0.0002508081873684099, emissions_rate=0.12398085183170075, cpu_power=42.5, gpu_power=81.42635799357137, ram_power=0.3412141799926758, cpu_energy=0.00023170797734096092, gpu_energy=0.0004458875789339345, ram_energy=1.8539948656557495e-06, energy_consumed=0.0006794495511405512, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 31/1000 [00:00<00:03, 307.72it/s]
  6%|▌         | 62/1000 [00:00<00:03, 306.33it/s]
  9%|▉         | 93/1000 [00:00<00:02, 307.36it/s]
 13%|█▎        | 126/1000 [00:00<00:02, 313.14it/s]
 16%|█▌        | 158/1000 [00:00<00:02, 314.38it/s]
 19%|█▉        | 191/1000 [00:00<00:02, 316.47it/s]
 22%|██▏       | 224/1000 [00:00<00:02, 318.30it/s]
 26%|██▌       | 257/1000 [00:00<00:02, 320.32it/s]
 29%|██▉       | 290/1000 [00:00<00:02, 321.78it/s]
 32%|███▏      | 323/1000 [00:01<00:02, 321.53it/s]
 36%|███▌      | 356/1000 [00:01<00:02, 321.19it/s]
 39%|███▉      | 389/1000 [00:01<00:01, 321.11it/s]
 42%|████▏     | 422/1000 [00:01<00:01, 321.48it/s]
 46%|████▌     | 455/1000 [00:01<00:01, 320.89it/s]
 49%|████▉     | 488/1000 [00:01<00:01, 317.74it/s]
 52%|█████▏    | 520/1000 [00:01<00:01, 316.42it/s]
 55%|█████▌    | 553/1000 [00:01<00:01, 318.97it/s]
 58%|█████▊    | 585/1000 [00:01<00:01, 317.81it/s]
 62%|██████▏   | 617/1000 [00:01<00:01, 314.22it/s]
 65%|██████▍   | 649/1000 [00:02<00:01, 311.58it/s]
 68%|██████▊   | 681/1000 [00:02<00:01, 307.91it/s]
 71%|███████   | 712/1000 [00:02<00:00, 307.36it/s]
 74%|███████▍  | 744/1000 [00:02<00:00, 308.83it/s]
 78%|███████▊  | 776/1000 [00:02<00:00, 309.51it/s]
 81%|████████  | 807/1000 [00:02<00:00, 308.06it/s]
 84%|████████▍ | 838/1000 [00:02<00:00, 307.04it/s]
 87%|████████▋ | 869/1000 [00:02<00:00, 306.94it/s]
 90%|█████████ | 900/1000 [00:02<00:00, 306.72it/s]
 93%|█████████▎| 931/1000 [00:02<00:00, 306.60it/s]
 96%|█████████▌| 962/1000 [00:03<00:00, 306.68it/s]
 99%|█████████▉| 993/1000 [00:03<00:00, 305.49it/s]
+[codecarbon WARNING @ 11:38:17] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:38:17] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.3412156105041504 W
+[codecarbon DEBUG @ 11:38:17] RAM : 0.34 W during 3.20 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:38:17] Energy consumed for all GPUs : 0.000519 kWh. Total GPU Power : 82.37376232926216 W
+[codecarbon DEBUG @ 11:38:17] GPU : 82.37 W during 3.20 s [measurement time: 0.0023]
+[codecarbon INFO @ 11:38:17] Energy consumed for all CPUs : 0.000270 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:38:17] CPU : 42.50 W during 3.20 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:38:17] 0.000791 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:38:17] EmissionsData(timestamp='2024-12-06T11:38:17', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.2032426630612463, emissions=0.00029191452505318387, emissions_rate=9.113094315939511e-05, cpu_power=42.5, gpu_power=82.37376232926216, ram_power=0.3412156105041504, cpu_energy=0.00026952306351959125, gpu_energy=0.0005191279153038408, ram_energy=2.1573081781853167e-06, energy_consumed=0.0007908082870016175, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon INFO @ 11:38:17] 0.012841 g.CO2eq/s mean an estimation of 404.9486086838621 kg.CO2eq/year
+[codecarbon DEBUG @ 11:38:17] last_duration=3.200012721004896
+------------------------
+[codecarbon DEBUG @ 11:38:17] EmissionsData(timestamp='2024-12-06T11:38:17', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.203582538990304, emissions=0.00029191452505318387, emissions_rate=9.11212748541165e-05, cpu_power=42.5, gpu_power=82.37376232926216, ram_power=0.3412156105041504, cpu_energy=0.00026952306351959125, gpu_energy=0.0005191279153038408, ram_energy=2.1573081781853167e-06, energy_consumed=0.0007908082870016175, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:38:17] EmissionsData(timestamp='2024-12-06T11:38:17', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.0020449289586395025, emissions=0.00029191452505318387, emissions_rate=0.14275044803874043, cpu_power=42.5, gpu_power=82.37376232926216, ram_power=0.3412156105041504, cpu_energy=0.00026952306351959125, gpu_energy=0.0005191279153038408, ram_energy=2.1573081781853167e-06, energy_consumed=0.0007908082870016175, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 30/1000 [00:00<00:03, 299.08it/s]
  6%|▌         | 61/1000 [00:00<00:03, 302.45it/s]
  9%|▉         | 92/1000 [00:00<00:02, 302.73it/s]
 12%|█▏        | 123/1000 [00:00<00:02, 303.67it/s]
