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image_classification/microsoft/resnet-50/2024-12-03-18-37-27/.hydra/config.yaml

@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: image-classification
+  model: microsoft/resnet-50
+  processor: microsoft/resnet-50
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/image_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: image_classification
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null

image_classification/microsoft/resnet-50/2024-12-03-18-37-27/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/image_classification/microsoft/resnet-50/2024-12-03-18-37-27
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/image_classification/microsoft/resnet-50/2024-12-03-18-37-27
+    - hydra.mode=RUN
+    task:
+    - backend.model=microsoft/resnet-50
+    - backend.processor=microsoft/resnet-50
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=microsoft/resnet-50,backend.processor=microsoft/resnet-50
+    id: ???
+    num: ???
+    config_name: image_classification
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/image_classification/microsoft/resnet-50/2024-12-03-18-37-27
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

image_classification/microsoft/resnet-50/2024-12-03-18-37-27/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=microsoft/resnet-50
+- backend.processor=microsoft/resnet-50

image_classification/microsoft/resnet-50/2024-12-03-18-37-27/benchmark_report.json

@@ -0,0 +1,107 @@
+{
+    "forward": {
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+        "latency": null,
+        "throughput": null,
+        "energy": {
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+            "gpu": 0.0005152875511178934,
+            "total": 0.0008126568714628173
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 1230531.6488617847
+        },
+        "measures": [
+            {
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+                "cpu": 0.00032766355427754916,
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+                "total": 0.0008984765243139482
+            },
+            {
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+                "cpu": 0.00033398171673874866,
+                "ram": 4.668879524099394e-06,
+                "gpu": 0.0005835515779537559,
+                "total": 0.0009222021742166043
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+            {
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+                "ram": 4.5424303870416166e-06,
+                "gpu": 0.0005685418437195722,
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+            {
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+                "gpu": 0.0005671440648242765,
+                "total": 0.0008942894036110603
+            },
+            {
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+                "ram": 4.587466357088687e-06,
+                "gpu": 0.0005724782357603431,
+                "total": 0.0009051889725689502
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
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+            {
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+                "cpu": 0.00032681702031970607,
+                "ram": 4.569198582007998e-06,
+                "gpu": 0.000573035458426574,
+                "total": 0.0009044216773282879
+            },
+            {
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+                "cpu": 0.0003248493934032417,
+                "ram": 4.541682951047131e-06,
+                "gpu": 0.0005708376788930991,
+                "total": 0.0009002287552473875
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003201444721040187,
+                "ram": 4.475387356327922e-06,
+                "gpu": 0.0005623048942844378,
+                "total": 0.0008869247537447843
+            }
+        ]
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 9.686615021411045e-05,
+            "ram": 7.841612635117118e-07,
+            "gpu": 0.00016168374046188205,
+            "total": 0.00025933405193950425
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 3856030.446141618
+        },
+        "measures": null
+    }
+}

image_classification/microsoft/resnet-50/2024-12-03-18-37-27/cli.log

@@ -0,0 +1,113 @@
+[2024-12-03 18:37:30,170][launcher][INFO] - ََAllocating process launcher
+[2024-12-03 18:37:30,170][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-03 18:37:30,183][device-isolation][INFO] - 	+ Launched device(s) isolation process 885
+[2024-12-03 18:37:30,183][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-03 18:37:30,190][process][INFO] - 	+ Launched benchmark in isolated process 886.
+[PROC-0][2024-12-03 18:37:32,762][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-03 18:37:33,678][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-03 18:37:33,678][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-03 18:37:34,208][pytorch][INFO] - 	+ Using AutoModel class AutoModelForImageClassification
+[PROC-0][2024-12-03 18:37:34,208][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-03 18:37:34,208][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-03 18:37:34,209][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-03 18:37:34,209][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-03 18:37:34,209][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-03 18:37:34,211][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-03 18:37:34,211][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-03 18:37:34,215][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-03 18:37:34,215][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-03 18:37:34,393][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-03 18:37:34,399][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-03 18:37:34,399][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-03 18:37:36,674][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-03 18:37:36,674][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-03 18:37:40,864][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-03 18:37:49,070][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-03 18:37:49,071][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-03 18:37:49,071][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-03 18:37:49,071][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-03 18:37:49,485][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-03 18:37:49,485][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-03 18:38:17,241][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 18:38:17,241][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-03 18:38:44,651][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 18:38:44,651][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-03 18:39:12,942][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 18:39:12,943][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-03 18:39:40,465][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 18:39:40,515][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-03 18:40:07,845][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 18:40:07,845][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-03 18:40:35,640][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 18:40:35,640][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-03 18:41:03,340][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 18:41:03,341][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-03 18:41:31,024][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 18:41:31,025][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-03 18:41:58,542][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 18:41:58,543][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-03 18:42:25,661][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 18:42:25,662][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-03 18:42:25,662][energy][INFO] - 			+ CPU: 0.000293 (kWh)
+[PROC-0][2024-12-03 18:42:25,662][energy][INFO] - 			+ GPU: 0.000515 (kWh)
+[PROC-0][2024-12-03 18:42:25,662][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-03 18:42:25,663][energy][INFO] - 			+ total: 0.000813 (kWh)
+[PROC-0][2024-12-03 18:42:25,663][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-03 18:42:25,663][energy][INFO] - 			+ CPU: 0.000328 (kWh)
+[PROC-0][2024-12-03 18:42:25,663][energy][INFO] - 			+ GPU: 0.000585 (kWh)
+[PROC-0][2024-12-03 18:42:25,663][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-03 18:42:25,663][energy][INFO] - 			+ total: 0.000917 (kWh)
+[PROC-0][2024-12-03 18:42:25,663][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-03 18:42:25,663][energy][INFO] - 			+ CPU: 0.000324 (kWh)
+[PROC-0][2024-12-03 18:42:25,664][energy][INFO] - 			+ GPU: 0.000570 (kWh)
+[PROC-0][2024-12-03 18:42:25,664][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-03 18:42:25,664][energy][INFO] - 			+ total: 0.000898 (kWh)
+[PROC-0][2024-12-03 18:42:25,664][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-03 18:42:25,664][energy][INFO] - 			+ CPU: 0.000334 (kWh)
+[PROC-0][2024-12-03 18:42:25,664][energy][INFO] - 			+ GPU: 0.000584 (kWh)
+[PROC-0][2024-12-03 18:42:25,664][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-03 18:42:25,664][energy][INFO] - 			+ total: 0.000922 (kWh)
+[PROC-0][2024-12-03 18:42:25,665][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-03 18:42:25,665][energy][INFO] - 			+ CPU: 0.000325 (kWh)
+[PROC-0][2024-12-03 18:42:25,665][energy][INFO] - 			+ GPU: 0.000569 (kWh)
+[PROC-0][2024-12-03 18:42:25,665][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-03 18:42:25,665][energy][INFO] - 			+ total: 0.000898 (kWh)
+[PROC-0][2024-12-03 18:42:25,665][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-03 18:42:25,665][energy][INFO] - 			+ CPU: 0.000323 (kWh)
+[PROC-0][2024-12-03 18:42:25,665][energy][INFO] - 			+ GPU: 0.000567 (kWh)
+[PROC-0][2024-12-03 18:42:25,665][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-03 18:42:25,666][energy][INFO] - 			+ total: 0.000894 (kWh)
+[PROC-0][2024-12-03 18:42:25,666][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-03 18:42:25,666][energy][INFO] - 			+ CPU: 0.000328 (kWh)
+[PROC-0][2024-12-03 18:42:25,666][energy][INFO] - 			+ GPU: 0.000572 (kWh)
+[PROC-0][2024-12-03 18:42:25,666][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-03 18:42:25,666][energy][INFO] - 			+ total: 0.000905 (kWh)
+[PROC-0][2024-12-03 18:42:25,666][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-03 18:42:25,666][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-03 18:42:25,667][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-03 18:42:25,667][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 18:42:25,715][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-03 18:42:25,715][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-03 18:42:25,715][energy][INFO] - 			+ CPU: 0.000327 (kWh)
+[PROC-0][2024-12-03 18:42:25,715][energy][INFO] - 			+ GPU: 0.000573 (kWh)
+[PROC-0][2024-12-03 18:42:25,715][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-03 18:42:25,716][energy][INFO] - 			+ total: 0.000904 (kWh)
+[PROC-0][2024-12-03 18:42:25,716][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-03 18:42:25,716][energy][INFO] - 			+ CPU: 0.000325 (kWh)
+[PROC-0][2024-12-03 18:42:25,716][energy][INFO] - 			+ GPU: 0.000571 (kWh)
+[PROC-0][2024-12-03 18:42:25,716][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-03 18:42:25,716][energy][INFO] - 			+ total: 0.000900 (kWh)
+[PROC-0][2024-12-03 18:42:25,716][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-03 18:42:25,716][energy][INFO] - 			+ CPU: 0.000320 (kWh)
+[PROC-0][2024-12-03 18:42:25,716][energy][INFO] - 			+ GPU: 0.000562 (kWh)
+[PROC-0][2024-12-03 18:42:25,717][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-03 18:42:25,717][energy][INFO] - 			+ total: 0.000887 (kWh)
+[PROC-0][2024-12-03 18:42:25,717][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-03 18:42:25,717][energy][INFO] - 			+ CPU: 0.000097 (kWh)
+[PROC-0][2024-12-03 18:42:25,717][energy][INFO] - 			+ GPU: 0.000162 (kWh)
+[PROC-0][2024-12-03 18:42:25,717][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-03 18:42:25,717][energy][INFO] - 			+ total: 0.000259 (kWh)
+[PROC-0][2024-12-03 18:42:25,717][energy][INFO] - 		+ forward energy efficiency: 1230531.648862 (samples/kWh)
+[PROC-0][2024-12-03 18:42:25,718][energy][INFO] - 		+ preprocess energy efficiency: 3856030.446142 (samples/kWh)
+[2024-12-03 18:42:26,402][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-03 18:42:26,450][datasets][INFO] - PyTorch version 2.4.0 available.

