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  1. automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/.hydra/config.yaml +94 -0
  2. automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/.hydra/hydra.yaml +175 -0
  3. automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/.hydra/overrides.yaml +2 -0
  4. automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/benchmark_report.json +203 -0
  5. automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/cli.log +191 -0
  6. automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/error.log +0 -0
  7. automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/experiment_config.json +107 -0
  8. automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/generate_codecarbon.json +33 -0
  9. automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/prefill_codecarbon.json +33 -0
  10. automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/preprocess_codecarbon.json +33 -0
  11. automatic_speech_recognition/pyannote/speaker-diarization-3.1/2024-12-04-21-40-43/.hydra/config.yaml +94 -0
  12. automatic_speech_recognition/pyannote/speaker-diarization-3.1/2024-12-04-21-40-43/.hydra/hydra.yaml +175 -0
  13. automatic_speech_recognition/pyannote/speaker-diarization-3.1/2024-12-04-21-40-43/.hydra/overrides.yaml +2 -0
  14. automatic_speech_recognition/pyannote/speaker-diarization-3.1/2024-12-04-21-40-43/cli.log +0 -0
  15. automatic_speech_recognition/pyannote/speaker-diarization-3.1/2024-12-04-21-40-43/error.log +7 -0
  16. sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/.hydra/config.yaml +94 -0
  17. sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/.hydra/hydra.yaml +175 -0
  18. sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/.hydra/overrides.yaml +2 -0
  19. sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/benchmark_report.json +107 -0
  20. sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/cli.log +113 -0
  21. sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/error.log +170 -0
  22. sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/experiment_config.json +107 -0
  23. sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/forward_codecarbon.json +33 -0
  24. sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/preprocess_codecarbon.json +33 -0
  25. sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/.hydra/config.yaml +94 -0
  26. sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/.hydra/hydra.yaml +175 -0
  27. sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/.hydra/overrides.yaml +2 -0
  28. sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/benchmark_report.json +107 -0
  29. sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/cli.log +113 -0
  30. sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/error.log +178 -0
  31. sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/experiment_config.json +107 -0
  32. sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/forward_codecarbon.json +33 -0
  33. sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/preprocess_codecarbon.json +33 -0
  34. text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52/.hydra/config.yaml +96 -0
  35. text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52/.hydra/hydra.yaml +175 -0
  36. text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52/.hydra/overrides.yaml +2 -0
  37. text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52/cli.log +0 -0
  38. text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52/error.log +7 -0
automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/.hydra/config.yaml ADDED
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+ backend:
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+ name: pytorch
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+ version: 2.4.0
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+ _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
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+ task: automatic-speech-recognition
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+ model: openai/whisper-small
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+ processor: openai/whisper-small
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+ library: null
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+ device: cuda
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+ device_ids: '0'
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+ seed: 42
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+ inter_op_num_threads: null
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+ intra_op_num_threads: null
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+ hub_kwargs: {}
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+ no_weights: true
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+ device_map: null
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+ torch_dtype: null
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+ amp_autocast: false
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+ amp_dtype: null
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+ eval_mode: true
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+ to_bettertransformer: false
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+ low_cpu_mem_usage: null
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+ attn_implementation: null
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+ cache_implementation: null
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+ torch_compile: false
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+ torch_compile_config: {}
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+ quantization_scheme: null
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+ quantization_config: {}
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+ deepspeed_inference: false
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+ deepspeed_inference_config: {}
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+ peft_type: null
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+ peft_config: {}
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+ launcher:
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+ name: process
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+ _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
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+ device_isolation: true
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+ device_isolation_action: warn
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+ start_method: spawn
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+ benchmark:
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+ name: energy_star
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+ _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
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+ dataset_name: EnergyStarAI/ASR
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+ dataset_config: ''
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+ dataset_split: train
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+ num_samples: 1000
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+ input_shapes:
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+ batch_size: 1
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+ text_column_name: text
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+ truncation: true
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+ max_length: -1
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+ dataset_prefix1: ''
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+ dataset_prefix2: ''
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+ t5_task: ''
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+ image_column_name: image
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+ resize: false
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+ question_column_name: question
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+ context_column_name: context
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+ sentence1_column_name: sentence1
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+ sentence2_column_name: sentence2
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+ audio_column_name: audio
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+ iterations: 10
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+ warmup_runs: 10
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+ energy: true
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+ forward_kwargs: {}
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+ generate_kwargs: {}
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+ call_kwargs: {}
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+ experiment_name: automatic_speech_recognition
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+ environment:
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+ cpu: ' AMD EPYC 7R32'
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+ cpu_count: 48
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+ cpu_ram_mb: 200472.73984
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+ system: Linux
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+ machine: x86_64
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+ platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
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+ processor: x86_64
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+ python_version: 3.9.20
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+ gpu:
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+ - NVIDIA A10G
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+ gpu_count: 1
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+ gpu_vram_mb: 24146608128
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+ optimum_benchmark_version: 0.2.0
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+ optimum_benchmark_commit: null
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+ transformers_version: 4.44.0
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+ transformers_commit: null
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+ accelerate_version: 0.33.0
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+ accelerate_commit: null
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+ diffusers_version: 0.30.0
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+ diffusers_commit: null
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+ optimum_version: null
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+ optimum_commit: null
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+ timm_version: null
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+ timm_commit: null
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+ peft_version: null
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+ peft_commit: null
automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/.hydra/hydra.yaml ADDED
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+ hydra:
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+ run:
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+ dir: /runs/automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58
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+ sweep:
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+ subdir: ${hydra.job.num}
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+ launcher:
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+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
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+ max_batch_size: null
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+ params: null
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+ help:
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+ app_name: ${hydra.job.name}
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+ header: '${hydra.help.app_name} is powered by Hydra.
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+
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+ '
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+ footer: 'Powered by Hydra (https://hydra.cc)
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+
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+ Use --hydra-help to view Hydra specific help
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+
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+ '
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+ template: '${hydra.help.header}
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+
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+ == Configuration groups ==
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+
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+ Compose your configuration from those groups (group=option)
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+
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+
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+ $APP_CONFIG_GROUPS
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+
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+
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+ == Config ==
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+
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+ Override anything in the config (foo.bar=value)
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+
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+
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+ $CONFIG
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+
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+
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+ ${hydra.help.footer}
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+
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+ '
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+ hydra_help:
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+ template: 'Hydra (${hydra.runtime.version})
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+
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+ See https://hydra.cc for more info.
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+
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+
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+ == Flags ==
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+
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+ $FLAGS_HELP
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+
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+
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+ == Configuration groups ==
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+
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+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
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+ to command line)
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+
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+
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+ $HYDRA_CONFIG_GROUPS
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+
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+
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+ Use ''--cfg hydra'' to Show the Hydra config.
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+
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+ '
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+ hydra_help: ???
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+ hydra_logging:
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+ version: 1
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+ formatters:
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+ (): colorlog.ColoredFormatter
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+ job_logging:
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+ version: 1
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+ formatters:
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+ simple:
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+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
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+ colorlog:
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+ (): colorlog.ColoredFormatter
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+ format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
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+ - %(message)s'
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+ log_colors:
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+ DEBUG: purple
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+ WARNING: yellow
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+ CRITICAL: red
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+ handlers:
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+ console:
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+ class: logging.StreamHandler
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+ formatter: colorlog
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+ stream: ext://sys.stdout
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+ file:
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+ class: logging.FileHandler
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+ formatter: simple
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+ filename: ${hydra.job.name}.log
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+ root:
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+ level: INFO
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+ handlers:
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+ - console
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+ - file
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+ disable_existing_loggers: false
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+ env: {}
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+ mode: RUN
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+ searchpath: []
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+ callbacks: {}
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+ output_subdir: .hydra
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+ overrides:
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+ hydra:
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+ - hydra.run.dir=/runs/automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58
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+ - hydra.mode=RUN
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+ task:
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+ - backend.model=openai/whisper-small
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+ - backend.processor=openai/whisper-small
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+ job:
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+ name: cli
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+ chdir: true
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+ override_dirname: backend.model=openai/whisper-small,backend.processor=openai/whisper-small
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+ id: ???
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+ num: ???
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+ config_name: automatic_speech_recognition
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+ env_set:
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+ env_copy: []
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+ version_base: '1.3'
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+ cwd: /
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+ config_sources:
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+ - path: hydra.conf
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+ schema: pkg
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+ provider: hydra
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+ - path: optimum_benchmark
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+ schema: pkg
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+ provider: main
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+ - path: hydra_plugins.hydra_colorlog.conf
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+ schema: pkg
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+ provider: hydra-colorlog
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+ - path: /optimum-benchmark/examples/energy_star
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+ schema: file
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+ provider: command-line
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+ - path: ''
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+ schema: structured
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+ provider: schema
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+ output_dir: /runs/automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58
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+ choices:
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+ hydra/env: default
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+ hydra/callbacks: null
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+ hydra/job_logging: colorlog
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+ hydra/hydra_logging: colorlog
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+ hydra/hydra_help: default
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+ hydra/help: default
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+ hydra/sweeper: basic
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+ hydra/launcher: basic
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+ hydra/output: default
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+ verbose: false
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+ - backend.model=openai/whisper-small
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+ - backend.processor=openai/whisper-small
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+ "per_token": {
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+ }
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+ }
automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/cli.log ADDED
@@ -0,0 +1,191 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2024-12-04 21:42:01,673][launcher][INFO] - ََAllocating process launcher
2
+ [2024-12-04 21:42:01,673][process][INFO] - + Setting multiprocessing start method to spawn.
3
+ [2024-12-04 21:42:01,684][device-isolation][INFO] - + Launched device(s) isolation process 491
4
+ [2024-12-04 21:42:01,685][device-isolation][INFO] - + Isolating device(s) [0]
5
+ [2024-12-04 21:42:01,690][process][INFO] - + Launched benchmark in isolated process 492.
6
+ [PROC-0][2024-12-04 21:42:04,460][datasets][INFO] - PyTorch version 2.4.0 available.