 15%|█▌        | 154/1000 [00:00<00:02, 304.46it/s]
 18%|█▊        | 185/1000 [00:00<00:02, 305.08it/s]
 22%|██▏       | 216/1000 [00:00<00:02, 305.64it/s]
 25%|██▍       | 247/1000 [00:00<00:02, 305.70it/s]
 28%|██▊       | 278/1000 [00:00<00:02, 303.91it/s]
 31%|███       | 309/1000 [00:01<00:02, 302.53it/s]
 34%|███▍      | 340/1000 [00:01<00:02, 302.72it/s]
 37%|███▋      | 371/1000 [00:01<00:02, 303.11it/s]
 40%|████      | 402/1000 [00:01<00:01, 303.88it/s]
 43%|████▎     | 433/1000 [00:01<00:01, 304.38it/s]
 46%|████▋     | 464/1000 [00:01<00:01, 305.03it/s]
 50%|████▉     | 495/1000 [00:01<00:01, 305.47it/s]
 53%|█████▎    | 526/1000 [00:01<00:01, 305.68it/s]
 56%|█████▌    | 557/1000 [00:01<00:01, 305.96it/s]
 59%|█████▉    | 588/1000 [00:01<00:01, 305.52it/s]
 62%|██████▏   | 619/1000 [00:02<00:01, 305.70it/s]
 65%|██████▌   | 650/1000 [00:02<00:01, 305.43it/s]
 68%|██████▊   | 681/1000 [00:02<00:01, 305.44it/s]
 71%|███████   | 712/1000 [00:02<00:00, 305.53it/s]
 74%|███████▍  | 743/1000 [00:02<00:00, 305.53it/s]
 77%|███████▋  | 774/1000 [00:02<00:00, 305.86it/s]
 80%|████████  | 805/1000 [00:02<00:00, 305.29it/s]
 84%|████████▎ | 836/1000 [00:02<00:00, 305.43it/s]
 87%|████████▋ | 867/1000 [00:02<00:00, 305.71it/s]
 90%|████████▉ | 898/1000 [00:02<00:00, 303.84it/s]
 93%|█████████▎| 929/1000 [00:03<00:00, 304.10it/s]
 96%|█████████▌| 960/1000 [00:03<00:00, 304.82it/s]
 99%|█████████▉| 991/1000 [00:03<00:00, 306.10it/s]
+[codecarbon WARNING @ 11:38:20] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:38:20] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.3412156105041504 W
+[codecarbon DEBUG @ 11:38:20] RAM : 0.34 W during 3.28 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:38:20] Energy consumed for all GPUs : 0.000594 kWh. Total GPU Power : 82.48475796224648 W
+[codecarbon DEBUG @ 11:38:20] GPU : 82.48 W during 3.28 s [measurement time: 0.0044]
+[codecarbon INFO @ 11:38:20] Energy consumed for all CPUs : 0.000308 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:38:20] CPU : 42.50 W during 3.29 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:38:20] 0.000905 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:38:20] last_duration=3.2831034610280767
+------------------------
+[codecarbon DEBUG @ 11:38:20] EmissionsData(timestamp='2024-12-06T11:38:20', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.2884545139968395, emissions=0.00033413391755233464, emissions_rate=0.00010160819197289824, cpu_power=42.5, gpu_power=82.48475796224648, ram_power=0.3412156105041504, cpu_energy=0.0003083439170501758, gpu_energy=0.0005943699199413288, ram_energy=2.468496503412548e-06, energy_consumed=0.0009051823334949173, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:38:20] EmissionsData(timestamp='2024-12-06T11:38:20', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.0020385209936648607, emissions=0.00033413391755233464, emissions_rate=0.16390997129326956, cpu_power=42.5, gpu_power=82.48475796224648, ram_power=0.3412156105041504, cpu_energy=0.0003083439170501758, gpu_energy=0.0005943699199413288, ram_energy=2.468496503412548e-06, energy_consumed=0.0009051823334949173, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 31/1000 [00:00<00:03, 305.18it/s]
  6%|▌         | 62/1000 [00:00<00:03, 306.07it/s]
  9%|▉         | 93/1000 [00:00<00:02, 305.63it/s]
 12%|█▏        | 124/1000 [00:00<00:02, 305.21it/s]
 16%|█▌        | 155/1000 [00:00<00:02, 304.81it/s]
 19%|█▊        | 186/1000 [00:00<00:02, 305.42it/s]
 22%|██▏       | 217/1000 [00:00<00:02, 305.58it/s]
 25%|██▍       | 248/1000 [00:00<00:02, 305.68it/s]
 28%|��█▊       | 279/1000 [00:00<00:02, 306.38it/s]
 31%|███       | 310/1000 [00:01<00:02, 307.48it/s]
 34%|███▍      | 341/1000 [00:01<00:02, 307.16it/s]
 37%|███▋      | 372/1000 [00:01<00:02, 306.54it/s]
 40%|████      | 403/1000 [00:01<00:01, 306.30it/s]
 43%|████▎     | 434/1000 [00:01<00:01, 306.09it/s]
 46%|████▋     | 465/1000 [00:01<00:01, 306.21it/s]
 50%|████▉     | 497/1000 [00:01<00:01, 309.01it/s]
 53%|█████▎    | 529/1000 [00:01<00:01, 312.15it/s]
 56%|█████▌    | 562/1000 [00:01<00:01, 314.81it/s]
 59%|█████▉    | 594/1000 [00:01<00:01, 315.62it/s]
 63%|██████▎   | 627/1000 [00:02<00:01, 317.80it/s]
 66%|██████▌   | 659/1000 [00:02<00:01, 318.38it/s]
 69%|██████▉   | 691/1000 [00:02<00:00, 318.81it/s]
 72%|███████▏  | 723/1000 [00:02<00:00, 319.01it/s]
 76%|███████▌  | 756/1000 [00:02<00:00, 319.47it/s]
 79%|███████▉  | 788/1000 [00:02<00:00, 319.53it/s]