image_classification/microsoft/resnet-50/2024-12-03-18-37-27/experiment_config.json

@@ -0,0 +1,107 @@
+{
+    "experiment_name": "image_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "image-classification",
+        "model": "microsoft/resnet-50",
+        "processor": "microsoft/resnet-50",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/image_classification",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}

image_classification/microsoft/resnet-50/2024-12-03-18-37-27/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-03T18:42:25",
+    "project_name": "codecarbon",
+    "run_id": "b94ac2e8-596e-42b1-8c9e-6543860f8a8e",
+    "duration": -1732037983.2031128,
+    "emissions": 0.0003273944172094787,
+    "emissions_rate": 1.2075583486384001e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 74.66230499324061,
+    "ram_power": 0.5942530632019043,
+    "cpu_energy": 0.0003201444721040187,
+    "gpu_energy": 0.0005623048942844378,
+    "ram_energy": 4.475387356327922e-06,
+    "energy_consumed": 0.0008869247537447843,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

image_classification/microsoft/resnet-50/2024-12-03-18-37-27/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-03T18:37:49",
+    "project_name": "codecarbon",
+    "run_id": "b94ac2e8-596e-42b1-8c9e-6543860f8a8e",
+    "duration": -1732038002.112201,
+    "emissions": 9.572911392857376e-05,
+    "emissions_rate": 1.1669907748273914e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 70.95781832217409,
+    "ram_power": 0.3441739082336426,
+    "cpu_energy": 9.686615021411045e-05,
+    "gpu_energy": 0.00016168374046188205,
+    "ram_energy": 7.841612635117118e-07,
+    "energy_consumed": 0.00025933405193950425,
+    "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/all-MiniLM-L6-v2/2024-12-03-17-27-27/.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/all-MiniLM-L6-v2
+  processor: sentence-transformers/all-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/all-MiniLM-L6-v2/2024-12-03-17-27-27/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/sentence_similarity/sentence-transformers/all-MiniLM-L6-v2/2024-12-03-17-27-27
+  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/all-MiniLM-L6-v2/2024-12-03-17-27-27
+    - hydra.mode=RUN
+    task:
+    - backend.model=sentence-transformers/all-MiniLM-L6-v2
+    - backend.processor=sentence-transformers/all-MiniLM-L6-v2
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=sentence-transformers/all-MiniLM-L6-v2,backend.processor=sentence-transformers/all-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/all-MiniLM-L6-v2/2024-12-03-17-27-27
+    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/all-MiniLM-L6-v2/2024-12-03-17-27-27/.hydra/overrides.yaml

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

sentence_similarity/sentence-transformers/all-MiniLM-L6-v2/2024-12-03-17-27-27/benchmark_report.json

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

sentence_similarity/sentence-transformers/all-MiniLM-L6-v2/2024-12-03-17-27-27/cli.log