7
+ [PROC-0][2024-12-04 21:42:05,370][backend][INFO] - َAllocating pytorch backend
8
+ [PROC-0][2024-12-04 21:42:05,370][backend][INFO] - + Setting random seed to 42
9
+ [PROC-0][2024-12-04 21:42:06,829][pytorch][INFO] - + Using AutoModel class AutoModelForSpeechSeq2Seq
10
+ [PROC-0][2024-12-04 21:42:06,830][pytorch][INFO] - + Creating backend temporary directory
11
+ [PROC-0][2024-12-04 21:42:06,830][pytorch][INFO] - + Loading model with random weights
12
+ [PROC-0][2024-12-04 21:42:06,830][pytorch][INFO] - + Creating no weights model
13
+ [PROC-0][2024-12-04 21:42:06,830][pytorch][INFO] - + Creating no weights model directory
14
+ [PROC-0][2024-12-04 21:42:06,830][pytorch][INFO] - + Creating no weights model state dict
15
+ [PROC-0][2024-12-04 21:42:06,832][pytorch][INFO] - + Saving no weights model safetensors
16
+ [PROC-0][2024-12-04 21:42:06,833][pytorch][INFO] - + Saving no weights model pretrained config
17
+ [PROC-0][2024-12-04 21:42:06,834][pytorch][INFO] - + Loading no weights AutoModel
18
+ [PROC-0][2024-12-04 21:42:06,834][pytorch][INFO] - + Loading model directly on device: cuda
19
+ [PROC-0][2024-12-04 21:42:07,049][pytorch][INFO] - + Turning on model's eval mode
20
+ [PROC-0][2024-12-04 21:42:07,056][benchmark][INFO] - Allocating energy_star benchmark
21
+ [PROC-0][2024-12-04 21:42:07,056][energy_star][INFO] - + Loading raw dataset
22
+ [PROC-0][2024-12-04 21:42:12,960][energy_star][INFO] - + Updating Text Generation kwargs with default values
23
+ [PROC-0][2024-12-04 21:42:12,960][energy_star][INFO] - + Initializing Text Generation report
24
+ [PROC-0][2024-12-04 21:42:12,961][energy][INFO] - + Tracking GPU energy on devices [0]
25
+ [PROC-0][2024-12-04 21:42:17,167][energy_star][INFO] - + Preprocessing dataset
26
+ [PROC-0][2024-12-04 21:42:32,399][energy][INFO] - + Saving codecarbon emission data to preprocess_codecarbon.json
27
+ [PROC-0][2024-12-04 21:42:32,399][energy_star][INFO] - + Preparing backend for Inference
28
+ [PROC-0][2024-12-04 21:42:32,400][energy_star][INFO] - + Initialising dataloader
29
+ [PROC-0][2024-12-04 21:42:32,400][energy_star][INFO] - + Warming up backend for Inference
30
+ [PROC-0][2024-12-04 21:42:33,923][energy_star][INFO] - + Additional warmup for Text Generation
31
+ [PROC-0][2024-12-04 21:42:34,768][energy_star][INFO] - + Running Text Generation energy tracking for 10 iterations
32
+ [PROC-0][2024-12-04 21:42:34,768][energy_star][INFO] - + Prefill iteration 1/10
33
+ [PROC-0][2024-12-04 21:44:14,704][energy][INFO] - + Saving codecarbon emission data to prefill_codecarbon.json
34
+ [PROC-0][2024-12-04 21:44:14,704][energy_star][INFO] - + Prefill iteration 2/10
35
+ [PROC-0][2024-12-04 21:45:54,695][energy][INFO] - + Saving codecarbon emission data to prefill_codecarbon.json
36
+ [PROC-0][2024-12-04 21:45:54,695][energy_star][INFO] - + Prefill iteration 3/10
37
+ [PROC-0][2024-12-04 21:47:34,694][energy][INFO] - + Saving codecarbon emission data to prefill_codecarbon.json
38
+ [PROC-0][2024-12-04 21:47:34,694][energy_star][INFO] - + Prefill iteration 4/10
39
+ [PROC-0][2024-12-04 21:49:14,695][energy][INFO] - + Saving codecarbon emission data to prefill_codecarbon.json
40
+ [PROC-0][2024-12-04 21:49:14,695][energy_star][INFO] - + Prefill iteration 5/10
41
+ [PROC-0][2024-12-04 21:50:54,698][energy][INFO] - + Saving codecarbon emission data to prefill_codecarbon.json
42
+ [PROC-0][2024-12-04 21:50:54,698][energy_star][INFO] - + Prefill iteration 6/10
43
+ [PROC-0][2024-12-04 21:52:34,697][energy][INFO] - + Saving codecarbon emission data to prefill_codecarbon.json
44
+ [PROC-0][2024-12-04 21:52:34,697][energy_star][INFO] - + Prefill iteration 7/10
45
+ [PROC-0][2024-12-04 21:54:14,695][energy][INFO] - + Saving codecarbon emission data to prefill_codecarbon.json
46
+ [PROC-0][2024-12-04 21:54:14,696][energy_star][INFO] - + Prefill iteration 8/10
47
+ [PROC-0][2024-12-04 21:55:54,694][energy][INFO] - + Saving codecarbon emission data to prefill_codecarbon.json
48
+ [PROC-0][2024-12-04 21:55:54,694][energy_star][INFO] - + Prefill iteration 9/10
49
+ [PROC-0][2024-12-04 21:57:34,694][energy][INFO] - + Saving codecarbon emission data to prefill_codecarbon.json
50
+ [PROC-0][2024-12-04 21:57:34,695][energy_star][INFO] - + Prefill iteration 10/10
51
+ [PROC-0][2024-12-04 21:59:14,798][energy][INFO] - + Saving codecarbon emission data to prefill_codecarbon.json
52
+ [PROC-0][2024-12-04 21:59:14,799][energy_star][INFO] - + Decoding iteration 1/10
53
+ [PROC-0][2024-12-04 22:15:06,041][energy][INFO] - + Saving codecarbon emission data to generate_codecarbon.json
54
+ [PROC-0][2024-12-04 22:15:06,041][energy_star][INFO] - + Decoding iteration 2/10
55
+ [PROC-0][2024-12-04 22:30:51,624][energy][INFO] - + Saving codecarbon emission data to generate_codecarbon.json
56
+ [PROC-0][2024-12-04 22:30:51,624][energy_star][INFO] - + Decoding iteration 3/10
57
+ [PROC-0][2024-12-04 22:46:36,438][energy][INFO] - + Saving codecarbon emission data to generate_codecarbon.json
58
+ [PROC-0][2024-12-04 22:46:36,439][energy_star][INFO] - + Decoding iteration 4/10
59
+ [PROC-0][2024-12-04 23:02:21,205][energy][INFO] - + Saving codecarbon emission data to generate_codecarbon.json
60
+ [PROC-0][2024-12-04 23:02:21,206][energy_star][INFO] - + Decoding iteration 5/10
61
+ [PROC-0][2024-12-04 23:18:07,862][energy][INFO] - + Saving codecarbon emission data to generate_codecarbon.json
62
+ [PROC-0][2024-12-04 23:18:07,862][energy_star][INFO] - + Decoding iteration 6/10
63
+ [PROC-0][2024-12-04 23:33:50,000][energy][INFO] - + Saving codecarbon emission data to generate_codecarbon.json
64
+ [PROC-0][2024-12-04 23:33:50,000][energy_star][INFO] - + Decoding iteration 7/10
65
+ [PROC-0][2024-12-04 23:49:34,542][energy][INFO] - + Saving codecarbon emission data to generate_codecarbon.json
66
+ [PROC-0][2024-12-04 23:49:34,542][energy_star][INFO] - + Decoding iteration 8/10
67
+ [PROC-0][2024-12-05 00:05:20,569][energy][INFO] - + Saving codecarbon emission data to generate_codecarbon.json
68
+ [PROC-0][2024-12-05 00:05:20,569][energy_star][INFO] - + Decoding iteration 9/10
69
+ [PROC-0][2024-12-05 00:21:06,577][energy][INFO] - + Saving codecarbon emission data to generate_codecarbon.json
70
+ [PROC-0][2024-12-05 00:21:06,577][energy_star][INFO] - + Decoding iteration 10/10
71
+ [PROC-0][2024-12-05 00:36:50,431][energy][INFO] - + Saving codecarbon emission data to generate_codecarbon.json
72
+ [PROC-0][2024-12-05 00:36:50,432][energy][INFO] - + prefill energy consumption:
73
+ [PROC-0][2024-12-05 00:36:50,432][energy][INFO] - + CPU: 0.001063 (kWh)
74
+ [PROC-0][2024-12-05 00:36:50,432][energy][INFO] - + GPU: 0.004004 (kWh)
75
+ [PROC-0][2024-12-05 00:36:50,432][energy][INFO] - + RAM: 0.000048 (kWh)
76
+ [PROC-0][2024-12-05 00:36:50,432][energy][INFO] - + total: 0.005114 (kWh)
77
+ [PROC-0][2024-12-05 00:36:50,432][energy][INFO] - + prefill_iteration_1 energy consumption:
78
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + CPU: 0.001180 (kWh)
79
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + GPU: 0.004326 (kWh)
80
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + RAM: 0.000053 (kWh)
81
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + total: 0.005559 (kWh)
82
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + prefill_iteration_2 energy consumption:
83
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + CPU: 0.001180 (kWh)
84
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + GPU: 0.004583 (kWh)
85
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + RAM: 0.000053 (kWh)
86
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + total: 0.005816 (kWh)
87
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + prefill_iteration_3 energy consumption:
88
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + CPU: 0.001181 (kWh)
89
+ [PROC-0][2024-12-05 00:36:50,433][energy][INFO] - + GPU: 0.004499 (kWh)
90
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + RAM: 0.000053 (kWh)
91
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + total: 0.005733 (kWh)
92
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + prefill_iteration_4 energy consumption:
93
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + CPU: 0.001181 (kWh)
94
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + GPU: 0.004336 (kWh)
95
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + RAM: 0.000053 (kWh)
96
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + total: 0.005569 (kWh)
97
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + prefill_iteration_5 energy consumption:
98
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + CPU: 0.001181 (kWh)
99
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + GPU: 0.004438 (kWh)
100
+ [PROC-0][2024-12-05 00:36:50,434][energy][INFO] - + RAM: 0.000053 (kWh)
101
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + total: 0.005672 (kWh)
102
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + prefill_iteration_6 energy consumption:
103
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + CPU: 0.001181 (kWh)
104
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + GPU: 0.004447 (kWh)
105
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + RAM: 0.000053 (kWh)
106
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + total: 0.005681 (kWh)
107
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + prefill_iteration_7 energy consumption:
108
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + CPU: 0.000000 (kWh)
109
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + GPU: 0.000000 (kWh)
110
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + RAM: 0.000000 (kWh)
111
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + total: 0.000000 (kWh)
112
+ [PROC-0][2024-12-05 00:36:50,435][energy][INFO] - + prefill_iteration_8 energy consumption:
113
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + CPU: 0.001181 (kWh)
114
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + GPU: 0.004500 (kWh)
115
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + RAM: 0.000053 (kWh)
116
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + total: 0.005734 (kWh)
117
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + prefill_iteration_9 energy consumption:
118
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + CPU: 0.001181 (kWh)
119
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + GPU: 0.004578 (kWh)
120
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + RAM: 0.000053 (kWh)
121
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + total: 0.005811 (kWh)
122
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + prefill_iteration_10 energy consumption:
123
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + CPU: 0.001182 (kWh)
124
+ [PROC-0][2024-12-05 00:36:50,436][energy][INFO] - + GPU: 0.004334 (kWh)
125
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + RAM: 0.000053 (kWh)
126
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + total: 0.005569 (kWh)
127
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + decode energy consumption:
128
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + CPU: 0.008983 (kWh)
129
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + GPU: 0.020038 (kWh)
130
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + RAM: 0.000403 (kWh)
131
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + total: 0.029424 (kWh)
132
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + decode_iteration_1 energy consumption:
133
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + CPU: 0.010050 (kWh)
134
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + GPU: 0.022509 (kWh)
135
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + RAM: 0.000451 (kWh)
136
+ [PROC-0][2024-12-05 00:36:50,437][energy][INFO] - + total: 0.033010 (kWh)
137
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + decode_iteration_2 energy consumption:
138
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + CPU: 0.009983 (kWh)
139
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + GPU: 0.022075 (kWh)
140
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + RAM: 0.000448 (kWh)
141
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + total: 0.032506 (kWh)
142
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + decode_iteration_3 energy consumption:
143
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + CPU: 0.009974 (kWh)
144
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + GPU: 0.022207 (kWh)
145
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + RAM: 0.000447 (kWh)
146
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + total: 0.032627 (kWh)
147
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + decode_iteration_4 energy consumption:
148
+ [PROC-0][2024-12-05 00:36:50,438][energy][INFO] - + CPU: 0.009973 (kWh)
149
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + GPU: 0.022316 (kWh)
150
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + RAM: 0.000447 (kWh)
151
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + total: 0.032737 (kWh)
152
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + decode_iteration_5 energy consumption:
153
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + CPU: -0.001181 (kWh)
154
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + GPU: -0.004438 (kWh)
155
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + RAM: -0.000053 (kWh)
156
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + total: -0.005672 (kWh)
157
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + decode_iteration_6 energy consumption:
158
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + CPU: 0.009942 (kWh)
159
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + GPU: 0.022229 (kWh)
160
+ [PROC-0][2024-12-05 00:36:50,439][energy][INFO] - + RAM: 0.000446 (kWh)
161
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + total: 0.032617 (kWh)
162
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + decode_iteration_7 energy consumption:
163
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + CPU: 0.011151 (kWh)
164
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + GPU: 0.026727 (kWh)
165
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + RAM: 0.000500 (kWh)
166
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + total: 0.038378 (kWh)
167
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + decode_iteration_8 energy consumption:
168
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + CPU: 0.009988 (kWh)
169
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + GPU: 0.022179 (kWh)
170
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + RAM: 0.000448 (kWh)
171
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + total: 0.032615 (kWh)
172
+ [PROC-0][2024-12-05 00:36:50,440][energy][INFO] - + decode_iteration_9 energy consumption:
173
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + CPU: 0.009988 (kWh)
174
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + GPU: 0.022162 (kWh)
175
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + RAM: 0.000448 (kWh)
176
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + total: 0.032597 (kWh)
177
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + decode_iteration_10 energy consumption:
178
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + CPU: 0.009961 (kWh)
179
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + GPU: 0.022418 (kWh)
180
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + RAM: 0.000447 (kWh)
181
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + total: 0.032825 (kWh)
182
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + preprocess energy consumption:
183
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + CPU: 0.000180 (kWh)
184
+ [PROC-0][2024-12-05 00:36:50,441][energy][INFO] - + GPU: 0.000276 (kWh)
185
+ [PROC-0][2024-12-05 00:36:50,442][energy][INFO] - + RAM: 0.000009 (kWh)
186
+ [PROC-0][2024-12-05 00:36:50,442][energy][INFO] - + total: 0.000465 (kWh)
187
+ [PROC-0][2024-12-05 00:36:50,442][energy][INFO] - + prefill energy efficiency: 195526.556644 (tokens/kWh)
188
+ [PROC-0][2024-12-05 00:36:50,442][energy][INFO] - + decode energy efficiency: 3364586.284552 (tokens/kWh)
189
+ [PROC-0][2024-12-05 00:36:50,442][energy][INFO] - + preprocess energy efficiency: 2150692.219800 (samples/kWh)
190
+ [2024-12-05 00:36:51,389][device-isolation][INFO] - + Closing device(s) isolation process...