 82%|████████▏ | 820/1000 [00:02<00:00, 319.24it/s]
 85%|████████▌ | 853/1000 [00:02<00:00, 319.37it/s]
 88%|████████▊ | 885/1000 [00:02<00:00, 315.40it/s]
 92%|█████████▏| 917/1000 [00:02<00:00, 312.55it/s]
 95%|█████████▍| 949/1000 [00:03<00:00, 311.80it/s]
 98%|█████████▊| 981/1000 [00:03<00:00, 310.17it/s]
+[codecarbon WARNING @ 11:38:23] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:38:23] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.3412156105041504 W
+[codecarbon DEBUG @ 11:38:23] RAM : 0.34 W during 3.22 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:38:23] Energy consumed for all GPUs : 0.000668 kWh. Total GPU Power : 82.03731960224725 W
+[codecarbon DEBUG @ 11:38:23] GPU : 82.04 W during 3.22 s [measurement time: 0.0023]
+[codecarbon INFO @ 11:38:23] Energy consumed for all CPUs : 0.000346 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:38:23] CPU : 42.50 W during 3.22 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:38:23] 0.001017 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:38:23] last_duration=3.2149330319371074
+------------------------
+[codecarbon DEBUG @ 11:38:23] EmissionsData(timestamp='2024-12-06T11:38:23', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.218181503005326, emissions=0.0003753204594399024, emissions_rate=0.00011662501294268401, cpu_power=42.5, gpu_power=82.03731960224725, ram_power=0.3412156105041504, cpu_energy=0.0003463351439935246, gpu_energy=0.0006676499785651657, ram_energy=2.773223235353656e-06, energy_consumed=0.0010167583457940442, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 11:38:23] EmissionsData(timestamp='2024-12-06T11:38:23', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=0.0020393700106069446, emissions=0.0003753204594399024, emissions_rate=0.1840374515109212, cpu_power=42.5, gpu_power=82.03731960224725, ram_power=0.3412156105041504, cpu_energy=0.0003463351439935246, gpu_energy=0.0006676499785651657, ram_energy=2.773223235353656e-06, energy_consumed=0.0010167583457940442, 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)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
  3%|▎         | 32/1000 [00:00<00:03, 318.65it/s]
  6%|▋         | 64/1000 [00:00<00:02, 319.05it/s]
 10%|▉         | 96/1000 [00:00<00:02, 319.24it/s]
 13%|█▎        | 128/1000 [00:00<00:02, 313.64it/s]
 16%|█▌        | 160/1000 [00:00<00:02, 310.27it/s]
 19%|█▉        | 192/1000 [00:00<00:02, 308.87it/s]
 22%|██▏       | 223/1000 [00:00<00:02, 308.24it/s]
 26%|██▌       | 255/1000 [00:00<00:02, 309.69it/s]
 29%|██▊       | 287/1000 [00:00<00:02, 310.49it/s]
 32%|███▏      | 320/1000 [00:01<00:02, 314.40it/s]
 35%|███▌      | 353/1000 [00:01<00:02, 316.40it/s]
 39%|███▊      | 386/1000 [00:01<00:01, 317.53it/s]
 42%|████▏     | 418/1000 [00:01<00:01, 318.05it/s]
 45%|████▌     | 450/1000 [00:01<00:01, 314.63it/s]
 48%|████▊     | 482/1000 [00:01<00:01, 311.78it/s]
 51%|█████▏    | 514/1000 [00:01<00:01, 310.12it/s]
 55%|█████▍    | 546/1000 [00:01<00:01, 309.03it/s]
 58%|█████▊    | 577/1000 [00:01<00:01, 308.93it/s]
 61%|██████    | 608/1000 [00:01<00:01, 308.00it/s]
 64%|██████▍   | 639/1000 [00:02<00:01, 307.47it/s]
 67%|██████▋   | 670/1000 [00:02<00:01, 307.10it/s]
 70%|███████   | 701/1000 [00:02<00:00, 306.96it/s]
 73%|███████▎  | 732/1000 [00:02<00:00, 306.84it/s]
 76%|███████▋  | 763/1000 [00:02<00:00, 306.35it/s]
 79%|███████▉  | 794/1000 [00:02<00:00, 306.48it/s]
 83%|████████▎ | 826/1000 [00:02<00:00, 310.22it/s]
 86%|████████▌ | 858/1000 [00:02<00:00, 309.67it/s]
 89%|████████▉ | 889/1000 [00:02<00:00, 308.19it/s]
 92%|█████████▏| 920/1000 [00:02<00:00, 307.32it/s]
 95%|█████████▌| 951/1000 [00:03<00:00, 307.28it/s]
 98%|█████████▊| 982/1000 [00:03<00:00, 307.05it/s]
+[codecarbon WARNING @ 11:38:26] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 11:38:26] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.3412184715270996 W
+[codecarbon DEBUG @ 11:38:26] RAM : 0.34 W during 3.23 s [measurement time: 0.0004]
+[codecarbon INFO @ 11:38:26] Energy consumed for all GPUs : 0.000743 kWh. Total GPU Power : 84.2840975439887 W
+[codecarbon DEBUG @ 11:38:26] GPU : 84.28 W during 3.23 s [measurement time: 0.0025]
+[codecarbon INFO @ 11:38:26] Energy consumed for all CPUs : 0.000384 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 11:38:26] CPU : 42.50 W during 3.23 s [measurement time: 0.0000]
+[codecarbon INFO @ 11:38:26] 0.001131 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 11:38:26] last_duration=3.227075955015607