@@ -0,0 +1,113 @@
+[2024-12-03 17:27:30,067][launcher][INFO] - ََAllocating process launcher
+[2024-12-03 17:27:30,067][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-03 17:27:30,079][device-isolation][INFO] - 	+ Launched device(s) isolation process 452
+[2024-12-03 17:27:30,080][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-03 17:27:30,086][process][INFO] - 	+ Launched benchmark in isolated process 453.
+[PROC-0][2024-12-03 17:27:32,819][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-03 17:27:33,783][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-03 17:27:33,783][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-03 17:27:35,506][pytorch][INFO] - 	+ Using AutoModel class AutoModel
+[PROC-0][2024-12-03 17:27:35,506][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-03 17:27:35,506][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-03 17:27:35,507][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-03 17:27:35,507][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-03 17:27:35,507][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-03 17:27:35,509][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-03 17:27:35,509][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-03 17:27:35,510][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-03 17:27:35,510][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-03 17:27:35,808][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-03 17:27:35,814][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-03 17:27:35,814][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-03 17:27:36,606][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-03 17:27:36,607][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-03 17:27:40,793][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-03 17:27:40,958][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-03 17:27:40,959][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-03 17:27:40,959][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-03 17:27:40,959][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-03 17:27:41,669][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-03 17:27:41,669][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-03 17:27:44,923][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:27:44,924][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-03 17:27:48,007][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:27:48,008][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-03 17:27:51,221][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:27:51,221][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-03 17:27:54,440][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:27:54,440][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-03 17:27:57,639][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:27:57,639][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-03 17:28:00,846][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:28:00,846][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-03 17:28:04,066][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:28:04,066][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-03 17:28:07,296][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:28:07,296][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-03 17:28:10,543][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:28:10,544][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-03 17:28:13,646][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:28:13,647][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-03 17:28:13,647][energy][INFO] - 			+ CPU: 0.000034 (kWh)
+[PROC-0][2024-12-03 17:28:13,647][energy][INFO] - 			+ GPU: 0.000064 (kWh)
+[PROC-0][2024-12-03 17:28:13,647][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,647][energy][INFO] - 			+ total: 0.000098 (kWh)
+[PROC-0][2024-12-03 17:28:13,647][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-03 17:28:13,647][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-03 17:28:13,647][energy][INFO] - 			+ GPU: 0.000071 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 			+ total: 0.000110 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 			+ CPU: 0.000036 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 			+ GPU: 0.000070 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 			+ total: 0.000106 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 			+ GPU: 0.000071 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 			+ total: 0.000110 (kWh)
+[PROC-0][2024-12-03 17:28:13,648][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ GPU: 0.000071 (kWh)
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ total: 0.000110 (kWh)
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ GPU: 0.000071 (kWh)
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ total: 0.000110 (kWh)
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ GPU: 0.000072 (kWh)
+[PROC-0][2024-12-03 17:28:13,649][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 			+ total: 0.000110 (kWh)
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 			+ GPU: 0.000072 (kWh)
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 			+ total: 0.000110 (kWh)
+[PROC-0][2024-12-03 17:28:13,650][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 			+ CPU: 0.000038 (kWh)
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 			+ GPU: 0.000071 (kWh)
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 			+ total: 0.000110 (kWh)
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 			+ CPU: 0.000037 (kWh)
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 			+ GPU: 0.000070 (kWh)
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 			+ total: 0.000107 (kWh)
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 			+ CPU: 0.000002 (kWh)
+[PROC-0][2024-12-03 17:28:13,651][energy][INFO] - 			+ GPU: 0.000004 (kWh)
+[PROC-0][2024-12-03 17:28:13,652][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 17:28:13,652][energy][INFO] - 			+ total: 0.000006 (kWh)
+[PROC-0][2024-12-03 17:28:13,652][energy][INFO] - 		+ forward energy efficiency: 10187337.986781 (samples/kWh)
+[PROC-0][2024-12-03 17:28:13,652][energy][INFO] - 		+ preprocess energy efficiency: 175654258.808694 (samples/kWh)
+[2024-12-03 17:28:14,309][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-03 17:28:14,356][datasets][INFO] - PyTorch version 2.4.0 available.