191
+ [2024-12-05 00:36:51,437][datasets][INFO] - PyTorch version 2.4.0 available.
automatic_speech_recognition/openai/whisper-small/2024-12-04-21-41-58/error.log ADDED
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+
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+ provider: main
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+ - path: hydra_plugins.hydra_colorlog.conf
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+ hydra/callbacks: null
168
+ hydra/job_logging: colorlog
169
+ hydra/hydra_logging: colorlog
170
+ hydra/hydra_help: default
171
+ hydra/help: default
172
+ hydra/sweeper: basic
173
+ hydra/launcher: basic
174
+ hydra/output: default
175
+ verbose: false
automatic_speech_recognition/pyannote/speaker-diarization-3.1/2024-12-04-21-40-43/.hydra/overrides.yaml ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ - backend.model=pyannote/speaker-diarization-3.1
2
+ - backend.processor=pyannote/speaker-diarization-3.1
automatic_speech_recognition/pyannote/speaker-diarization-3.1/2024-12-04-21-40-43/cli.log ADDED
File without changes
automatic_speech_recognition/pyannote/speaker-diarization-3.1/2024-12-04-21-40-43/error.log ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ Error executing job with overrides: ['backend.model=pyannote/speaker-diarization-3.1', 'backend.processor=pyannote/speaker-diarization-3.1']
2
+ Traceback (most recent call last):
3
+ File "/optimum-benchmark/optimum_benchmark/cli.py", line 62, in benchmark_cli
4
+ experiment_config: ExperimentConfig = OmegaConf.to_object(experiment_config)
5
+ ValueError: `library` must be either `transformers`, `diffusers` or `timm`, but got pyannote-audio
6
+
7
+ Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/.hydra/config.yaml ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ backend:
2
+ name: pytorch
3
+ version: 2.4.0
4
+ _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
5
+ task: sentence-similarity
6
+ model: sentence-transformers/all-MiniLM-L12-v2
7
+ processor: sentence-transformers/all-MiniLM-L12-v2
8
+ library: transformers
9
+ device: cuda
10
+ device_ids: '0'
11
+ seed: 42
12
+ inter_op_num_threads: null
13
+ intra_op_num_threads: null
14
+ hub_kwargs: {}
15
+ no_weights: true
16
+ device_map: null
17
+ torch_dtype: null
18
+ amp_autocast: false
19
+ amp_dtype: null
20
+ eval_mode: true
21
+ to_bettertransformer: false
22
+ low_cpu_mem_usage: null
23
+ attn_implementation: null
24
+ cache_implementation: null
25
+ torch_compile: false
26
+ torch_compile_config: {}
27
+ quantization_scheme: null
28
+ quantization_config: {}
29
+ deepspeed_inference: false
30
+ deepspeed_inference_config: {}
31
+ peft_type: null
32
+ peft_config: {}
33
+ launcher:
34
+ name: process
35
+ _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
36
+ device_isolation: true
37
+ device_isolation_action: warn
38
+ start_method: spawn
39
+ benchmark:
40
+ name: energy_star
41
+ _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
42
+ dataset_name: EnergyStarAI/sentence_similarity
43
+ dataset_config: ''
44
+ dataset_split: train
45
+ num_samples: 1000
46
+ input_shapes:
47
+ batch_size: 1
48
+ text_column_name: text
49
+ truncation: true
50
+ max_length: -1
51
+ dataset_prefix1: ''
52
+ dataset_prefix2: ''
53
+ t5_task: ''
54
+ image_column_name: image
55
+ resize: false
56
+ question_column_name: question
57
+ context_column_name: context
58
+ sentence1_column_name: sentence1
59
+ sentence2_column_name: sentence2
60
+ audio_column_name: audio
61
+ iterations: 10
62
+ warmup_runs: 10
63
+ energy: true
64
+ forward_kwargs: {}
65
+ generate_kwargs: {}
66
+ call_kwargs: {}
67
+ experiment_name: sentence_similarity_udever-bloom-7b1
68
+ environment:
69
+ cpu: ' AMD EPYC 7R32'
70
+ cpu_count: 48
71
+ cpu_ram_mb: 200472.73984
72
+ system: Linux
73
+ machine: x86_64
74
+ platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
75
+ processor: x86_64
76
+ python_version: 3.9.20
77
+ gpu:
78
+ - NVIDIA A10G
79
+ gpu_count: 1
80
+ gpu_vram_mb: 24146608128
81
+ optimum_benchmark_version: 0.2.0
82
+ optimum_benchmark_commit: null
83
+ transformers_version: 4.44.0
84
+ transformers_commit: null
85
+ accelerate_version: 0.33.0
86
+ accelerate_commit: null
87
+ diffusers_version: 0.30.0
88
+ diffusers_commit: null
89
+ optimum_version: null
90
+ optimum_commit: null
91
+ timm_version: null
92
+ timm_commit: null
93
+ peft_version: null
94
+ peft_commit: null
sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/.hydra/hydra.yaml ADDED
@@ -0,0 +1,175 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ hydra:
2
+ run:
3
+ dir: /runs/sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55
4
+ sweep:
5
+ dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
6
+ subdir: ${hydra.job.num}
7
+ launcher:
8
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
9
+ sweeper:
10
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
11
+ max_batch_size: null
12
+ params: null
13
+ help:
14
+ app_name: ${hydra.job.name}
15
+ header: '${hydra.help.app_name} is powered by Hydra.
16
+
17
+ '
18
+ footer: 'Powered by Hydra (https://hydra.cc)
19
+
20
+ Use --hydra-help to view Hydra specific help
21
+
22
+ '
23
+ template: '${hydra.help.header}
24
+
25
+ == Configuration groups ==
26
+
27
+ Compose your configuration from those groups (group=option)
28
+
29
+
30
+ $APP_CONFIG_GROUPS
31
+
32
+
33
+ == Config ==
34
+
35
+ Override anything in the config (foo.bar=value)
36
+
37
+
38
+ $CONFIG
39
+
40
+
41
+ ${hydra.help.footer}
42
+
43
+ '
44
+ hydra_help:
45
+ template: 'Hydra (${hydra.runtime.version})
46
+
47
+ See https://hydra.cc for more info.
48
+
49
+
50
+ == Flags ==
51
+
52
+ $FLAGS_HELP
53
+
54
+
55
+ == Configuration groups ==
56
+
57
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
58
+ to command line)
59
+
60
+
61
+ $HYDRA_CONFIG_GROUPS
62
+
63
+
64
+ Use ''--cfg hydra'' to Show the Hydra config.
65
+
66
+ '
67
+ hydra_help: ???
68
+ hydra_logging:
69
+ version: 1
70
+ formatters:
71
+ colorlog:
72
+ (): colorlog.ColoredFormatter
73
+ format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
74
+ handlers:
75
+ console:
76
+ class: logging.StreamHandler
77
+ formatter: colorlog
78
+ stream: ext://sys.stdout
79
+ root:
80
+ level: INFO
81
+ handlers:
82
+ - console
83
+ disable_existing_loggers: false
84
+ job_logging:
85
+ version: 1
86
+ formatters:
87
+ simple:
88
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
89
+ colorlog:
90
+ (): colorlog.ColoredFormatter
91
+ format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
92
+ - %(message)s'
93
+ log_colors:
94
+ DEBUG: purple
95
+ INFO: green
96
+ WARNING: yellow
97
+ ERROR: red
98
+ CRITICAL: red
99
+ handlers:
100
+ console:
101
+ class: logging.StreamHandler
102
+ formatter: colorlog
103
+ stream: ext://sys.stdout
104
+ file:
105
+ class: logging.FileHandler
106
+ formatter: simple
107
+ filename: ${hydra.job.name}.log
108
+ root:
109
+ level: INFO
110
+ handlers:
111
+ - console
112
+ - file
113
+ disable_existing_loggers: false
114
+ env: {}
115
+ mode: RUN
116
+ searchpath: []
117
+ callbacks: {}
118
+ output_subdir: .hydra
119
+ overrides:
120
+ hydra:
121
+ - hydra.run.dir=/runs/sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55
122
+ - hydra.mode=RUN
123
+ task:
124
+ - backend.model=sentence-transformers/all-MiniLM-L12-v2
125
+ - backend.processor=sentence-transformers/all-MiniLM-L12-v2
126
+ job:
127
+ name: cli
128
+ chdir: true
129
+ override_dirname: backend.model=sentence-transformers/all-MiniLM-L12-v2,backend.processor=sentence-transformers/all-MiniLM-L12-v2
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+ id: ???
131
+ num: ???
132
+ config_name: sentence_similarity
133
+ env_set:
134
+ OVERRIDE_BENCHMARKS: '1'
135
+ env_copy: []
136
+ config:
137
+ override_dirname:
138
+ kv_sep: '='
139
+ item_sep: ','
140
+ exclude_keys: []
141
+ runtime:
142
+ version: 1.3.2
143
+ version_base: '1.3'
144
+ cwd: /
145
+ config_sources:
146
+ - path: hydra.conf
147
+ schema: pkg
148
+ provider: hydra
149
+ - path: optimum_benchmark
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+ schema: pkg
151
+ provider: main
152
+ - path: hydra_plugins.hydra_colorlog.conf
153
+ schema: pkg
154
+ provider: hydra-colorlog
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+ - path: /optimum-benchmark/examples/energy_star
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+ schema: file
157
+ provider: command-line
158
+ - path: ''
159
+ schema: structured
160
+ provider: schema
161
+ output_dir: /runs/sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55
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+ choices:
163
+ benchmark: energy_star
164
+ launcher: process
165
+ backend: pytorch
166
+ hydra/env: default
167
+ hydra/callbacks: null
168
+ hydra/job_logging: colorlog
169
+ hydra/hydra_logging: colorlog
170
+ hydra/hydra_help: default
171
+ hydra/help: default
172
+ hydra/sweeper: basic
173
+ hydra/launcher: basic
174
+ hydra/output: default
175
+ verbose: false
sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/.hydra/overrides.yaml ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ - backend.model=sentence-transformers/all-MiniLM-L12-v2
2
+ - backend.processor=sentence-transformers/all-MiniLM-L12-v2
sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/benchmark_report.json ADDED
@@ -0,0 +1,107 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/cli.log ADDED
@@ -0,0 +1,113 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2024-12-05 00:36:58,469][launcher][INFO] - ََAllocating process launcher
2
+ [2024-12-05 00:36:58,469][process][INFO] - + Setting multiprocessing start method to spawn.