+------------------------
+[codecarbon DEBUG @ 11:38:26] EmissionsData(timestamp='2024-12-06T11:38:26', project_name='codecarbon', run_id='34ced19d-5612-4cb0-b87b-e0575cf3253d', duration=3.2304750490002334, emissions=0.0004174066316394302, emissions_rate=0.00012920905603917574, cpu_power=42.5, gpu_power=84.2840975439887, ram_power=0.3412184715270996, cpu_energy=0.0003844715173744286, gpu_energy=0.0007432208723550104, ram_energy=3.079103363458876e-06, energy_consumed=0.0011307714930928984, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)

sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "sentence_similarity_udever-bloom-7b1",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "sentence-similarity",
+        "model": "sentence-transformers/paraphrase-MiniLM-L6-v2",
+        "processor": "sentence-transformers/paraphrase-MiniLM-L6-v2",
+        "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/sentence_similarity",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}

sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-06T11:38:26",
+    "project_name": "codecarbon",
+    "run_id": "34ced19d-5612-4cb0-b87b-e0575cf3253d",
+    "duration": -1732784632.0731199,
+    "emissions": 4.208617219952779e-05,
+    "emissions_rate": 1.3036088181474662e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 84.2840975439887,
+    "ram_power": 0.3412184715270996,
+    "cpu_energy": 3.8136373380904024e-05,
+    "gpu_energy": 7.557089378984472e-05,
+    "ram_energy": 3.0588012810522036e-07,
+    "energy_consumed": 0.00011401314729885415,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

sentence_similarity/sentence-transformers/paraphrase-MiniLM-L6-v2/2024-12-06-11-37-40/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-06T11:37:53",
+    "project_name": "codecarbon",
+    "run_id": "34ced19d-5612-4cb0-b87b-e0575cf3253d",
+    "duration": -1732784635.1371212,
+    "emissions": 2.1301847465912246e-06,
+    "emissions_rate": 1.2947676218352943e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 83.59350259699416,
+    "ram_power": 0.26796913146972656,
+    "cpu_energy": 1.9664361006612634e-06,
+    "gpu_energy": 3.7922252573707738e-06,
+    "ram_energy": 1.2095510410428298e-08,
+    "energy_consumed": 5.770756868442466e-06,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

text_generation/facebook/opt-125m/2024-12-06-11-38-28/.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-125m
+  processor: facebook/opt-125m
+  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-125m/2024-12-06-11-38-28/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/text_generation/facebook/opt-125m/2024-12-06-11-38-28
+  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-125m/2024-12-06-11-38-28
+    - hydra.mode=RUN
+    task:
+    - backend.model=facebook/opt-125m
+    - backend.processor=facebook/opt-125m
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=facebook/opt-125m,backend.processor=facebook/opt-125m
+    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-125m/2024-12-06-11-38-28
+    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-125m/2024-12-06-11-38-28/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=facebook/opt-125m
+- backend.processor=facebook/opt-125m

text_generation/facebook/opt-125m/2024-12-06-11-38-28/benchmark_report.json

@@ -0,0 +1,203 @@
+{
+    "prefill": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.00015961811663645173,
+            "ram": 1.4629956913679388e-06,
+            "gpu": 0.0008433003413063744,
+            "total": 0.001004381453634194
+        },
+        "efficiency": {
+            "unit": "tokens/kWh",
+            "value": 299525642.2860714
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.00017775775790012432,
+                "ram": 1.628736405520292e-06,
+                "gpu": 0.0009053257242594981,
+                "total": 0.0010847122185651426
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00017750304687619474,
+                "ram": 1.6267816700028285e-06,
+                "gpu": 0.0009313315783980869,
+                "total": 0.0011104614069442843
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00017748282437177198,
+                "ram": 1.6267703432671715e-06,
+                "gpu": 0.0009362540823367738,
+                "total": 0.001115363677051813
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00017734234650213497,