sentence_similarity/sentence-transformers/all-MiniLM-L6-v2/2024-12-03-17-27-27/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 @ 17:27:36] [setup] RAM Tracking...
+[codecarbon INFO @ 17:27:36] [setup] GPU Tracking...
+[codecarbon INFO @ 17:27:36] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 17:27:36] GPU available. Starting setup
+[codecarbon INFO @ 17:27:36] [setup] CPU Tracking...
+[codecarbon DEBUG @ 17:27:36] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 17:27:36] 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 @ 17:27:36] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 17:27:36] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 17:27:37] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 17:27:37] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 17:27:37] >>> Tracker's metadata:
+[codecarbon INFO @ 17:27:37]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 17:27:37]   Python version: 3.9.20
+[codecarbon INFO @ 17:27:37]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 17:27:37]   Available RAM : 186.705 GB
+[codecarbon INFO @ 17:27:37]   CPU count: 48
+[codecarbon INFO @ 17:27:37]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 17:27:37]   GPU count: 1
+[codecarbon INFO @ 17:27:37]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 17:27:38] Not running on AWS
+[codecarbon DEBUG @ 17:27:39] Not running on Azure
+[codecarbon DEBUG @ 17:27:40] Not running on GCP
+[codecarbon INFO @ 17:27:40] Saving emissions data to file /runs/sentence_similarity/sentence-transformers/all-MiniLM-L6-v2/2024-12-03-17-27-27/codecarbon.csv
+[codecarbon DEBUG @ 17:27:40] EmissionsData(timestamp='2024-12-03T17:27:40', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.002136246068403125, 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 @ 17:27:40] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.2655043601989746 W
+[codecarbon DEBUG @ 17:27:40] RAM : 0.27 W during 0.16 s [measurement time: 0.0005]
+[codecarbon INFO @ 17:27:40] Energy consumed for all GPUs : 0.000004 kWh. Total GPU Power : 83.40582264689574 W
+[codecarbon DEBUG @ 17:27:40] GPU : 83.41 W during 0.16 s [measurement time: 0.0022]
+[codecarbon INFO @ 17:27:40] Energy consumed for all CPUs : 0.000002 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:27:40] CPU : 42.50 W during 0.16 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:27:40] 0.000006 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:27:40] last_duration=0.16088268999010324
+------------------------
+[codecarbon DEBUG @ 17:27:40] EmissionsData(timestamp='2024-12-03T17:27:40', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.16403498221188784, emissions=2.1014826534480243e-06, emissions_rate=1.2811185913584517e-05, cpu_power=42.5, gpu_power=83.40582264689574, ram_power=0.2655043601989746, cpu_energy=1.9352999284617707e-06, gpu_energy=3.745836330892871e-06, ram_energy=1.1865474745674232e-08, energy_consumed=5.693001734100316e-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 @ 17:27:41] EmissionsData(timestamp='2024-12-03T17:27:41', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.0022145879920572042, emissions=2.1014826534480243e-06, emissions_rate=0.0009489271417460759, cpu_power=42.5, gpu_power=83.40582264689574, ram_power=0.2655043601989746, cpu_energy=1.9352999284617707e-06, gpu_energy=3.745836330892871e-06, ram_energy=1.1865474745674232e-08, energy_consumed=5.693001734100316e-06, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 17:27:44] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 17:27:44] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.34078216552734375 W
+[codecarbon DEBUG @ 17:27:44] RAM : 0.34 W during 3.25 s [measurement time: 0.0005]
+[codecarbon INFO @ 17:27:44] Energy consumed for all GPUs : 0.000075 kWh. Total GPU Power : 78.88328900630715 W
+[codecarbon DEBUG @ 17:27:44] GPU : 78.88 W during 3.25 s [measurement time: 0.0023]
+[codecarbon INFO @ 17:27:44] Energy consumed for all CPUs : 0.000040 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:27:44] CPU : 42.50 W during 3.25 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:27:44] 0.000116 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:27:44] last_duration=3.2499246599618345
+------------------------
+[codecarbon DEBUG @ 17:27:44] EmissionsData(timestamp='2024-12-03T17:27:44', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.253297318937257, emissions=4.268653913823294e-05, emissions_rate=1.3121007689569916e-05, cpu_power=42.5, gpu_power=78.88328900630715, ram_power=0.34078216552734375, cpu_energy=4.034108823446635e-05, gpu_energy=7.497894887364964e-05, ram_energy=3.1952857565166694e-07, energy_consumed=0.00011563956568376766, 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 @ 17:27:44] EmissionsData(timestamp='2024-12-03T17:27:44', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.0020191711373627186, emissions=4.268653913823294e-05, emissions_rate=0.021140624659476224, cpu_power=42.5, gpu_power=78.88328900630715, ram_power=0.34078216552734375, cpu_energy=4.034108823446635e-05, gpu_energy=7.497894887364964e-05, ram_energy=3.1952857565166694e-07, energy_consumed=0.00011563956568376766, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 17:27:48] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 17:27:48] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.34087371826171875 W
+[codecarbon DEBUG @ 17:27:48] RAM : 0.34 W during 3.08 s [measurement time: 0.0004]
+[codecarbon INFO @ 17:27:48] Energy consumed for all GPUs : 0.000145 kWh. Total GPU Power : 81.45146171903654 W
+[codecarbon DEBUG @ 17:27:48] GPU : 81.45 W during 3.08 s [measurement time: 0.0023]
+[codecarbon INFO @ 17:27:48] Energy consumed for all CPUs : 0.000077 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:27:48] CPU : 42.50 W during 3.08 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:27:48] 0.000222 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:27:48] last_duration=3.0799942889716476
+------------------------
+[codecarbon DEBUG @ 17:27:48] EmissionsData(timestamp='2024-12-03T17:27:48', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.0831521609798074, emissions=8.195962681479956e-05, emissions_rate=2.6583062572154492e-05, cpu_power=42.5, gpu_power=81.45146171903654, ram_power=0.34087371826171875, cpu_energy=7.673816447430808e-05, gpu_energy=0.00014468261574762664, ram_energy=6.111727029667126e-07, energy_consumed=0.00022203195292490145, 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 @ 17:27:48] EmissionsData(timestamp='2024-12-03T17:27:48', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.002026340924203396, emissions=8.195962681479956e-05, emissions_rate=0.040447106326404525, cpu_power=42.5, gpu_power=81.45146171903654, ram_power=0.34087371826171875, cpu_energy=7.673816447430808e-05, gpu_energy=0.00014468261574762664, ram_energy=6.111727029667126e-07, energy_consumed=0.00022203195292490145, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 17:27:51] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 17:27:51] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.34090232849121094 W
+[codecarbon DEBUG @ 17:27:51] RAM : 0.34 W during 3.21 s [measurement time: 0.0004]
+[codecarbon INFO @ 17:27:51] Energy consumed for all GPUs : 0.000216 kWh. Total GPU Power : 80.27951851539734 W
+[codecarbon DEBUG @ 17:27:51] GPU : 80.28 W during 3.21 s [measurement time: 0.0064]
+[codecarbon INFO @ 17:27:51] Energy consumed for all CPUs : 0.000115 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:27:51] CPU : 42.50 W during 3.21 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:27:51] 0.000332 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:27:51] last_duration=3.205060424050316
+------------------------