3
+ [2024-12-05 00:36:58,482][device-isolation][INFO] - + Launched device(s) isolation process 822
4
+ [2024-12-05 00:36:58,482][device-isolation][INFO] - + Isolating device(s) [0]
5
+ [2024-12-05 00:36:58,488][process][INFO] - + Launched benchmark in isolated process 823.
6
+ [PROC-0][2024-12-05 00:37:01,111][datasets][INFO] - PyTorch version 2.4.0 available.
7
+ [PROC-0][2024-12-05 00:37:02,059][backend][INFO] - َAllocating pytorch backend
8
+ [PROC-0][2024-12-05 00:37:02,059][backend][INFO] - + Setting random seed to 42
9
+ [PROC-0][2024-12-05 00:37:02,694][pytorch][INFO] - + Using AutoModel class AutoModel
10
+ [PROC-0][2024-12-05 00:37:02,694][pytorch][INFO] - + Creating backend temporary directory
11
+ [PROC-0][2024-12-05 00:37:02,694][pytorch][INFO] - + Loading model with random weights
12
+ [PROC-0][2024-12-05 00:37:02,694][pytorch][INFO] - + Creating no weights model
13
+ [PROC-0][2024-12-05 00:37:02,694][pytorch][INFO] - + Creating no weights model directory
14
+ [PROC-0][2024-12-05 00:37:02,694][pytorch][INFO] - + Creating no weights model state dict
15
+ [PROC-0][2024-12-05 00:37:02,696][pytorch][INFO] - + Saving no weights model safetensors
16
+ [PROC-0][2024-12-05 00:37:02,697][pytorch][INFO] - + Saving no weights model pretrained config
17
+ [PROC-0][2024-12-05 00:37:02,698][pytorch][INFO] - + Loading no weights AutoModel
18
+ [PROC-0][2024-12-05 00:37:02,698][pytorch][INFO] - + Loading model directly on device: cuda
19
+ [PROC-0][2024-12-05 00:37:02,999][pytorch][INFO] - + Turning on model's eval mode
20
+ [PROC-0][2024-12-05 00:37:03,005][benchmark][INFO] - Allocating energy_star benchmark
21
+ [PROC-0][2024-12-05 00:37:03,005][energy_star][INFO] - + Loading raw dataset
22
+ [PROC-0][2024-12-05 00:37:04,014][energy_star][INFO] - + Initializing Inference report
23
+ [PROC-0][2024-12-05 00:37:04,015][energy][INFO] - + Tracking GPU energy on devices [0]
24
+ [PROC-0][2024-12-05 00:37:08,201][energy_star][INFO] - + Preprocessing dataset
25
+ [PROC-0][2024-12-05 00:37:08,367][energy][INFO] - + Saving codecarbon emission data to preprocess_codecarbon.json
26
+ [PROC-0][2024-12-05 00:37:08,367][energy_star][INFO] - + Preparing backend for Inference
27
+ [PROC-0][2024-12-05 00:37:08,368][energy_star][INFO] - + Initialising dataloader
28
+ [PROC-0][2024-12-05 00:37:08,368][energy_star][INFO] - + Warming up backend for Inference
29
+ [PROC-0][2024-12-05 00:37:09,127][energy_star][INFO] - + Running Inference energy tracking for 10 iterations
30
+ [PROC-0][2024-12-05 00:37:09,127][energy_star][INFO] - + Iteration 1/10
31
+ [PROC-0][2024-12-05 00:37:14,755][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
32
+ [PROC-0][2024-12-05 00:37:14,755][energy_star][INFO] - + Iteration 2/10
33
+ [PROC-0][2024-12-05 00:37:20,218][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
34
+ [PROC-0][2024-12-05 00:37:20,219][energy_star][INFO] - + Iteration 3/10
35
+ [PROC-0][2024-12-05 00:37:25,658][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
36
+ [PROC-0][2024-12-05 00:37:25,658][energy_star][INFO] - + Iteration 4/10
37
+ [PROC-0][2024-12-05 00:37:31,035][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
38
+ [PROC-0][2024-12-05 00:37:31,035][energy_star][INFO] - + Iteration 5/10
39
+ [PROC-0][2024-12-05 00:37:36,396][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
40
+ [PROC-0][2024-12-05 00:37:36,396][energy_star][INFO] - + Iteration 6/10
41
+ [PROC-0][2024-12-05 00:37:41,785][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
42
+ [PROC-0][2024-12-05 00:37:41,785][energy_star][INFO] - + Iteration 7/10
43
+ [PROC-0][2024-12-05 00:37:47,170][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
44
+ [PROC-0][2024-12-05 00:37:47,170][energy_star][INFO] - + Iteration 8/10
45
+ [PROC-0][2024-12-05 00:37:52,652][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
46
+ [PROC-0][2024-12-05 00:37:52,652][energy_star][INFO] - + Iteration 9/10
47
+ [PROC-0][2024-12-05 00:37:58,250][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
48
+ [PROC-0][2024-12-05 00:37:58,250][energy_star][INFO] - + Iteration 10/10
49
+ [PROC-0][2024-12-05 00:38:03,944][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
50
+ [PROC-0][2024-12-05 00:38:03,945][energy][INFO] - + forward energy consumption:
51
+ [PROC-0][2024-12-05 00:38:03,945][energy][INFO] - + CPU: 0.000058 (kWh)
52
+ [PROC-0][2024-12-05 00:38:03,945][energy][INFO] - + GPU: 0.000111 (kWh)
53
+ [PROC-0][2024-12-05 00:38:03,945][energy][INFO] - + RAM: 0.000000 (kWh)
54
+ [PROC-0][2024-12-05 00:38:03,945][energy][INFO] - + total: 0.000169 (kWh)
55
+ [PROC-0][2024-12-05 00:38:03,945][energy][INFO] - + forward_iteration_1 energy consumption:
56
+ [PROC-0][2024-12-05 00:38:03,945][energy][INFO] - + CPU: 0.000066 (kWh)
57
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + GPU: 0.000126 (kWh)
58
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + RAM: 0.000001 (kWh)
59
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + total: 0.000193 (kWh)
60
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + forward_iteration_2 energy consumption:
61
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + CPU: 0.000064 (kWh)
62
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + GPU: 0.000121 (kWh)
63
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + RAM: 0.000001 (kWh)
64
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + total: 0.000186 (kWh)
65
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + forward_iteration_3 energy consumption:
66
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + CPU: 0.000064 (kWh)
67
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + GPU: 0.000123 (kWh)
68
+ [PROC-0][2024-12-05 00:38:03,946][energy][INFO] - + RAM: 0.000001 (kWh)
69
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + total: 0.000188 (kWh)
70
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + forward_iteration_4 energy consumption:
71
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + CPU: 0.000063 (kWh)
72
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + GPU: 0.000119 (kWh)
73
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + RAM: 0.000001 (kWh)
74
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + total: 0.000183 (kWh)
75
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + forward_iteration_5 energy consumption:
76
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + CPU: 0.000063 (kWh)
77
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + GPU: 0.000121 (kWh)
78
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + RAM: 0.000001 (kWh)
79
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + total: 0.000185 (kWh)
80
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + forward_iteration_6 energy consumption:
81
+ [PROC-0][2024-12-05 00:38:03,947][energy][INFO] - + CPU: 0.000064 (kWh)
82
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + GPU: 0.000121 (kWh)
83
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + RAM: 0.000001 (kWh)
84
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + total: 0.000185 (kWh)
85
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + forward_iteration_7 energy consumption:
86
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + CPU: 0.000000 (kWh)
87
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + GPU: 0.000000 (kWh)
88
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + RAM: 0.000000 (kWh)
89
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + total: 0.000000 (kWh)
90
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + forward_iteration_8 energy consumption:
91
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + CPU: 0.000065 (kWh)
92
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + GPU: 0.000123 (kWh)
93
+ [PROC-0][2024-12-05 00:38:03,948][energy][INFO] - + RAM: 0.000001 (kWh)
94
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + total: 0.000188 (kWh)
95
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + forward_iteration_9 energy consumption:
96
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + CPU: 0.000066 (kWh)
97
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + GPU: 0.000125 (kWh)
98
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + RAM: 0.000001 (kWh)
99
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + total: 0.000191 (kWh)
100
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + forward_iteration_10 energy consumption:
101
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + CPU: 0.000067 (kWh)
102
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + GPU: 0.000127 (kWh)
103
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + RAM: 0.000001 (kWh)
104
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + total: 0.000194 (kWh)
105
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + preprocess energy consumption:
106
+ [PROC-0][2024-12-05 00:38:03,949][energy][INFO] - + CPU: 0.000002 (kWh)
107
+ [PROC-0][2024-12-05 00:38:03,950][energy][INFO] - + GPU: 0.000004 (kWh)
108
+ [PROC-0][2024-12-05 00:38:03,950][energy][INFO] - + RAM: 0.000000 (kWh)
109
+ [PROC-0][2024-12-05 00:38:03,950][energy][INFO] - + total: 0.000006 (kWh)
110
+ [PROC-0][2024-12-05 00:38:03,950][energy][INFO] - + forward energy efficiency: 5904990.958539 (samples/kWh)
111
+ [PROC-0][2024-12-05 00:38:03,950][energy][INFO] - + preprocess energy efficiency: 178114553.876209 (samples/kWh)
112
+ [2024-12-05 00:38:04,604][device-isolation][INFO] - + Closing device(s) isolation process...
113
+ [2024-12-05 00:38:04,652][datasets][INFO] - PyTorch version 2.4.0 available.
sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/error.log ADDED
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1
+ /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
2
+ warnings.warn(
3
+ [codecarbon INFO @ 00:37:04] [setup] RAM Tracking...
4
+ [codecarbon INFO @ 00:37:04] [setup] GPU Tracking...
5
+ [codecarbon INFO @ 00:37:04] Tracking Nvidia GPU via pynvml
6
+ [codecarbon DEBUG @ 00:37:04] GPU available. Starting setup
7
+ [codecarbon INFO @ 00:37:04] [setup] CPU Tracking...
8
+ [codecarbon DEBUG @ 00:37:04] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
9
+ [codecarbon DEBUG @ 00:37:04] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
10
+ [codecarbon DEBUG @ 00:37:04] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
11
+ [codecarbon WARNING @ 00:37:04] No CPU tracking mode found. Falling back on CPU constant mode.
12
+ [codecarbon WARNING @ 00:37:05] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
13
+ [codecarbon INFO @ 00:37:05] CPU Model on constant consumption mode: AMD EPYC 7R32
14
+ [codecarbon INFO @ 00:37:05] >>> Tracker's metadata:
15
+ [codecarbon INFO @ 00:37:05] Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
16
+ [codecarbon INFO @ 00:37:05] Python version: 3.9.20
17
+ [codecarbon INFO @ 00:37:05] CodeCarbon version: 2.5.1
18
+ [codecarbon INFO @ 00:37:05] Available RAM : 186.705 GB
19
+ [codecarbon INFO @ 00:37:05] CPU count: 48
20
+ [codecarbon INFO @ 00:37:05] CPU model: AMD EPYC 7R32
21
+ [codecarbon INFO @ 00:37:05] GPU count: 1
22
+ [codecarbon INFO @ 00:37:05] GPU model: 1 x NVIDIA A10G
23
+ [codecarbon DEBUG @ 00:37:06] Not running on AWS
24
+ [codecarbon DEBUG @ 00:37:07] Not running on Azure
25
+ [codecarbon DEBUG @ 00:37:08] Not running on GCP
26
+ [codecarbon INFO @ 00:37:08] Saving emissions data to file /runs/sentence_similarity/sentence-transformers/all-MiniLM-L12-v2/2024-12-05-00-36-55/codecarbon.csv
27
+ [codecarbon DEBUG @ 00:37:08] EmissionsData(timestamp='2024-12-05T00:37:08', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.0022454530117101967, 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)
28
+
29
+ [codecarbon INFO @ 00:37:08] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.26567602157592773 W
30
+ [codecarbon DEBUG @ 00:37:08] RAM : 0.27 W during 0.16 s [measurement time: 0.0005]
31
+ [codecarbon INFO @ 00:37:08] Energy consumed for all GPUs : 0.000004 kWh. Total GPU Power : 81.04958906810351 W
32
+ [codecarbon DEBUG @ 00:37:08] GPU : 81.05 W during 0.16 s [measurement time: 0.0023]
33
+ [codecarbon INFO @ 00:37:08] Energy consumed for all CPUs : 0.000002 kWh. Total CPU Power : 42.5 W
34
+ [codecarbon DEBUG @ 00:37:08] CPU : 42.50 W during 0.16 s [measurement time: 0.0000]
35
+ [codecarbon INFO @ 00:37:08] 0.000006 kWh of electricity used since the beginning.