+                "ram": 1.6257317069958753e-06,
+                "gpu": 0.0009438043661536,
+                "total": 0.00112277244436273
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0001778692368289436,
+                "ram": 1.630127784029496e-06,
+                "gpu": 0.0009538204852788112,
+                "total": 0.0011333198498917844
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0001777150071745079,
+                "ram": 1.6287870340222759e-06,
+                "gpu": 0.0009490429814551504,
+                "total": 0.0011283867756636803
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.000176967954050148,
+                "ram": 1.622320821020758e-06,
+                "gpu": 0.0009375529722639442,
+                "total": 0.0011161432471351127
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00017695565216628096,
+                "ram": 1.6218754447515748e-06,
+                "gpu": 0.000938151583854463,
+                "total": 0.0011167291114654952
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00017658734049441085,
+                "ram": 1.618825704069116e-06,
+                "gpu": 0.0009377196390634168,
+                "total": 0.0011159258052618973
+            }
+        ]
+    },
+    "decode": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.0006670421107859714,
+            "ram": 6.123682284506015e-06,
+            "gpu": 0.001455102414081111,
+            "total": 0.002128268207151589
+        },
+        "efficiency": {
+            "unit": "tokens/kWh",
+            "value": 4228790.323398823
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.0007370514876859993,
+                "ram": 6.7653575920105514e-06,
+                "gpu": 0.0017596466854943316,
+                "total": 0.002503463530772341
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0007383834340736537,
+                "ram": 6.778989960165064e-06,
+                "gpu": 0.0016500699311663425,
+                "total": 0.0023952323552001577
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0007373868646430008,
+                "ram": 6.769671475726232e-06,
+                "gpu": 0.0015689462551549127,
+                "total": 0.00231310279127364
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0007397144937226483,
+                "ram": 6.790784718125929e-06,
+                "gpu": 0.001561138471133816,
+                "total": 0.002307643749574593
+            },
+            {
+                "unit": "kWh",
+                "cpu": -0.0001778692368289436,
+                "ram": -1.630127784029496e-06,
+                "gpu": -0.0009538204852788112,
+                "total": -0.0011333198498917844
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0007436416582792137,
+                "ram": 6.8266961433826635e-06,
+                "gpu": 0.0016269043570780184,
+                "total": 0.0023773727115006154
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0009206054350879445,
+                "ram": 8.449086892235852e-06,
+                "gpu": 0.0025127681213241715,
+                "total": 0.0034418226433043514
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0007393844037542289,
+                "ram": 6.787822469942927e-06,
+                "gpu": 0.001570666812089172,
+                "total": 0.002316839038313345
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0007543674005729881,
+                "ram": 6.925673557496776e-06,
+                "gpu": 0.0016240760214820682,
+                "total": 0.002385369095612556
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0007377551668689803,
+                "ram": 6.772867820003657e-06,
+                "gpu": 0.0016306279711670868,
+                "total": 0.002375156005856074
+            }
+        ]
+    },
+    "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": 1.0703117998814884e-05,
+            "ram": 7.105618238450323e-08,
+            "gpu": 1.734556943233656e-05,
+            "total": 2.8119743613535947e-05
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 35562201.908506446
+        },
+        "measures": null
+    }
+}

text_generation/facebook/opt-125m/2024-12-06-11-38-28/cli.log

@@ -0,0 +1,188 @@
+[2024-12-06 11:38:31,287][launcher][INFO] - ََAllocating process launcher
+[2024-12-06 11:38:31,287][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-06 11:38:31,299][process][INFO] - 	+ Launched benchmark in isolated process 430.