+[codecarbon DEBUG @ 17:27:51] EmissionsData(timestamp='2024-12-03T17:27:51', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.212398014962673, emissions=0.0001224596736853669, emissions_rate=3.812095298122323e-05, cpu_power=42.5, gpu_power=80.27951851539734, ram_power=0.34090232849121094, cpu_energy=0.0001146611426885809, gpu_energy=0.00021617239516302789, ram_energy=9.146845304683606e-07, energy_consumed=0.00033174822238207714, 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 @ 17:27:51] EmissionsData(timestamp='2024-12-03T17:27:51', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.002021312015131116, emissions=0.0001224596736853669, emissions_rate=0.06058425060983143, cpu_power=42.5, gpu_power=80.27951851539734, ram_power=0.34090232849121094, cpu_energy=0.0001146611426885809, gpu_energy=0.00021617239516302789, ram_energy=9.146845304683606e-07, energy_consumed=0.00033174822238207714, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 17:27:54] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 17:27:54] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.34090375900268555 W
+[codecarbon DEBUG @ 17:27:54] RAM : 0.34 W during 3.21 s [measurement time: 0.0004]
+[codecarbon INFO @ 17:27:54] Energy consumed for all GPUs : 0.000288 kWh. Total GPU Power : 80.02529425974497 W
+[codecarbon DEBUG @ 17:27:54] GPU : 80.03 W during 3.21 s [measurement time: 0.0057]
+[codecarbon INFO @ 17:27:54] Energy consumed for all CPUs : 0.000153 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:27:54] CPU : 42.50 W during 3.22 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:27:54] 0.000441 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:27:54] last_duration=3.2114167609252036
+------------------------
+[codecarbon DEBUG @ 17:27:54] EmissionsData(timestamp='2024-12-03T17:27:54', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.2180411859881133, emissions=0.000162953254371185, emissions_rate=5.063740485383176e-05, cpu_power=42.5, gpu_power=80.02529425974497, ram_power=0.34090375900268555, cpu_energy=0.00015265072303025388, gpu_energy=0.00028757745228702447, ram_energy=1.218799365251766e-06, energy_consumed=0.0004414469746825301, 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 @ 17:27:54] EmissionsData(timestamp='2024-12-03T17:27:54', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.0020318119786679745, emissions=0.000162953254371185, emissions_rate=0.08020095170322537, cpu_power=42.5, gpu_power=80.02529425974497, ram_power=0.34090375900268555, cpu_energy=0.00015265072303025388, gpu_energy=0.00028757745228702447, ram_energy=1.218799365251766e-06, energy_consumed=0.0004414469746825301, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 17:27:57] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 17:27:57] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34090662002563477 W
+[codecarbon DEBUG @ 17:27:57] RAM : 0.34 W during 3.20 s [measurement time: 0.0004]
+[codecarbon INFO @ 17:27:57] Energy consumed for all GPUs : 0.000359 kWh. Total GPU Power : 80.50833834750415 W
+[codecarbon DEBUG @ 17:27:57] GPU : 80.51 W during 3.20 s [measurement time: 0.0023]
+[codecarbon INFO @ 17:27:57] Energy consumed for all CPUs : 0.000190 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:27:57] CPU : 42.50 W during 3.20 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:27:57] 0.000551 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:27:57] last_duration=3.1950438488274813
+------------------------
+[codecarbon DEBUG @ 17:27:57] EmissionsData(timestamp='2024-12-03T17:27:57', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.198286573868245, emissions=0.0002033840723078556, emissions_rate=6.359157242806664e-05, cpu_power=42.5, gpu_power=80.50833834750415, ram_power=0.34090662002563477, cpu_energy=0.00019040710182032652, gpu_energy=0.00035904723168300734, ram_energy=1.5213666468569857e-06, energy_consumed=0.0005509757001501909, 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 @ 17:27:57] EmissionsData(timestamp='2024-12-03T17:27:57', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.002005632035434246, emissions=0.0002033840723078556, emissions_rate=0.1014064737272808, cpu_power=42.5, gpu_power=80.50833834750415, ram_power=0.34090662002563477, cpu_energy=0.00019040710182032652, gpu_energy=0.00035904723168300734, ram_energy=1.5213666468569857e-06, energy_consumed=0.0005509757001501909, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 17:28:00] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 17:28:00] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.340909481048584 W
+[codecarbon DEBUG @ 17:28:00] RAM : 0.34 W during 3.20 s [measurement time: 0.0005]
+[codecarbon INFO @ 17:28:00] Energy consumed for all GPUs : 0.000431 kWh. Total GPU Power : 80.42918174151322 W
+[codecarbon DEBUG @ 17:28:00] GPU : 80.43 W during 3.20 s [measurement time: 0.0022]
+[codecarbon INFO @ 17:28:00] Energy consumed for all CPUs : 0.000228 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:28:00] CPU : 42.50 W during 3.21 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:28:00] 0.000661 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:28:00] last_duration=3.202793454984203
+------------------------
+[codecarbon DEBUG @ 17:28:00] EmissionsData(timestamp='2024-12-03T17:28:00', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.2059976290911436, emissions=0.0002438871582391259, emissions_rate=7.607215801599472e-05, cpu_power=42.5, gpu_power=80.42918174151322, ram_power=0.340909481048584, cpu_energy=0.00022825435440819195, gpu_energy=0.000430621177830659, ram_energy=1.8246703072093944e-06, energy_consumed=0.0006607002025460604, 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 @ 17:28:00] EmissionsData(timestamp='2024-12-03T17:28:00', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.003235484939068556, emissions=0.0002438871582391259, emissions_rate=0.0753788575227728, cpu_power=42.5, gpu_power=80.42918174151322, ram_power=0.340909481048584, cpu_energy=0.00022825435440819195, gpu_energy=0.000430621177830659, ram_energy=1.8246703072093944e-06, energy_consumed=0.0006607002025460604, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 17:28:04] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 17:28:04] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.340909481048584 W
+[codecarbon DEBUG @ 17:28:04] RAM : 0.34 W during 3.22 s [measurement time: 0.0005]
+[codecarbon INFO @ 17:28:04] Energy consumed for all GPUs : 0.000502 kWh. Total GPU Power : 79.9737333941352 W
+[codecarbon DEBUG @ 17:28:04] GPU : 79.97 W during 3.22 s [measurement time: 0.0023]
+[codecarbon INFO @ 17:28:04] Energy consumed for all CPUs : 0.000266 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:28:04] CPU : 42.50 W during 3.22 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:28:04] 0.000770 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:28:04] EmissionsData(timestamp='2024-12-03T17:28:04', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.218712278874591, emissions=0.00028440024936486055, emissions_rate=8.835839451431176e-05, cpu_power=42.5, gpu_power=79.9737333941352, ram_power=0.340909481048584, cpu_energy=0.00026625195854818837, gpu_energy=0.0005020706794347518, ram_energy=2.1291714365555452e-06, energy_consumed=0.0007704518094194957, 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 @ 17:28:04] 0.012599 g.CO2eq/s mean an estimation of 397.33480401749296 kg.CO2eq/year
+[codecarbon DEBUG @ 17:28:04] last_duration=3.2154337328393012
+------------------------
+[codecarbon DEBUG @ 17:28:04] EmissionsData(timestamp='2024-12-03T17:28:04', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.2190629618708044, emissions=0.00028440024936486055, emissions_rate=8.834876879810306e-05, cpu_power=42.5, gpu_power=79.9737333941352, ram_power=0.340909481048584, cpu_energy=0.00026625195854818837, gpu_energy=0.0005020706794347518, ram_energy=2.1291714365555452e-06, energy_consumed=0.0007704518094194957, 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 @ 17:28:04] EmissionsData(timestamp='2024-12-03T17:28:04', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.0020292322151362896, emissions=0.00028440024936486055, emissions_rate=0.14015165304566157, cpu_power=42.5, gpu_power=79.9737333941352, ram_power=0.340909481048584, cpu_energy=0.00026625195854818837, gpu_energy=0.0005020706794347518, ram_energy=2.1291714365555452e-06, energy_consumed=0.0007704518094194957, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 17:28:07] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 17:28:07] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.3409123420715332 W