36
+ [codecarbon DEBUG @ 00:37:08] last_duration=0.16165502701187506
37
+ ------------------------
38
+ [codecarbon DEBUG @ 00:37:08] EmissionsData(timestamp='2024-12-05T00:37:08', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.16491737304022536, emissions=2.072454888483118e-06, emissions_rate=1.2566625639723359e-05, cpu_power=42.5, gpu_power=81.04958906810351, ram_power=0.26567602157592773, cpu_energy=1.9452090272049344e-06, gpu_energy=3.657225147613019e-06, ram_energy=1.193016676754692e-08, energy_consumed=5.614364341585501e-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)
39
+ [codecarbon DEBUG @ 00:37:09] EmissionsData(timestamp='2024-12-05T00:37:09', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.003446593997068703, emissions=2.072454888483118e-06, emissions_rate=0.0006013051987689069, cpu_power=42.5, gpu_power=81.04958906810351, ram_power=0.26567602157592773, cpu_energy=1.9452090272049344e-06, gpu_energy=3.657225147613019e-06, ram_energy=1.193016676754692e-08, energy_consumed=5.614364341585501e-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)
40
+
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+ [codecarbon WARNING @ 00:37:14] Background scheduler didn't run for a long period (5s), results might be inaccurate
97
+ [codecarbon INFO @ 00:37:14] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.34178638458251953 W
98
+ [codecarbon DEBUG @ 00:37:14] RAM : 0.34 W during 5.62 s [measurement time: 0.0005]
99
+ [codecarbon INFO @ 00:37:14] Energy consumed for all GPUs : 0.000130 kWh. Total GPU Power : 80.90480266562896 W
100
+ [codecarbon DEBUG @ 00:37:14] GPU : 80.90 W during 5.62 s [measurement time: 0.0026]
101
+ [codecarbon INFO @ 00:37:14] Energy consumed for all CPUs : 0.000068 kWh. Total CPU Power : 42.5 W
102
+ [codecarbon DEBUG @ 00:37:14] CPU : 42.50 W during 5.63 s [measurement time: 0.0000]
103
+ [codecarbon INFO @ 00:37:14] 0.000199 kWh of electricity used since the beginning.
104
+ [codecarbon DEBUG @ 00:37:14] last_duration=5.623332002025563
105
+ ------------------------
106
+ [codecarbon DEBUG @ 00:37:14] EmissionsData(timestamp='2024-12-05T00:37:14', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=5.626995744998567, emissions=7.344831051653639e-05, emissions_rate=1.3052846286905286e-05, cpu_power=42.5, gpu_power=80.90480266562896, ram_power=0.34178638458251953, cpu_energy=6.83737928957271e-05, gpu_energy=0.0001300548262648249, ram_energy=5.458327347855121e-07, energy_consumed=0.0001989744518953375, 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)
107
+ [codecarbon DEBUG @ 00:37:14] EmissionsData(timestamp='2024-12-05T00:37:14', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.005245147971436381, emissions=7.344831051653639e-05, emissions_rate=0.014003095988238174, cpu_power=42.5, gpu_power=80.90480266562896, ram_power=0.34178638458251953, cpu_energy=6.83737928957271e-05, gpu_energy=0.0001300548262648249, ram_energy=5.458327347855121e-07, energy_consumed=0.0001989744518953375, 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 @ 00:37:20] Background scheduler didn't run for a long period (5s), results might be inaccurate
163
+ [codecarbon INFO @ 00:37:20] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.3418750762939453 W
164
+ [codecarbon DEBUG @ 00:37:20] RAM : 0.34 W during 5.46 s [measurement time: 0.0004]
165
+ [codecarbon INFO @ 00:37:20] Energy consumed for all GPUs : 0.000251 kWh. Total GPU Power : 79.51430083582915 W
166
+ [codecarbon DEBUG @ 00:37:20] GPU : 79.51 W during 5.46 s [measurement time: 0.0030]
167
+ [codecarbon INFO @ 00:37:20] Energy consumed for all CPUs : 0.000133 kWh. Total CPU Power : 42.5 W
168
+ [codecarbon DEBUG @ 00:37:20] CPU : 42.50 W during 5.46 s [measurement time: 0.0000]
169
+ [codecarbon INFO @ 00:37:20] 0.000385 kWh of electricity used since the beginning.
170
+ [codecarbon DEBUG @ 00:37:20] last_duration=5.458206440962385
171
+ ------------------------
172
+ [codecarbon DEBUG @ 00:37:20] EmissionsData(timestamp='2024-12-05T00:37:20', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=5.462129193008877, emissions=0.00014195088109618715, emissions_rate=2.598819546009161e-05, cpu_power=42.5, gpu_power=79.51430083582915, ram_power=0.3418750762939453, cpu_energy=0.00013285603376563004, gpu_energy=0.0002506304782814439, ram_energy=1.064181679434311e-06, energy_consumed=0.0003845506937265083, 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)
173
+ [codecarbon DEBUG @ 00:37:20] EmissionsData(timestamp='2024-12-05T00:37:20', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.0020164839806966484, emissions=0.00014195088109618715, emissions_rate=0.07039524362953105, cpu_power=42.5, gpu_power=79.51430083582915, ram_power=0.3418750762939453, cpu_energy=0.00013285603376563004, gpu_energy=0.0002506304782814439, ram_energy=1.064181679434311e-06, energy_consumed=0.0003845506937265083, 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 @ 00:37:25] Background scheduler didn't run for a long period (5s), results might be inaccurate
229
+ [codecarbon INFO @ 00:37:25] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34191083908081055 W
230
+ [codecarbon DEBUG @ 00:37:25] RAM : 0.34 W during 5.44 s [measurement time: 0.0004]
231
+ [codecarbon INFO @ 00:37:25] Energy consumed for all GPUs : 0.000373 kWh. Total GPU Power : 81.32767939620143 W
232
+ [codecarbon DEBUG @ 00:37:25] GPU : 81.33 W during 5.44 s [measurement time: 0.0023]
233
+ [codecarbon INFO @ 00:37:25] Energy consumed for all CPUs : 0.000197 kWh. Total CPU Power : 42.5 W
234
+ [codecarbon DEBUG @ 00:37:25] CPU : 42.50 W during 5.44 s [measurement time: 0.0000]
235
+ [codecarbon INFO @ 00:37:25] 0.000572 kWh of electricity used since the beginning.
236
+ [codecarbon DEBUG @ 00:37:25] last_duration=5.435178957995959
237
+ ------------------------
238
+ [codecarbon DEBUG @ 00:37:25] EmissionsData(timestamp='2024-12-05T00:37:25', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=5.4384063520119525, emissions=0.0002111720454010686, emissions_rate=3.882976587855465e-05, cpu_power=42.5, gpu_power=81.32767939620143, ram_power=0.34191083908081055, cpu_energy=0.0001970582170962896, gpu_energy=0.0003734350209692039, ram_energy=1.5803970365000247e-06, energy_consumed=0.0005720736351019935, 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)
239
+ [codecarbon DEBUG @ 00:37:25] EmissionsData(timestamp='2024-12-05T00:37:25', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.002025774971116334, emissions=0.0002111720454010686, emissions_rate=0.10424259772777182, cpu_power=42.5, gpu_power=81.32767939620143, ram_power=0.34191083908081055, cpu_energy=0.0001970582170962896, gpu_energy=0.0003734350209692039, ram_energy=1.5803970365000247e-06, energy_consumed=0.0005720736351019935, 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 @ 00:37:31] Background scheduler didn't run for a long period (5s), results might be inaccurate
295
+ [codecarbon INFO @ 00:37:31] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34191083908081055 W
296
+ [codecarbon DEBUG @ 00:37:31] RAM : 0.34 W during 5.37 s [measurement time: 0.0004]
297
+ [codecarbon INFO @ 00:37:31] Energy consumed for all GPUs : 0.000492 kWh. Total GPU Power : 79.68353647234068 W
298
+ [codecarbon DEBUG @ 00:37:31] GPU : 79.68 W during 5.37 s [measurement time: 0.0060]
299
+ [codecarbon INFO @ 00:37:31] Energy consumed for all CPUs : 0.000261 kWh. Total CPU Power : 42.5 W
300
+ [codecarbon DEBUG @ 00:37:31] CPU : 42.50 W during 5.38 s [measurement time: 0.0000]
301
+ [codecarbon INFO @ 00:37:31] 0.000755 kWh of electricity used since the beginning.
302
+ [codecarbon DEBUG @ 00:37:31] last_duration=5.369190519966651
303
+ ------------------------
304
+ [codecarbon DEBUG @ 00:37:31] EmissionsData(timestamp='2024-12-05T00:37:31', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=5.3761263599735685, emissions=0.00027866356477632083, emissions_rate=5.1833522152870464e-05, cpu_power=42.5, gpu_power=79.68353647234068, ram_power=0.34191083908081055, cpu_energy=0.0002605251592452987, gpu_energy=0.0004922953938351071, ram_energy=2.090345136726384e-06, energy_consumed=0.0007549108982171322, 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)
305
+ [codecarbon DEBUG @ 00:37:31] EmissionsData(timestamp='2024-12-05T00:37:31', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.002033925033174455, emissions=0.00027866356477632083, emissions_rate=0.13700778555313603, cpu_power=42.5, gpu_power=79.68353647234068, ram_power=0.34191083908081055, cpu_energy=0.0002605251592452987, gpu_energy=0.0004922953938351071, ram_energy=2.090345136726384e-06, energy_consumed=0.0007549108982171322, 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)
306
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+ [codecarbon WARNING @ 00:37:36] Background scheduler didn't run for a long period (5s), results might be inaccurate
361
+ [codecarbon INFO @ 00:37:36] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.34191226959228516 W
362
+ [codecarbon DEBUG @ 00:37:36] RAM : 0.34 W during 5.36 s [measurement time: 0.0004]
363
+ [codecarbon INFO @ 00:37:36] Energy consumed for all GPUs : 0.000614 kWh. Total GPU Power : 81.48378815444873 W
364
+ [codecarbon DEBUG @ 00:37:36] GPU : 81.48 W during 5.36 s [measurement time: 0.0023]
365
+ [codecarbon INFO @ 00:37:36] Energy consumed for all CPUs : 0.000324 kWh. Total CPU Power : 42.5 W
366
+ [codecarbon DEBUG @ 00:37:36] CPU : 42.50 W during 5.36 s [measurement time: 0.0000]
367
+ [codecarbon INFO @ 00:37:36] 0.000940 kWh of electricity used since the beginning.