+[PROC-0][2024-12-06 11:38:33,876][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-06 11:38:34,773][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-06 11:38:34,773][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-06 11:38:35,560][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCausalLM
+[PROC-0][2024-12-06 11:38:35,560][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-06 11:38:35,560][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-06 11:38:35,560][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-06 11:38:35,560][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-06 11:38:35,560][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-06 11:38:35,583][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-06 11:38:35,583][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-06 11:38:35,584][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-06 11:38:35,584][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-06 11:38:35,743][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-06 11:38:35,750][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-06 11:38:35,750][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-06 11:38:37,434][energy_star][INFO] - 	+ Updating Text Generation kwargs with default values
+[PROC-0][2024-12-06 11:38:37,434][energy_star][INFO] - 	+ Initializing Text Generation report
+[PROC-0][2024-12-06 11:38:37,434][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-06 11:38:41,632][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-06 11:38:42,539][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-06 11:38:42,540][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-06 11:38:42,540][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-06 11:38:42,540][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-06 11:38:43,292][energy_star][INFO] - 	+ Additional warmup for Text Generation
+[PROC-0][2024-12-06 11:38:43,366][energy_star][INFO] - 	+ Running Text Generation energy tracking for 10 iterations
+[PROC-0][2024-12-06 11:38:43,366][energy_star][INFO] - 	+ Prefill iteration 1/10
+[PROC-0][2024-12-06 11:38:58,424][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-06 11:38:58,424][energy_star][INFO] - 	+ Prefill iteration 2/10
+[PROC-0][2024-12-06 11:39:13,460][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-06 11:39:13,461][energy_star][INFO] - 	+ Prefill iteration 3/10
+[PROC-0][2024-12-06 11:39:28,495][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-06 11:39:28,496][energy_star][INFO] - 	+ Prefill iteration 4/10
+[PROC-0][2024-12-06 11:39:43,518][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-06 11:39:43,518][energy_star][INFO] - 	+ Prefill iteration 5/10
+[PROC-0][2024-12-06 11:39:58,586][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-06 11:39:58,586][energy_star][INFO] - 	+ Prefill iteration 6/10
+[PROC-0][2024-12-06 11:40:13,640][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-06 11:40:13,641][energy_star][INFO] - 	+ Prefill iteration 7/10
+[PROC-0][2024-12-06 11:40:28,665][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-06 11:40:28,666][energy_star][INFO] - 	+ Prefill iteration 8/10
+[PROC-0][2024-12-06 11:40:43,656][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-06 11:40:43,657][energy_star][INFO] - 	+ Prefill iteration 9/10
+[PROC-0][2024-12-06 11:40:58,647][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-06 11:40:58,647][energy_star][INFO] - 	+ Prefill iteration 10/10
+[PROC-0][2024-12-06 11:41:13,606][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-06 11:41:13,606][energy_star][INFO] - 	+ Decoding iteration 1/10
+[PROC-0][2024-12-06 11:42:31,096][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-06 11:42:31,097][energy_star][INFO] - 	+ Decoding iteration 2/10
+[PROC-0][2024-12-06 11:43:48,678][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-06 11:43:48,679][energy_star][INFO] - 	+ Decoding iteration 3/10
+[PROC-0][2024-12-06 11:45:06,174][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-06 11:45:06,174][energy_star][INFO] - 	+ Decoding iteration 4/10
+[PROC-0][2024-12-06 11:46:23,855][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-06 11:46:23,856][energy_star][INFO] - 	+ Decoding iteration 5/10
+[PROC-0][2024-12-06 11:47:41,227][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-06 11:47:41,228][energy_star][INFO] - 	+ Decoding iteration 6/10
+[PROC-0][2024-12-06 11:48:59,272][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-06 11:48:59,273][energy_star][INFO] - 	+ Decoding iteration 7/10
+[PROC-0][2024-12-06 11:50:17,254][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-06 11:50:17,255][energy_star][INFO] - 	+ Decoding iteration 8/10
+[PROC-0][2024-12-06 11:51:34,876][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-06 11:51:34,876][energy_star][INFO] - 	+ Decoding iteration 9/10
+[PROC-0][2024-12-06 11:52:53,765][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-06 11:52:53,766][energy_star][INFO] - 	+ Decoding iteration 10/10
+[PROC-0][2024-12-06 11:54:11,216][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-06 11:54:11,217][energy][INFO] - 		+ prefill energy consumption:
+[PROC-0][2024-12-06 11:54:11,217][energy][INFO] - 			+ CPU: 0.000160 (kWh)
+[PROC-0][2024-12-06 11:54:11,217][energy][INFO] - 			+ GPU: 0.000843 (kWh)
+[PROC-0][2024-12-06 11:54:11,217][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-06 11:54:11,217][energy][INFO] - 			+ total: 0.001004 (kWh)
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 		+ prefill_iteration_1 energy consumption:
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 			+ CPU: 0.000178 (kWh)
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 			+ GPU: 0.000905 (kWh)
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 			+ RAM: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 			+ total: 0.001085 (kWh)
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 		+ prefill_iteration_2 energy consumption:
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 			+ CPU: 0.000178 (kWh)
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 			+ GPU: 0.000931 (kWh)
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 			+ RAM: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 			+ total: 0.001110 (kWh)
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 		+ prefill_iteration_3 energy consumption:
+[PROC-0][2024-12-06 11:54:11,218][energy][INFO] - 			+ CPU: 0.000177 (kWh)
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 			+ GPU: 0.000936 (kWh)
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 			+ RAM: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 			+ total: 0.001115 (kWh)
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 		+ prefill_iteration_4 energy consumption:
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 			+ CPU: 0.000177 (kWh)
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 			+ GPU: 0.000944 (kWh)
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 			+ RAM: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 			+ total: 0.001123 (kWh)
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 		+ prefill_iteration_5 energy consumption:
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 			+ CPU: 0.000178 (kWh)
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 			+ GPU: 0.000954 (kWh)
+[PROC-0][2024-12-06 11:54:11,219][energy][INFO] - 			+ RAM: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 			+ total: 0.001133 (kWh)
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 		+ prefill_iteration_6 energy consumption:
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 			+ CPU: 0.000178 (kWh)
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 			+ GPU: 0.000949 (kWh)
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 			+ RAM: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 			+ total: 0.001128 (kWh)
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 		+ prefill_iteration_7 energy consumption:
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 		+ prefill_iteration_8 energy consumption:
+[PROC-0][2024-12-06 11:54:11,220][energy][INFO] - 			+ CPU: 0.000177 (kWh)
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 			+ GPU: 0.000938 (kWh)
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 			+ RAM: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 			+ total: 0.001116 (kWh)
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 		+ prefill_iteration_9 energy consumption:
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 			+ CPU: 0.000177 (kWh)
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 			+ GPU: 0.000938 (kWh)
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 			+ RAM: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 			+ total: 0.001117 (kWh)
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 		+ prefill_iteration_10 energy consumption:
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 			+ CPU: 0.000177 (kWh)
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 			+ GPU: 0.000938 (kWh)
+[PROC-0][2024-12-06 11:54:11,221][energy][INFO] - 			+ RAM: 0.000002 (kWh)
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 			+ total: 0.001116 (kWh)
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 		+ decode energy consumption:
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 			+ CPU: 0.000667 (kWh)
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 			+ GPU: 0.001455 (kWh)
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 			+ total: 0.002128 (kWh)
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 		+ decode_iteration_1 energy consumption:
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 			+ CPU: 0.000737 (kWh)
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 			+ GPU: 0.001760 (kWh)
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 			+ RAM: 0.000007 (kWh)
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 			+ total: 0.002503 (kWh)
+[PROC-0][2024-12-06 11:54:11,222][energy][INFO] - 		+ decode_iteration_2 energy consumption:
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 			+ CPU: 0.000738 (kWh)
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 			+ GPU: 0.001650 (kWh)
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 			+ RAM: 0.000007 (kWh)
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 			+ total: 0.002395 (kWh)
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 		+ decode_iteration_3 energy consumption:
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 			+ CPU: 0.000737 (kWh)
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 			+ GPU: 0.001569 (kWh)
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 			+ RAM: 0.000007 (kWh)
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 			+ total: 0.002313 (kWh)
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 		+ decode_iteration_4 energy consumption:
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 			+ CPU: 0.000740 (kWh)
+[PROC-0][2024-12-06 11:54:11,223][energy][INFO] - 			+ GPU: 0.001561 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 			+ RAM: 0.000007 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 			+ total: 0.002308 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 		+ decode_iteration_5 energy consumption:
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 			+ CPU: -0.000178 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 			+ GPU: -0.000954 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 			+ RAM: -0.000002 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 			+ total: -0.001133 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 		+ decode_iteration_6 energy consumption:
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 			+ CPU: 0.000744 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 			+ GPU: 0.001627 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 			+ RAM: 0.000007 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 			+ total: 0.002377 (kWh)
+[PROC-0][2024-12-06 11:54:11,224][energy][INFO] - 		+ decode_iteration_7 energy consumption:
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 			+ CPU: 0.000921 (kWh)
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 			+ GPU: 0.002513 (kWh)
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 			+ RAM: 0.000008 (kWh)
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 			+ total: 0.003442 (kWh)
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 		+ decode_iteration_8 energy consumption:
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 			+ CPU: 0.000739 (kWh)
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 			+ GPU: 0.001571 (kWh)
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 			+ RAM: 0.000007 (kWh)
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 			+ total: 0.002317 (kWh)
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 		+ decode_iteration_9 energy consumption:
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 			+ CPU: 0.000754 (kWh)
+[PROC-0][2024-12-06 11:54:11,225][energy][INFO] - 			+ GPU: 0.001624 (kWh)
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 			+ RAM: 0.000007 (kWh)
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 			+ total: 0.002385 (kWh)
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 		+ decode_iteration_10 energy consumption:
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 			+ CPU: 0.000738 (kWh)
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 			+ GPU: 0.001631 (kWh)
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 			+ RAM: 0.000007 (kWh)
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 			+ total: 0.002375 (kWh)
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 			+ CPU: 0.000011 (kWh)
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 			+ GPU: 0.000017 (kWh)
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-06 11:54:11,226][energy][INFO] - 			+ total: 0.000028 (kWh)
+[PROC-0][2024-12-06 11:54:11,227][energy][INFO] - 		+ prefill energy efficiency: 299525642.286071 (tokens/kWh)
+[PROC-0][2024-12-06 11:54:11,227][energy][INFO] - 		+ decode energy efficiency: 4228790.323399 (tokens/kWh)
+[PROC-0][2024-12-06 11:54:11,227][energy][INFO] - 		+ preprocess energy efficiency: 35562201.908506 (samples/kWh)
+[2024-12-06 11:54:11,876][datasets][INFO] - PyTorch version 2.4.0 available.