+[codecarbon DEBUG @ 17:28:07] RAM : 0.34 W during 3.22 s [measurement time: 0.0004]
+[codecarbon INFO @ 17:28:07] Energy consumed for all GPUs : 0.000574 kWh. Total GPU Power : 79.90649134801077 W
+[codecarbon DEBUG @ 17:28:07] GPU : 79.91 W during 3.22 s [measurement time: 0.0056]
+[codecarbon INFO @ 17:28:07] Energy consumed for all CPUs : 0.000304 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:28:07] CPU : 42.50 W during 3.23 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:28:07] 0.000880 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:28:07] last_duration=3.222660018131137
+------------------------
+[codecarbon DEBUG @ 17:28:07] EmissionsData(timestamp='2024-12-03T17:28:07', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.2291442879941314, emissions=0.0003249955170073433, emissions_rate=0.00010064447049197139, cpu_power=42.5, gpu_power=79.90649134801077, ram_power=0.3409123420715332, cpu_energy=0.0003043726071419466, gpu_energy=0.0005736190700069699, ram_energy=2.4343586605649717e-06, energy_consumed=0.0008804260358094815, 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 @ 17:28:07] EmissionsData(timestamp='2024-12-03T17:28:07', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.0020259409211575985, emissions=0.0003249955170073433, emissions_rate=0.1604170751542176, cpu_power=42.5, gpu_power=79.90649134801077, ram_power=0.3409123420715332, cpu_energy=0.0003043726071419466, gpu_energy=0.0005736190700069699, ram_energy=2.4343586605649717e-06, energy_consumed=0.0008804260358094815, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 17:28:10] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 17:28:10] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.3409123420715332 W
+[codecarbon DEBUG @ 17:28:10] RAM : 0.34 W during 3.24 s [measurement time: 0.0004]
+[codecarbon INFO @ 17:28:10] Energy consumed for all GPUs : 0.000645 kWh. Total GPU Power : 79.20958686324002 W
+[codecarbon DEBUG @ 17:28:10] GPU : 79.21 W during 3.24 s [measurement time: 0.0023]
+[codecarbon INFO @ 17:28:10] Energy consumed for all CPUs : 0.000343 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:28:10] CPU : 42.50 W during 3.25 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:28:10] 0.000990 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:28:10] last_duration=3.243541341042146
+------------------------
+[codecarbon DEBUG @ 17:28:10] EmissionsData(timestamp='2024-12-03T17:28:10', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.246739154914394, emissions=0.0003656073799658421, emissions_rate=0.00011260756177854453, cpu_power=42.5, gpu_power=79.20958686324002, ram_power=0.3409123420715332, cpu_energy=0.00034270095814588586, gpu_energy=0.0006450027382243206, ram_energy=2.7415232133732965e-06, energy_consumed=0.0009904452195835798, 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 @ 17:28:10] EmissionsData(timestamp='2024-12-03T17:28:10', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=0.002620323095470667, emissions=0.0003656073799658421, emissions_rate=0.13952759512665025, cpu_power=42.5, gpu_power=79.20958686324002, ram_power=0.3409123420715332, cpu_energy=0.00034270095814588586, gpu_energy=0.0006450027382243206, ram_energy=2.7415232133732965e-06, energy_consumed=0.0009904452195835798, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 17:28:13] Background scheduler didn't run for a long period (3s), results might be inaccurate
+[codecarbon INFO @ 17:28:13] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.3409123420715332 W
+[codecarbon DEBUG @ 17:28:13] RAM : 0.34 W during 3.10 s [measurement time: 0.0004]
+[codecarbon INFO @ 17:28:13] Energy consumed for all GPUs : 0.000715 kWh. Total GPU Power : 80.98731760148895 W
+[codecarbon DEBUG @ 17:28:13] GPU : 80.99 W during 3.10 s [measurement time: 0.0035]
+[codecarbon INFO @ 17:28:13] Energy consumed for all CPUs : 0.000379 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 17:28:13] CPU : 42.50 W during 3.10 s [measurement time: 0.0000]
+[codecarbon INFO @ 17:28:13] 0.001097 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 17:28:13] last_duration=3.0973922731354833
+------------------------
+[codecarbon DEBUG @ 17:28:13] EmissionsData(timestamp='2024-12-03T17:28:13', project_name='codecarbon', run_id='732fc27a-1994-4201-9f5c-c78f30ffb9be', duration=3.101867353077978, emissions=0.00040496082985680935, emissions_rate=0.00013055388376133085, cpu_power=42.5, gpu_power=80.98731760148895, ram_power=0.3409123420715332, cpu_energy=0.00037931905859958436, gpu_energy=0.0007147014050943312, ram_energy=3.034847628709558e-06, energy_consumed=0.0010970553113226252, 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/all-MiniLM-L6-v2/2024-12-03-17-27-27/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/all-MiniLM-L6-v2",
+        "processor": "sentence-transformers/all-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/all-MiniLM-L6-v2/2024-12-03-17-27-27/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-03T17:28:13",
+    "project_name": "codecarbon",
+    "run_id": "732fc27a-1994-4201-9f5c-c78f30ffb9be",
+    "duration": -1732038007.215988,
+    "emissions": 3.9353449890967254e-05,
+    "emissions_rate": 1.2697745455672623e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 80.98731760148895,
+    "ram_power": 0.3409123420715332,
+    "cpu_energy": 3.661810045369851e-05,
+    "gpu_energy": 6.969866687001058e-05,
+    "ram_energy": 2.9332441533626145e-07,
+    "energy_consumed": 0.00010661009173904543,
+    "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/all-MiniLM-L6-v2/2024-12-03-17-27-27/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-03T17:27:40",
+    "project_name": "codecarbon",
+    "run_id": "732fc27a-1994-4201-9f5c-c78f30ffb9be",
+    "duration": -1732038010.1533983,
+    "emissions": 2.1014826534480243e-06,
+    "emissions_rate": 1.2980228898053656e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 83.40582264689574,
+    "ram_power": 0.2655043601989746,
+    "cpu_energy": 1.9352999284617707e-06,
+    "gpu_energy": 3.745836330892871e-06,
+    "ram_energy": 1.1865474745674232e-08,
+    "energy_consumed": 5.693001734100316e-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/all-mpnet-base-v2/2024-12-03-17-25-01/.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/all-mpnet-base-v2
+  processor: sentence-transformers/all-mpnet-base-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/all-mpnet-base-v2/2024-12-03-17-25-01/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/sentence_similarity/sentence-transformers/all-mpnet-base-v2/2024-12-03-17-25-01
+  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/all-mpnet-base-v2/2024-12-03-17-25-01
+    - hydra.mode=RUN
+    task:
+    - backend.model=sentence-transformers/all-mpnet-base-v2
+    - backend.processor=sentence-transformers/all-mpnet-base-v2
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=sentence-transformers/all-mpnet-base-v2,backend.processor=sentence-transformers/all-mpnet-base-v2
+    id: ???
+    num: ???
+    config_name: sentence_similarity
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
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+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
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+      schema: structured
+      provider: schema
+    output_dir: /runs/sentence_similarity/sentence-transformers/all-mpnet-base-v2/2024-12-03-17-25-01
+    choices:
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+      launcher: process
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+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
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+      hydra/output: default
+  verbose: false