368
+ [codecarbon DEBUG @ 00:37:36] last_duration=5.35688115702942
369
+ ------------------------
370
+ [codecarbon DEBUG @ 00:37:36] EmissionsData(timestamp='2024-12-05T00:37:36', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=5.3600602590013295, emissions=0.0003469731288729262, emissions_rate=6.473306494833571e-05, cpu_power=42.5, gpu_power=81.48378815444873, ram_power=0.34191226959228516, cpu_energy=0.00032380243782552295, gpu_energy=0.0006135627130712251, ram_energy=2.599126761581372e-06, energy_consumed=0.0009399642776583294, 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)
371
+ [codecarbon DEBUG @ 00:37:36] EmissionsData(timestamp='2024-12-05T00:37:36', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.0020143139990977943, emissions=0.0003469731288729262, emissions_rate=0.17225374446503103, cpu_power=42.5, gpu_power=81.48378815444873, ram_power=0.34191226959228516, cpu_energy=0.00032380243782552295, gpu_energy=0.0006135627130712251, ram_energy=2.599126761581372e-06, energy_consumed=0.0009399642776583294, 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)
372
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426
+ [codecarbon WARNING @ 00:37:41] Background scheduler didn't run for a long period (5s), results might be inaccurate
427
+ [codecarbon INFO @ 00:37:41] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.34191226959228516 W
428
+ [codecarbon DEBUG @ 00:37:41] RAM : 0.34 W during 5.38 s [measurement time: 0.0004]
429
+ [codecarbon INFO @ 00:37:41] Energy consumed for all GPUs : 0.000735 kWh. Total GPU Power : 80.88542164475706 W
430
+ [codecarbon DEBUG @ 00:37:41] GPU : 80.89 W during 5.39 s [measurement time: 0.0028]
431
+ [codecarbon INFO @ 00:37:41] Energy consumed for all CPUs : 0.000387 kWh. Total CPU Power : 42.5 W
432
+ [codecarbon DEBUG @ 00:37:41] CPU : 42.50 W during 5.39 s [measurement time: 0.0000]
433
+ [codecarbon INFO @ 00:37:41] 0.001125 kWh of electricity used since the beginning.
434
+ [codecarbon DEBUG @ 00:37:41] last_duration=5.38450276304502
435
+ ------------------------
436
+ [codecarbon DEBUG @ 00:37:41] EmissionsData(timestamp='2024-12-05T00:37:41', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=5.38823386002332, emissions=0.00041530683678693217, emissions_rate=7.707661686108308e-05, cpu_power=42.5, gpu_power=80.88542164475706, ram_power=0.34191226959228516, cpu_energy=0.0003874122222387086, gpu_energy=0.0007345603098691811, ram_energy=3.1105315721308648e-06, energy_consumed=0.0011250830636800205, 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)
437
+ [codecarbon DEBUG @ 00:37:41] EmissionsData(timestamp='2024-12-05T00:37:41', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.006022343994118273, emissions=0.00041530683678693217, emissions_rate=0.06896099545169487, cpu_power=42.5, gpu_power=80.88542164475706, ram_power=0.34191226959228516, cpu_energy=0.0003874122222387086, gpu_energy=0.0007345603098691811, ram_energy=3.1105315721308648e-06, energy_consumed=0.0011250830636800205, 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)
438
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492
+ [codecarbon WARNING @ 00:37:47] Background scheduler didn't run for a long period (5s), results might be inaccurate
493
+ [codecarbon INFO @ 00:37:47] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.3419151306152344 W
494
+ [codecarbon DEBUG @ 00:37:47] RAM : 0.34 W during 5.38 s [measurement time: 0.0004]
495
+ [codecarbon INFO @ 00:37:47] Energy consumed for all GPUs : 0.000856 kWh. Total GPU Power : 80.91784923283659 W
496
+ [codecarbon DEBUG @ 00:37:47] GPU : 80.92 W during 5.38 s [measurement time: 0.0030]
497
+ [codecarbon INFO @ 00:37:47] Energy consumed for all CPUs : 0.000451 kWh. Total CPU Power : 42.5 W
498
+ [codecarbon DEBUG @ 00:37:47] CPU : 42.50 W during 5.38 s [measurement time: 0.0000]
499
+ [codecarbon INFO @ 00:37:47] 0.001310 kWh of electricity used since the beginning.
500
+ [codecarbon DEBUG @ 00:37:47] EmissionsData(timestamp='2024-12-05T00:37:47', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=5.383781075011939, emissions=0.0004836005986516783, emissions_rate=8.982545759452262e-05, cpu_power=42.5, gpu_power=80.91784923283659, ram_power=0.3419151306152344, cpu_energy=0.0004509697803620333, gpu_energy=0.000855502351067905, ram_energy=3.6215028043111817e-06, energy_consumed=0.0013100936342342493, 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)
501
+ [codecarbon INFO @ 00:37:47] 0.012699 g.CO2eq/s mean an estimation of 400.48506857409944 kg.CO2eq/year
502
+ [codecarbon DEBUG @ 00:37:47] last_duration=5.379895540012512
503
+ ------------------------
504
+ [codecarbon DEBUG @ 00:37:47] EmissionsData(timestamp='2024-12-05T00:37:47', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=5.384111588005908, emissions=0.0004836005986516783, emissions_rate=8.98199435035832e-05, cpu_power=42.5, gpu_power=80.91784923283659, ram_power=0.3419151306152344, cpu_energy=0.0004509697803620333, gpu_energy=0.000855502351067905, ram_energy=3.6215028043111817e-06, energy_consumed=0.0013100936342342493, 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)
505
+ [codecarbon DEBUG @ 00:37:47] EmissionsData(timestamp='2024-12-05T00:37:47', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.002039326005615294, emissions=0.0004836005986516783, emissions_rate=0.23713746469180588, cpu_power=42.5, gpu_power=80.91784923283659, ram_power=0.3419151306152344, cpu_energy=0.0004509697803620333, gpu_energy=0.000855502351067905, ram_energy=3.6215028043111817e-06, energy_consumed=0.0013100936342342493, 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)
506
+
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560
+ [codecarbon WARNING @ 00:37:52] Background scheduler didn't run for a long period (5s), results might be inaccurate
561
+ [codecarbon INFO @ 00:37:52] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.3419151306152344 W
562
+ [codecarbon DEBUG @ 00:37:52] RAM : 0.34 W during 5.48 s [measurement time: 0.0005]
563
+ [codecarbon INFO @ 00:37:52] Energy consumed for all GPUs : 0.000979 kWh. Total GPU Power : 80.90339416228707 W
564
+ [codecarbon DEBUG @ 00:37:52] GPU : 80.90 W during 5.48 s [measurement time: 0.0023]
565
+ [codecarbon INFO @ 00:37:52] Energy consumed for all CPUs : 0.000516 kWh. Total CPU Power : 42.5 W
566
+ [codecarbon DEBUG @ 00:37:52] CPU : 42.50 W during 5.48 s [measurement time: 0.0000]
567
+ [codecarbon INFO @ 00:37:52] 0.001498 kWh of electricity used since the beginning.
568
+ [codecarbon DEBUG @ 00:37:52] last_duration=5.478222850011662
569
+ ------------------------
570
+ [codecarbon DEBUG @ 00:37:52] EmissionsData(timestamp='2024-12-05T00:37:52', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=5.481445233977865, emissions=0.0005531313714491181, emissions_rate=0.00010090976883622216, cpu_power=42.5, gpu_power=80.90339416228707, ram_power=0.3419151306152344, cpu_energy=0.0005156799431951287, gpu_energy=0.0009786335606838392, ram_energy=4.141813693321208e-06, energy_consumed=0.0014984553175722889, 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)
571
+ [codecarbon DEBUG @ 00:37:52] EmissionsData(timestamp='2024-12-05T00:37:52', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.00202655402245, emissions=0.0005531313714491181, emissions_rate=0.2729418339316761, cpu_power=42.5, gpu_power=80.90339416228707, ram_power=0.3419151306152344, cpu_energy=0.0005156799431951287, gpu_energy=0.0009786335606838392, ram_energy=4.141813693321208e-06, energy_consumed=0.0014984553175722889, 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)
572
+
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575
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+ [codecarbon WARNING @ 00:37:58] Background scheduler didn't run for a long period (5s), results might be inaccurate
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+ [codecarbon DEBUG @ 00:37:58] RAM : 0.34 W during 5.59 s [measurement time: 0.0005]
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+ [codecarbon DEBUG @ 00:37:58] GPU : 80.22 W during 5.59 s [measurement time: 0.0022]
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+ [codecarbon INFO @ 00:37:58] Energy consumed for all CPUs : 0.000582 kWh. Total CPU Power : 42.5 W
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635
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636
+ [codecarbon DEBUG @ 00:37:58] last_duration=5.593650219030678
637
+ ------------------------
638
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639
+ [codecarbon DEBUG @ 00:37:58] EmissionsData(timestamp='2024-12-05T00:37:58', project_name='codecarbon', run_id='949ebe32-92ae-4a61-b9e4-1c493887be0e', duration=0.002028044022154063, emissions=0.000623736870132487, emissions_rate=0.3075558830670708, cpu_power=42.5, gpu_power=80.22327428835422, ram_power=0.3419151306152344, cpu_energy=0.000581752840171733, gpu_energy=0.001103302549307017, ram_energy=4.673087442212113e-06, energy_consumed=0.001689728476920962, 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 DEBUG @ 00:38:03] last_duration=5.689292910974473
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+ ------------------------
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+ name: energy_star
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+ _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
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+ cpu: ' AMD EPYC 7R32'
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+ footer: 'Powered by Hydra (https://hydra.cc)
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+
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+ Use --hydra-help to view Hydra specific help
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+
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+
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28
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+ $APP_CONFIG_GROUPS
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+
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+
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+ $CONFIG
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+
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+
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+ ${hydra.help.footer}
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+
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+ See https://hydra.cc for more info.
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+
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+
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+
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+
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+
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sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/cli.log ADDED
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+ [2024-12-04 21:40:49,001][launcher][INFO] - ََAllocating process launcher
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+ [2024-12-04 21:40:49,001][process][INFO] - + Setting multiprocessing start method to spawn.
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5
+ [2024-12-04 21:40:49,018][process][INFO] - + Launched benchmark in isolated process 243.
6
+ [PROC-0][2024-12-04 21:40:51,760][datasets][INFO] - PyTorch version 2.4.0 available.