text_generation/facebook/opt-125m/2024-12-06-11-38-28/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-125m",
+        "processor": "facebook/opt-125m",
+        "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-125m/2024-12-06-11-38-28/generate_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-06T11:54:11",
+    "project_name": "codecarbon",
+    "run_id": "9cda2a10-a20d-4c49-94a2-24281becc965",
+    "duration": -1732784557.8532782,
+    "emissions": 0.0012886783125127116,
+    "emissions_rate": 1.6639211053565298e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 119.38410406581427,
+    "ram_power": 0.390073299407959,
+    "cpu_energy": 0.0009143425073633912,
+    "gpu_energy": 0.0025683476102305036,
+    "ram_energy": 8.391693524072773e-06,
+    "energy_consumed": 0.0034910818111179714,
+    "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-125m/2024-12-06-11-38-28/prefill_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-06T11:41:13",
+    "project_name": "codecarbon",
+    "run_id": "9cda2a10-a20d-4c49-94a2-24281becc965",
+    "duration": -1732784620.3468251,
+    "emissions": 0.0004119265778975735,
+    "emissions_rate": 2.7544871326692854e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 225.72072854514866,
+    "ram_power": 0.38968849182128906,
+    "cpu_energy": 0.00017658734049441085,
+    "gpu_energy": 0.0009377196390634168,
+    "ram_energy": 1.618825704069116e-06,
+    "energy_consumed": 0.0011159258052618973,
+    "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-125m/2024-12-06-11-38-28/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-06T11:38:42",
+    "project_name": "codecarbon",
+    "run_id": "9cda2a10-a20d-4c49-94a2-24281becc965",
+    "duration": -1732784634.3970468,
+    "emissions": 1.0379964065229701e-05,
+    "emissions_rate": 1.1474858923913597e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 69.05202666503745,
+    "ram_power": 0.28311967849731445,
+    "cpu_energy": 1.0703117998814884e-05,
+    "gpu_energy": 1.734556943233656e-05,
+    "ram_energy": 7.105618238450323e-08,
+    "energy_consumed": 2.8119743613535947e-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/meta-llama/Llama-3.1-8B-Instruct/2024-12-06-11-54-12/.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: meta-llama/Llama-3.1-8B-Instruct
+  processor: meta-llama/Llama-3.1-8B-Instruct
+  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/meta-llama/Llama-3.1-8B-Instruct/2024-12-06-11-54-12/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-12-06-11-54-12
+  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/meta-llama/Llama-3.1-8B-Instruct/2024-12-06-11-54-12
+    - hydra.mode=RUN
+    task:
+    - backend.model=meta-llama/Llama-3.1-8B-Instruct
+    - backend.processor=meta-llama/Llama-3.1-8B-Instruct
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=meta-llama/Llama-3.1-8B-Instruct,backend.processor=meta-llama/Llama-3.1-8B-Instruct
+    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/meta-llama/Llama-3.1-8B-Instruct/2024-12-06-11-54-12
+    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/meta-llama/Llama-3.1-8B-Instruct/2024-12-06-11-54-12/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=meta-llama/Llama-3.1-8B-Instruct
+- backend.processor=meta-llama/Llama-3.1-8B-Instruct

text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-12-06-11-54-12/cli.log

@@ -0,0 +1,17 @@
+[2024-12-06 11:54:15,706][launcher][INFO] - ََAllocating process launcher
+[2024-12-06 11:54:15,706][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-06 11:54:15,719][process][INFO] - 	+ Launched benchmark in isolated process 618.
+[PROC-0][2024-12-06 11:54:18,276][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-06 11:54:19,178][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-06 11:54:19,178][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-06 11:54:20,438][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCausalLM
+[PROC-0][2024-12-06 11:54:20,438][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-06 11:54:20,438][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-06 11:54:20,438][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-06 11:54:20,438][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-06 11:54:20,439][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-06 11:54:20,459][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-06 11:54:20,459][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-06 11:54:20,460][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-06 11:54:20,460][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[2024-12-06 11:54:21,466][experiment][ERROR] - Error during experiment

text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-12-06-11-54-12/error.log

@@ -0,0 +1,50 @@
+Error executing job with overrides: ['backend.model=meta-llama/Llama-3.1-8B-Instruct', 'backend.processor=meta-llama/Llama-3.1-8B-Instruct']
+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 81, in __init__
+    self.load_model_with_no_weights()
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 246, in load_model_with_no_weights
+    self.load_model_from_pretrained()
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 204, in load_model_from_pretrained
+    self.pretrained_model = self.automodel_class.from_pretrained(
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/auto/auto_factory.py", line 564, in from_pretrained
+    return model_class.from_pretrained(
+  File "/opt/conda/lib/python3.9/site-packages/transformers/modeling_utils.py", line 3810, in from_pretrained
+    model = cls(config, *model_args, **model_kwargs)
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 1116, in __init__
+    self.model = LlamaModel(config)
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 902, in __init__
+    [LlamaDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 902, in <listcomp>
+    [LlamaDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 691, in __init__
+    self.mlp = LlamaMLP(config)
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 287, in __init__
+    self.up_proj = nn.Linear(self.hidden_size, self.intermediate_size, bias=config.mlp_bias)
+  File "/opt/conda/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 99, in __init__
+    self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
+  File "/opt/conda/lib/python3.9/site-packages/torch/utils/_device.py", line 79, in __torch_function__
+    return func(*args, **kwargs)
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 224.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 69.50 MiB is free. Process 600116 has 22.12 GiB memory in use. Of the allocated memory 21.83 GiB is allocated by PyTorch, and 1.24 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
+
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-12-06-11-54-12/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": "meta-llama/Llama-3.1-8B-Instruct",
+        "processor": "meta-llama/Llama-3.1-8B-Instruct",
+        "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
+    }
+}