sentence_similarity/sentence-transformers/all-mpnet-base-v2/2024-12-03-17-25-01/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=sentence-transformers/all-mpnet-base-v2
+- backend.processor=sentence-transformers/all-mpnet-base-v2

sentence_similarity/sentence-transformers/all-mpnet-base-v2/2024-12-03-17-25-01/benchmark_report.json

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sentence_similarity/sentence-transformers/all-mpnet-base-v2/2024-12-03-17-25-01/cli.log

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+[PROC-0][2024-12-03 17:25:55,150][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:25:55,150][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-03 17:26:08,046][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-03 17:26:08,047][energy_star][INFO] - 	+ Iteration 5/10
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+[2024-12-03 17:27:26,219][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-03 17:27:26,271][datasets][INFO] - PyTorch version 2.4.0 available.

sentence_similarity/sentence-transformers/all-mpnet-base-v2/2024-12-03-17-25-01/experiment_config.json

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

sentence_similarity/sentence-transformers/all-mpnet-base-v2/2024-12-03-17-25-01/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
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+    "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/all-mpnet-base-v2/2024-12-03-17-25-01/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-03T17:25:16",
+    "project_name": "codecarbon",
+    "run_id": "ea6e7f2a-efe7-45bc-ae2f-b60652620784",
+    "duration": -1732038010.154033,
+    "emissions": 2.0675599400542375e-06,
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+    "energy_consumed": 5.601103727776376e-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,
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+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

text_generation/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15/.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: Qwen/Qwen2.5-1.5B-Instruct
+  processor: Qwen/Qwen2.5-1.5B-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/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/text_generation/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15
+  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/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15
+    - hydra.mode=RUN
+    task:
+    - backend.model=Qwen/Qwen2.5-1.5B-Instruct
+    - backend.processor=Qwen/Qwen2.5-1.5B-Instruct
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=Qwen/Qwen2.5-1.5B-Instruct,backend.processor=Qwen/Qwen2.5-1.5B-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/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15
+    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/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=Qwen/Qwen2.5-1.5B-Instruct
+- backend.processor=Qwen/Qwen2.5-1.5B-Instruct

text_generation/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15/benchmark_report.json