7
+ [PROC-0][2024-12-04 21:40:52,678][backend][INFO] - َAllocating pytorch backend
8
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21
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22
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23
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+ [PROC-0][2024-12-04 21:41:00,637][energy_star][INFO] - + Preprocessing dataset
25
+ [PROC-0][2024-12-04 21:41:00,843][energy][INFO] - + Saving codecarbon emission data to preprocess_codecarbon.json
26
+ [PROC-0][2024-12-04 21:41:00,843][energy_star][INFO] - + Preparing backend for Inference
27
+ [PROC-0][2024-12-04 21:41:00,843][energy_star][INFO] - + Initialising dataloader
28
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29
+ [PROC-0][2024-12-04 21:41:01,498][energy_star][INFO] - + Running Inference energy tracking for 10 iterations
30
+ [PROC-0][2024-12-04 21:41:01,498][energy_star][INFO] - + Iteration 1/10
31
+ [PROC-0][2024-12-04 21:41:07,056][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
32
+ [PROC-0][2024-12-04 21:41:07,057][energy_star][INFO] - + Iteration 2/10
33
+ [PROC-0][2024-12-04 21:41:12,562][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
34
+ [PROC-0][2024-12-04 21:41:12,563][energy_star][INFO] - + Iteration 3/10
35
+ [PROC-0][2024-12-04 21:41:18,071][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
36
+ [PROC-0][2024-12-04 21:41:18,071][energy_star][INFO] - + Iteration 4/10
37
+ [PROC-0][2024-12-04 21:41:23,852][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
38
+ [PROC-0][2024-12-04 21:41:23,853][energy_star][INFO] - + Iteration 5/10
39
+ [PROC-0][2024-12-04 21:41:29,575][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
40
+ [PROC-0][2024-12-04 21:41:29,575][energy_star][INFO] - + Iteration 6/10
41
+ [PROC-0][2024-12-04 21:41:35,002][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
42
+ [PROC-0][2024-12-04 21:41:35,003][energy_star][INFO] - + Iteration 7/10
43
+ [PROC-0][2024-12-04 21:41:40,713][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
44
+ [PROC-0][2024-12-04 21:41:40,714][energy_star][INFO] - + Iteration 8/10
45
+ [PROC-0][2024-12-04 21:41:46,210][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
46
+ [PROC-0][2024-12-04 21:41:46,210][energy_star][INFO] - + Iteration 9/10
47
+ [PROC-0][2024-12-04 21:41:51,550][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
48
+ [PROC-0][2024-12-04 21:41:51,550][energy_star][INFO] - + Iteration 10/10
49
+ [PROC-0][2024-12-04 21:41:56,948][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
50
+ [PROC-0][2024-12-04 21:41:56,948][energy][INFO] - + forward energy consumption:
51
+ [PROC-0][2024-12-04 21:41:56,948][energy][INFO] - + CPU: 0.000059 (kWh)
52
+ [PROC-0][2024-12-04 21:41:56,948][energy][INFO] - + GPU: 0.000112 (kWh)
53
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54
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + total: 0.000171 (kWh)
55
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + forward_iteration_1 energy consumption:
56
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + CPU: 0.000066 (kWh)
57
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + GPU: 0.000124 (kWh)
58
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + RAM: 0.000001 (kWh)
59
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + total: 0.000191 (kWh)
60
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + forward_iteration_2 energy consumption:
61
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + CPU: 0.000065 (kWh)
62
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + GPU: 0.000122 (kWh)
63
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64
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + total: 0.000188 (kWh)
65
+ [PROC-0][2024-12-04 21:41:56,949][energy][INFO] - + forward_iteration_3 energy consumption:
66
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + CPU: 0.000065 (kWh)
67
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + GPU: 0.000122 (kWh)
68
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + RAM: 0.000001 (kWh)
69
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + total: 0.000188 (kWh)
70
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + forward_iteration_4 energy consumption:
71
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + CPU: 0.000068 (kWh)
72
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + GPU: 0.000128 (kWh)
73
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + RAM: 0.000001 (kWh)
74
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + total: 0.000197 (kWh)
75
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + forward_iteration_5 energy consumption:
76
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + CPU: 0.000068 (kWh)
77
+ [PROC-0][2024-12-04 21:41:56,950][energy][INFO] - + GPU: 0.000128 (kWh)
78
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + RAM: 0.000001 (kWh)
79
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + total: 0.000196 (kWh)
80
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + forward_iteration_6 energy consumption:
81
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + CPU: 0.000064 (kWh)
82
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + GPU: 0.000123 (kWh)
83
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + RAM: 0.000001 (kWh)
84
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + total: 0.000187 (kWh)
85
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + forward_iteration_7 energy consumption:
86
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + CPU: 0.000000 (kWh)
87
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + GPU: 0.000000 (kWh)
88
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + RAM: 0.000000 (kWh)
89
+ [PROC-0][2024-12-04 21:41:56,951][energy][INFO] - + total: 0.000000 (kWh)
90
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + forward_iteration_8 energy consumption:
91
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + CPU: 0.000065 (kWh)
92
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + GPU: 0.000125 (kWh)
93
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + RAM: 0.000001 (kWh)
94
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + total: 0.000190 (kWh)
95
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + forward_iteration_9 energy consumption:
96
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + CPU: 0.000063 (kWh)
97
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + GPU: 0.000123 (kWh)
98
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + RAM: 0.000001 (kWh)
99
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + total: 0.000187 (kWh)
100
+ [PROC-0][2024-12-04 21:41:56,952][energy][INFO] - + forward_iteration_10 energy consumption:
101
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + CPU: 0.000064 (kWh)
102
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + GPU: 0.000123 (kWh)
103
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + RAM: 0.000001 (kWh)
104
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + total: 0.000187 (kWh)
105
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + preprocess energy consumption:
106
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + CPU: 0.000002 (kWh)
107
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + GPU: 0.000004 (kWh)
108
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + RAM: 0.000000 (kWh)
109
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + total: 0.000006 (kWh)
110
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + forward energy efficiency: 5841080.015430 (samples/kWh)
111
+ [PROC-0][2024-12-04 21:41:56,953][energy][INFO] - + preprocess energy efficiency: 166314799.482465 (samples/kWh)
112
+ [2024-12-04 21:41:57,805][device-isolation][INFO] - + Closing device(s) isolation process...
113
+ [2024-12-04 21:41:57,852][datasets][INFO] - PyTorch version 2.4.0 available.
sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/error.log ADDED
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1
+ /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
2
+ warnings.warn(
3
+
4
+
5
+
6
+
7
+
8
+
9
+
10
+ [codecarbon INFO @ 21:40:56] [setup] RAM Tracking...
11
+ [codecarbon INFO @ 21:40:56] [setup] GPU Tracking...
12
+ [codecarbon INFO @ 21:40:56] Tracking Nvidia GPU via pynvml
13
+ [codecarbon DEBUG @ 21:40:56] GPU available. Starting setup
14
+ [codecarbon INFO @ 21:40:56] [setup] CPU Tracking...
15
+ [codecarbon DEBUG @ 21:40:56] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
16
+ [codecarbon DEBUG @ 21:40:56] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
17
+ [codecarbon DEBUG @ 21:40:56] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
18
+ [codecarbon WARNING @ 21:40:56] No CPU tracking mode found. Falling back on CPU constant mode.
19
+ [codecarbon WARNING @ 21:40:57] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
20
+ [codecarbon INFO @ 21:40:57] CPU Model on constant consumption mode: AMD EPYC 7R32
21
+ [codecarbon INFO @ 21:40:57] >>> Tracker's metadata:
22
+ [codecarbon INFO @ 21:40:57] Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
23
+ [codecarbon INFO @ 21:40:57] Python version: 3.9.20
24
+ [codecarbon INFO @ 21:40:57] CodeCarbon version: 2.5.1
25
+ [codecarbon INFO @ 21:40:57] Available RAM : 186.705 GB
26
+ [codecarbon INFO @ 21:40:57] CPU count: 48
27
+ [codecarbon INFO @ 21:40:57] CPU model: AMD EPYC 7R32
28
+ [codecarbon INFO @ 21:40:57] GPU count: 1
29
+ [codecarbon INFO @ 21:40:57] GPU model: 1 x NVIDIA A10G
30
+ [codecarbon DEBUG @ 21:40:58] Not running on AWS
31
+ [codecarbon DEBUG @ 21:40:59] Not running on Azure
32
+ [codecarbon DEBUG @ 21:41:00] Not running on GCP
33
+ [codecarbon INFO @ 21:41:00] Saving emissions data to file /runs/sentence_similarity/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/2024-12-04-21-40-46/codecarbon.csv
34
+ [codecarbon DEBUG @ 21:41:00] EmissionsData(timestamp='2024-12-04T21:41:00', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.002095217991154641, 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)
35
+
36
+
37
+ [codecarbon INFO @ 21:41:00] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.358670711517334 W
38
+ [codecarbon DEBUG @ 21:41:00] RAM : 0.36 W during 0.20 s [measurement time: 0.0005]
39
+ [codecarbon INFO @ 21:41:00] Energy consumed for all GPUs : 0.000004 kWh. Total GPU Power : 63.313183121484805 W
40
+ [codecarbon DEBUG @ 21:41:00] GPU : 63.31 W during 0.20 s [measurement time: 0.0022]
41
+ [codecarbon INFO @ 21:41:00] Energy consumed for all CPUs : 0.000002 kWh. Total CPU Power : 42.5 W
42
+ [codecarbon DEBUG @ 21:41:00] CPU : 42.50 W during 0.21 s [measurement time: 0.0000]
43
+ [codecarbon INFO @ 21:41:00] 0.000006 kWh of electricity used since the beginning.
44
+ [codecarbon DEBUG @ 21:41:00] last_duration=0.20219684799667448
45
+ ------------------------
46
+ [codecarbon DEBUG @ 21:41:00] EmissionsData(timestamp='2024-12-04T21:41:00', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.20531185902655125, emissions=2.2194920658859325e-06, emissions_rate=1.0810345181273257e-05, cpu_power=42.5, gpu_power=63.313183121484805, ram_power=0.358670711517334, cpu_energy=2.4225458650309725e-06, gpu_energy=3.5700028560015085e-06, ram_energy=2.014529724960743e-08, energy_consumed=6.012694018282088e-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)
47
+ [codecarbon DEBUG @ 21:41:01] EmissionsData(timestamp='2024-12-04T21:41:01', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.00529201200697571, emissions=2.2194920658859325e-06, emissions_rate=0.0004194042007010359, cpu_power=42.5, gpu_power=63.313183121484805, ram_power=0.358670711517334, cpu_energy=2.4225458650309725e-06, gpu_energy=3.5700028560015085e-06, ram_energy=2.014529724960743e-08, energy_consumed=6.012694018282088e-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)
48
+
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+ [codecarbon WARNING @ 21:41:07] Background scheduler didn't run for a long period (5s), results might be inaccurate
105
+ [codecarbon INFO @ 21:41:07] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.4217991828918457 W
106
+ [codecarbon DEBUG @ 21:41:07] RAM : 0.42 W during 5.55 s [measurement time: 0.0004]
107
+ [codecarbon INFO @ 21:41:07] Energy consumed for all GPUs : 0.000128 kWh. Total GPU Power : 80.5587352712058 W
108
+ [codecarbon DEBUG @ 21:41:07] GPU : 80.56 W during 5.56 s [measurement time: 0.0023]
109
+ [codecarbon INFO @ 21:41:07] Energy consumed for all CPUs : 0.000068 kWh. Total CPU Power : 42.5 W
110
+ [codecarbon DEBUG @ 21:41:07] CPU : 42.50 W during 5.56 s [measurement time: 0.0000]
111
+ [codecarbon INFO @ 21:41:07] 0.000197 kWh of electricity used since the beginning.
112
+ [codecarbon DEBUG @ 21:41:07] last_duration=5.554333877982572
113
+ ------------------------
114
+ [codecarbon DEBUG @ 21:41:07] EmissionsData(timestamp='2024-12-04T21:41:07', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.557659258018248, emissions=7.25665004257193e-05, emissions_rate=1.305702581910268e-05, cpu_power=42.5, gpu_power=80.5587352712058, ram_power=0.4217991828918457, cpu_energy=6.803259559953101e-05, gpu_energy=0.0001278820467502939, ram_energy=6.709502475631516e-07, energy_consumed=0.00019658559259738806, 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)
115
+ [codecarbon DEBUG @ 21:41:07] EmissionsData(timestamp='2024-12-04T21:41:07', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.005300023010931909, emissions=7.25665004257193e-05, emissions_rate=0.013691733087958773, cpu_power=42.5, gpu_power=80.5587352712058, ram_power=0.4217991828918457, cpu_energy=6.803259559953101e-05, gpu_energy=0.0001278820467502939, ram_energy=6.709502475631516e-07, energy_consumed=0.00019658559259738806, 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 @ 21:41:12] Background scheduler didn't run for a long period (5s), results might be inaccurate
171
+ [codecarbon INFO @ 21:41:12] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.42191505432128906 W
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+ [codecarbon DEBUG @ 21:41:12] RAM : 0.42 W during 5.50 s [measurement time: 0.0004]
173
+ [codecarbon INFO @ 21:41:12] Energy consumed for all GPUs : 0.000250 kWh. Total GPU Power : 80.02536311863172 W
174
+ [codecarbon DEBUG @ 21:41:12] GPU : 80.03 W during 5.50 s [measurement time: 0.0057]
175
+ [codecarbon INFO @ 21:41:12] Energy consumed for all CPUs : 0.000133 kWh. Total CPU Power : 42.5 W
176
+ [codecarbon DEBUG @ 21:41:12] CPU : 42.50 W during 5.50 s [measurement time: 0.0000]
177
+ [codecarbon INFO @ 21:41:12] 0.000384 kWh of electricity used since the beginning.