@@ -0,0 +1,203 @@
+{
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+}

text_generation/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15/cli.log

@@ -0,0 +1,188 @@
+[2024-12-03 17:28:18,232][launcher][INFO] - ََAllocating process launcher
+[2024-12-03 17:28:18,232][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-03 17:28:18,244][process][INFO] - 	+ Launched benchmark in isolated process 697.
+[PROC-0][2024-12-03 17:28:20,817][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-03 17:28:21,803][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-03 17:28:21,803][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-03 17:28:22,989][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCausalLM
+[PROC-0][2024-12-03 17:28:22,989][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-03 17:28:22,989][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-03 17:28:22,990][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-03 17:28:22,990][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-03 17:28:22,990][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-03 17:28:23,013][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-03 17:28:23,013][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-03 17:28:23,014][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-03 17:28:23,014][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-03 17:28:23,293][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-03 17:28:23,299][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-03 17:28:23,300][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-03 17:28:24,818][energy_star][INFO] - 	+ Updating Text Generation kwargs with default values
+[PROC-0][2024-12-03 17:28:24,818][energy_star][INFO] - 	+ Initializing Text Generation report
+[PROC-0][2024-12-03 17:28:24,818][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-03 17:28:29,020][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-03 17:28:30,067][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-03 17:28:30,067][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-03 17:28:30,067][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-03 17:28:30,068][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-03 17:28:31,721][energy_star][INFO] - 	+ Additional warmup for Text Generation
+[PROC-0][2024-12-03 17:28:31,998][energy_star][INFO] - 	+ Running Text Generation energy tracking for 10 iterations
+[PROC-0][2024-12-03 17:28:31,999][energy_star][INFO] - 	+ Prefill iteration 1/10
+[PROC-0][2024-12-03 17:30:09,885][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-03 17:30:09,885][energy_star][INFO] - 	+ Prefill iteration 2/10
+[PROC-0][2024-12-03 17:31:48,100][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-03 17:31:48,101][energy_star][INFO] - 	+ Prefill iteration 3/10
+[PROC-0][2024-12-03 17:33:26,209][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-03 17:33:26,210][energy_star][INFO] - 	+ Prefill iteration 4/10
+[PROC-0][2024-12-03 17:35:04,397][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-03 17:35:04,397][energy_star][INFO] - 	+ Prefill iteration 5/10
+[PROC-0][2024-12-03 17:36:42,536][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-03 17:36:42,536][energy_star][INFO] - 	+ Prefill iteration 6/10
+[PROC-0][2024-12-03 17:38:20,526][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-03 17:38:20,526][energy_star][INFO] - 	+ Prefill iteration 7/10
+[PROC-0][2024-12-03 17:39:57,836][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-03 17:39:57,837][energy_star][INFO] - 	+ Prefill iteration 8/10
+[PROC-0][2024-12-03 17:41:35,525][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-03 17:41:35,525][energy_star][INFO] - 	+ Prefill iteration 9/10
+[PROC-0][2024-12-03 17:43:13,714][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-03 17:43:13,714][energy_star][INFO] - 	+ Prefill iteration 10/10
+[PROC-0][2024-12-03 17:44:51,844][energy][INFO] - 	+ Saving codecarbon emission data to prefill_codecarbon.json
+[PROC-0][2024-12-03 17:44:51,844][energy_star][INFO] - 	+ Decoding iteration 1/10
+[PROC-0][2024-12-03 17:50:07,050][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-03 17:50:07,050][energy_star][INFO] - 	+ Decoding iteration 2/10
+[PROC-0][2024-12-03 17:55:22,212][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-03 17:55:22,212][energy_star][INFO] - 	+ Decoding iteration 3/10
+[PROC-0][2024-12-03 18:00:37,855][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-03 18:00:37,855][energy_star][INFO] - 	+ Decoding iteration 4/10
+[PROC-0][2024-12-03 18:05:53,198][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-03 18:05:53,199][energy_star][INFO] - 	+ Decoding iteration 5/10
+[PROC-0][2024-12-03 18:11:08,550][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-03 18:11:08,551][energy_star][INFO] - 	+ Decoding iteration 6/10
+[PROC-0][2024-12-03 18:16:24,043][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-03 18:16:24,044][energy_star][INFO] - 	+ Decoding iteration 7/10
+[PROC-0][2024-12-03 18:21:39,640][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-03 18:21:39,640][energy_star][INFO] - 	+ Decoding iteration 8/10
+[PROC-0][2024-12-03 18:26:55,273][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-03 18:26:55,274][energy_star][INFO] - 	+ Decoding iteration 9/10
+[PROC-0][2024-12-03 18:32:10,535][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-03 18:32:10,535][energy_star][INFO] - 	+ Decoding iteration 10/10
+[PROC-0][2024-12-03 18:37:25,556][energy][INFO] - 	+ Saving codecarbon emission data to generate_codecarbon.json
+[PROC-0][2024-12-03 18:37:25,557][energy][INFO] - 		+ prefill energy consumption:
+[PROC-0][2024-12-03 18:37:25,557][energy][INFO] - 			+ CPU: 0.001042 (kWh)
+[PROC-0][2024-12-03 18:37:25,557][energy][INFO] - 			+ GPU: 0.007093 (kWh)
+[PROC-0][2024-12-03 18:37:25,557][energy][INFO] - 			+ RAM: 0.000011 (kWh)
+[PROC-0][2024-12-03 18:37:25,557][energy][INFO] - 			+ total: 0.008145 (kWh)
+[PROC-0][2024-12-03 18:37:25,557][energy][INFO] - 		+ prefill_iteration_1 energy consumption:
+[PROC-0][2024-12-03 18:37:25,557][energy][INFO] - 			+ CPU: 0.001156 (kWh)
+[PROC-0][2024-12-03 18:37:25,557][energy][INFO] - 			+ GPU: 0.007838 (kWh)
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 			+ RAM: 0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 			+ total: 0.009006 (kWh)
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 		+ prefill_iteration_2 energy consumption:
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 			+ CPU: 0.001159 (kWh)
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 			+ GPU: 0.007902 (kWh)
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 			+ RAM: 0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 			+ total: 0.009074 (kWh)
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 		+ prefill_iteration_3 energy consumption:
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 			+ CPU: 0.001158 (kWh)
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 			+ GPU: 0.007889 (kWh)
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 			+ RAM: 0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,558][energy][INFO] - 			+ total: 0.009059 (kWh)
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 		+ prefill_iteration_4 energy consumption:
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 			+ CPU: 0.001159 (kWh)
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 			+ GPU: 0.007895 (kWh)
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 			+ RAM: 0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 			+ total: 0.009067 (kWh)
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 		+ prefill_iteration_5 energy consumption:
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 			+ CPU: 0.001159 (kWh)
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 			+ GPU: 0.007897 (kWh)
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 			+ RAM: 0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 			+ total: 0.009067 (kWh)
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 		+ prefill_iteration_6 energy consumption:
+[PROC-0][2024-12-03 18:37:25,559][energy][INFO] - 			+ CPU: 0.001157 (kWh)
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 			+ GPU: 0.007875 (kWh)
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 			+ RAM: 0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 			+ total: 0.009044 (kWh)
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 		+ prefill_iteration_7 energy consumption:
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 		+ prefill_iteration_8 energy consumption:
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 			+ CPU: 0.001153 (kWh)
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 			+ GPU: 0.007840 (kWh)
+[PROC-0][2024-12-03 18:37:25,560][energy][INFO] - 			+ RAM: 0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 			+ total: 0.009005 (kWh)
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 		+ prefill_iteration_9 energy consumption:
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 			+ CPU: 0.001159 (kWh)
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 			+ GPU: 0.007894 (kWh)
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 			+ RAM: 0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 			+ total: 0.009065 (kWh)
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 		+ prefill_iteration_10 energy consumption:
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 			+ CPU: 0.001158 (kWh)
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 			+ GPU: 0.007895 (kWh)
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 			+ RAM: 0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 			+ total: 0.009066 (kWh)
+[PROC-0][2024-12-03 18:37:25,561][energy][INFO] - 		+ decode energy consumption:
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 			+ CPU: 0.002309 (kWh)
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 			+ GPU: 0.008326 (kWh)
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 			+ RAM: 0.000024 (kWh)
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 			+ total: 0.010659 (kWh)
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 		+ decode_iteration_1 energy consumption:
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 			+ CPU: 0.002566 (kWh)
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 			+ GPU: 0.009338 (kWh)
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 			+ RAM: 0.000027 (kWh)
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 			+ total: 0.011930 (kWh)
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 		+ decode_iteration_2 energy consumption:
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 			+ CPU: 0.002561 (kWh)
+[PROC-0][2024-12-03 18:37:25,562][energy][INFO] - 			+ GPU: 0.009251 (kWh)
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 			+ RAM: 0.000027 (kWh)
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 			+ total: 0.011839 (kWh)
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 		+ decode_iteration_3 energy consumption:
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 			+ CPU: 0.002568 (kWh)
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 			+ GPU: 0.009276 (kWh)
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 			+ RAM: 0.000027 (kWh)
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 			+ total: 0.011871 (kWh)
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 		+ decode_iteration_4 energy consumption:
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 			+ CPU: 0.002564 (kWh)
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 			+ GPU: 0.009252 (kWh)
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 			+ RAM: 0.000027 (kWh)
+[PROC-0][2024-12-03 18:37:25,563][energy][INFO] - 			+ total: 0.011843 (kWh)
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 		+ decode_iteration_5 energy consumption:
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 			+ CPU: -0.001159 (kWh)
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 			+ GPU: -0.007897 (kWh)
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 			+ RAM: -0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 			+ total: -0.009067 (kWh)
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 		+ decode_iteration_6 energy consumption:
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 			+ CPU: 0.002568 (kWh)
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 			+ GPU: 0.009297 (kWh)
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 			+ RAM: 0.000027 (kWh)
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 			+ total: 0.011892 (kWh)
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 		+ decode_iteration_7 energy consumption:
+[PROC-0][2024-12-03 18:37:25,564][energy][INFO] - 			+ CPU: 0.003726 (kWh)
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 			+ GPU: 0.017192 (kWh)
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 			+ RAM: 0.000039 (kWh)
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 			+ total: 0.020957 (kWh)
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 		+ decode_iteration_8 energy consumption:
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 			+ CPU: 0.002573 (kWh)
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 			+ GPU: 0.009311 (kWh)
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 			+ RAM: 0.000027 (kWh)
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 			+ total: 0.011911 (kWh)
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 		+ decode_iteration_9 energy consumption:
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 			+ CPU: 0.002563 (kWh)
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 			+ GPU: 0.009000 (kWh)
+[PROC-0][2024-12-03 18:37:25,565][energy][INFO] - 			+ RAM: 0.000027 (kWh)
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 			+ total: 0.011590 (kWh)
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 		+ decode_iteration_10 energy consumption:
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 			+ CPU: 0.002561 (kWh)
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 			+ GPU: 0.009240 (kWh)
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 			+ RAM: 0.000027 (kWh)
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 			+ total: 0.011827 (kWh)
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 			+ CPU: 0.000012 (kWh)
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 			+ GPU: 0.000021 (kWh)
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-03 18:37:25,566][energy][INFO] - 			+ total: 0.000033 (kWh)
+[PROC-0][2024-12-03 18:37:25,567][energy][INFO] - 		+ prefill energy efficiency: 45080238.155766 (tokens/kWh)
+[PROC-0][2024-12-03 18:37:25,567][energy][INFO] - 		+ decode energy efficiency: 844336.752318 (tokens/kWh)
+[PROC-0][2024-12-03 18:37:25,567][energy][INFO] - 		+ preprocess energy efficiency: 30293551.635430 (samples/kWh)
+[2024-12-03 18:37:26,296][datasets][INFO] - PyTorch version 2.4.0 available.

text_generation/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15/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": "Qwen/Qwen2.5-1.5B-Instruct",
+        "processor": "Qwen/Qwen2.5-1.5B-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
+    }
+}

text_generation/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15/generate_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-03T18:37:25",
+    "project_name": "codecarbon",
+    "run_id": "7a211d4e-0f2e-460c-a239-545d6b7c407d",
+    "duration": -1732037695.2965999,
+    "emissions": 0.007712389755398175,
+    "emissions_rate": 2.4482330803332173e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 195.82009333318672,
+    "ram_power": 0.4469733238220215,
+    "cpu_energy": 0.003718992364739014,
+    "gpu_energy": 0.017135072319156563,
+    "ram_energy": 3.9111940474464404e-05,
+    "energy_consumed": 0.020893176624370013,
+    "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/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15/prefill_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-03T17:44:51",
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+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
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+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}

text_generation/Qwen/Qwen2.5-1.5B-Instruct/2024-12-03-17-28-15/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-03T17:28:30",
+    "project_name": "codecarbon",
+    "run_id": "7a211d4e-0f2e-460c-a239-545d6b7c407d",
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+    "ram_energy": 9.613805157658694e-08,
+    "energy_consumed": 3.301032549879164e-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
+}