178
+ [codecarbon DEBUG @ 21:41:12] last_duration=5.4962086220039055
179
+ ------------------------
180
+ [codecarbon DEBUG @ 21:41:12] EmissionsData(timestamp='2024-12-04T21:41:12', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.502865254005883, emissions=0.00014189053092958443, emissions_rate=2.5784845599534417e-05, cpu_power=42.5, gpu_power=80.02536311863172, ram_power=0.42191505432128906, cpu_energy=0.0001329957828916021, gpu_energy=0.0002500763111727977, ram_energy=1.3151086132727109e-06, energy_consumed=0.00038438720267767253, 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)
181
+ [codecarbon DEBUG @ 21:41:12] EmissionsData(timestamp='2024-12-04T21:41:12', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.0020321760093793273, emissions=0.00014189053092958443, emissions_rate=0.06982196929532744, cpu_power=42.5, gpu_power=80.02536311863172, ram_power=0.42191505432128906, cpu_energy=0.0001329957828916021, gpu_energy=0.0002500763111727977, ram_energy=1.3151086132727109e-06, energy_consumed=0.00038438720267767253, 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 @ 21:41:18] Background scheduler didn't run for a long period (5s), results might be inaccurate
237
+ [codecarbon INFO @ 21:41:18] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.4219307899475098 W
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+ [codecarbon DEBUG @ 21:41:18] RAM : 0.42 W during 5.50 s [measurement time: 0.0005]
239
+ [codecarbon INFO @ 21:41:18] Energy consumed for all GPUs : 0.000373 kWh. Total GPU Power : 80.0877431989967 W
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+ [codecarbon DEBUG @ 21:41:18] GPU : 80.09 W during 5.50 s [measurement time: 0.0023]
241
+ [codecarbon INFO @ 21:41:18] Energy consumed for all CPUs : 0.000198 kWh. Total CPU Power : 42.5 W
242
+ [codecarbon DEBUG @ 21:41:18] CPU : 42.50 W during 5.51 s [measurement time: 0.0000]
243
+ [codecarbon INFO @ 21:41:18] 0.000573 kWh of electricity used since the beginning.
244
+ [codecarbon DEBUG @ 21:41:18] last_duration=5.503680415975396
245
+ ------------------------
246
+ [codecarbon DEBUG @ 21:41:18] EmissionsData(timestamp='2024-12-04T21:41:18', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.5071164420223795, emissions=0.00021133107931143805, emissions_rate=3.837418030584276e-05, cpu_power=42.5, gpu_power=80.0877431989967, ram_power=0.4219307899475098, cpu_energy=0.0001980087208722883, gpu_energy=0.0003725355758064097, ram_energy=1.960167736127847e-06, energy_consumed=0.0005725044644148259, 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)
247
+ [codecarbon DEBUG @ 21:41:18] EmissionsData(timestamp='2024-12-04T21:41:18', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.006641042011324316, emissions=0.00021133107931143805, emissions_rate=0.031821975971703824, cpu_power=42.5, gpu_power=80.0877431989967, ram_power=0.4219307899475098, cpu_energy=0.0001980087208722883, gpu_energy=0.0003725355758064097, ram_energy=1.960167736127847e-06, energy_consumed=0.0005725044644148259, 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 @ 21:41:23] Background scheduler didn't run for a long period (5s), results might be inaccurate
306
+ [codecarbon INFO @ 21:41:23] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.421933650970459 W
307
+ [codecarbon DEBUG @ 21:41:23] RAM : 0.42 W during 5.78 s [measurement time: 0.0004]
308
+ [codecarbon INFO @ 21:41:23] Energy consumed for all GPUs : 0.000501 kWh. Total GPU Power : 79.87532674888328 W
309
+ [codecarbon DEBUG @ 21:41:23] GPU : 79.88 W during 5.78 s [measurement time: 0.0023]
310
+ [codecarbon INFO @ 21:41:23] Energy consumed for all CPUs : 0.000266 kWh. Total CPU Power : 42.5 W
311
+ [codecarbon DEBUG @ 21:41:23] CPU : 42.50 W during 5.78 s [measurement time: 0.0000]
312
+ [codecarbon INFO @ 21:41:23] 0.000770 kWh of electricity used since the beginning.
313
+ [codecarbon DEBUG @ 21:41:23] last_duration=5.7772260020137765
314
+ ------------------------
315
+ [codecarbon DEBUG @ 21:41:23] EmissionsData(timestamp='2024-12-04T21:41:23', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.780409655009862, emissions=0.0002840937397998374, emissions_rate=4.9147682734495175e-05, cpu_power=42.5, gpu_power=79.87532674888328, ram_power=0.421933650970459, cpu_energy=0.0002662484930160847, gpu_energy=0.0005007356783659489, ram_energy=2.637291195278228e-06, energy_consumed=0.0007696214625773118, 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)
316
+ [codecarbon DEBUG @ 21:41:23] EmissionsData(timestamp='2024-12-04T21:41:23', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.005203137989155948, emissions=0.0002840937397998374, emissions_rate=0.05460046233483095, cpu_power=42.5, gpu_power=79.87532674888328, ram_power=0.421933650970459, cpu_energy=0.0002662484930160847, gpu_energy=0.0005007356783659489, ram_energy=2.637291195278228e-06, energy_consumed=0.0007696214625773118, 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 @ 21:41:29] Background scheduler didn't run for a long period (5s), results might be inaccurate
373
+ [codecarbon INFO @ 21:41:29] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.421933650970459 W
374
+ [codecarbon DEBUG @ 21:41:29] RAM : 0.42 W during 5.72 s [measurement time: 0.0004]
375
+ [codecarbon INFO @ 21:41:29] Energy consumed for all GPUs : 0.000629 kWh. Total GPU Power : 80.62234383570966 W
376
+ [codecarbon DEBUG @ 21:41:29] GPU : 80.62 W during 5.72 s [measurement time: 0.0059]
377
+ [codecarbon INFO @ 21:41:29] Energy consumed for all CPUs : 0.000334 kWh. Total CPU Power : 42.5 W
378
+ [codecarbon DEBUG @ 21:41:29] CPU : 42.50 W during 5.72 s [measurement time: 0.0000]
379
+ [codecarbon INFO @ 21:41:29] 0.000966 kWh of electricity used since the beginning.
380
+ [codecarbon DEBUG @ 21:41:29] last_duration=5.714988129970152
381
+ ------------------------
382
+ [codecarbon DEBUG @ 21:41:29] EmissionsData(timestamp='2024-12-04T21:41:29', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.7217791639850475, emissions=0.00035652631813954327, emissions_rate=6.23103947079344e-05, cpu_power=42.5, gpu_power=80.62234383570966, ram_power=0.421933650970459, cpu_energy=0.0003337960765023228, gpu_energy=0.0006287410585477105, ram_energy=3.3071197624280633e-06, energy_consumed=0.0009658442548124613, 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)
383
+ [codecarbon DEBUG @ 21:41:29] EmissionsData(timestamp='2024-12-04T21:41:29', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.0020339550101198256, emissions=0.00035652631813954327, emissions_rate=0.17528721941521183, cpu_power=42.5, gpu_power=80.62234383570966, ram_power=0.421933650970459, cpu_energy=0.0003337960765023228, gpu_energy=0.0006287410585477105, ram_energy=3.3071197624280633e-06, energy_consumed=0.0009658442548124613, 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 @ 21:41:34] Background scheduler didn't run for a long period (5s), results might be inaccurate
439
+ [codecarbon INFO @ 21:41:34] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.4219350814819336 W
440
+ [codecarbon DEBUG @ 21:41:34] RAM : 0.42 W during 5.42 s [measurement time: 0.0004]
441
+ [codecarbon INFO @ 21:41:35] Energy consumed for all GPUs : 0.000752 kWh. Total GPU Power : 81.4907511602875 W
442
+ [codecarbon DEBUG @ 21:41:35] GPU : 81.49 W during 5.42 s [measurement time: 0.0023]
443
+ [codecarbon INFO @ 21:41:35] Energy consumed for all CPUs : 0.000398 kWh. Total CPU Power : 42.5 W
444
+ [codecarbon DEBUG @ 21:41:35] CPU : 42.50 W during 5.43 s [measurement time: 0.0000]
445
+ [codecarbon INFO @ 21:41:35] 0.001153 kWh of electricity used since the beginning.
446
+ [codecarbon DEBUG @ 21:41:35] last_duration=5.423253223998472
447
+ ------------------------
448
+ [codecarbon DEBUG @ 21:41:35] EmissionsData(timestamp='2024-12-04T21:41:35', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.426443868025672, emissions=0.00042573062954880483, emissions_rate=7.845481127287518e-05, cpu_power=42.5, gpu_power=81.4907511602875, ram_power=0.4219350814819336, cpu_energy=0.00039785707053577226, gpu_energy=0.0007515217123286178, ram_energy=3.942758145850851e-06, energy_consumed=0.0011533215410102409, 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)
449
+ [codecarbon DEBUG @ 21:41:35] EmissionsData(timestamp='2024-12-04T21:41:35', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.002038365986663848, emissions=0.00042573062954880483, emissions_rate=0.20885877822440976, cpu_power=42.5, gpu_power=81.4907511602875, ram_power=0.4219350814819336, cpu_energy=0.00039785707053577226, gpu_energy=0.0007515217123286178, ram_energy=3.942758145850851e-06, energy_consumed=0.0011533215410102409, 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)
450
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+ [codecarbon WARNING @ 21:41:40] Background scheduler didn't run for a long period (5s), results might be inaccurate
508
+ [codecarbon INFO @ 21:41:40] Energy consumed for RAM : 0.000005 kWh. RAM Power : 0.4219350814819336 W
509
+ [codecarbon DEBUG @ 21:41:40] RAM : 0.42 W during 5.71 s [measurement time: 0.0004]
510
+ [codecarbon INFO @ 21:41:40] Energy consumed for all GPUs : 0.000880 kWh. Total GPU Power : 80.97259072749019 W
511
+ [codecarbon DEBUG @ 21:41:40] GPU : 80.97 W during 5.71 s [measurement time: 0.0023]
512
+ [codecarbon INFO @ 21:41:40] Energy consumed for all CPUs : 0.000465 kWh. Total CPU Power : 42.5 W
513
+ [codecarbon DEBUG @ 21:41:40] CPU : 42.50 W during 5.71 s [measurement time: 0.0000]
514
+ [codecarbon INFO @ 21:41:40] 0.001350 kWh of electricity used since the beginning.
515
+ [codecarbon DEBUG @ 21:41:40] EmissionsData(timestamp='2024-12-04T21:41:40', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.709941094974056, emissions=0.0004982483443375706, emissions_rate=8.725980461972427e-05, cpu_power=42.5, gpu_power=80.97259072749019, ram_power=0.4219350814819336, cpu_energy=0.00046526514224654725, gpu_energy=0.0008798982039177616, ram_energy=4.611625174304834e-06, energy_consumed=0.0013497749713386137, 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)
516
+ [codecarbon INFO @ 21:41:40] 0.012705 g.CO2eq/s mean an estimation of 400.6583086926967 kg.CO2eq/year
517
+ [codecarbon DEBUG @ 21:41:40] last_duration=5.706764361995738
518
+ ------------------------
519
+ [codecarbon DEBUG @ 21:41:40] EmissionsData(timestamp='2024-12-04T21:41:40', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.710274618992116, emissions=0.0004982483443375706, emissions_rate=8.725470797506288e-05, cpu_power=42.5, gpu_power=80.97259072749019, ram_power=0.4219350814819336, cpu_energy=0.00046526514224654725, gpu_energy=0.0008798982039177616, ram_energy=4.611625174304834e-06, energy_consumed=0.0013497749713386137, 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)
520
+ [codecarbon DEBUG @ 21:41:40] EmissionsData(timestamp='2024-12-04T21:41:40', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.0022437340230681, emissions=0.0004982483443375706, emissions_rate=0.2220621246613989, cpu_power=42.5, gpu_power=80.97259072749019, ram_power=0.4219350814819336, cpu_energy=0.00046526514224654725, gpu_energy=0.0008798982039177616, ram_energy=4.611625174304834e-06, energy_consumed=0.0013497749713386137, 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)
521
+
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576
+ [codecarbon WARNING @ 21:41:46] Background scheduler didn't run for a long period (5s), results might be inaccurate
577
+ [codecarbon INFO @ 21:41:46] Energy consumed for RAM : 0.000005 kWh. RAM Power : 0.4219350814819336 W
578
+ [codecarbon DEBUG @ 21:41:46] RAM : 0.42 W during 5.49 s [measurement time: 0.0004]
579
+ [codecarbon INFO @ 21:41:46] Energy consumed for all GPUs : 0.001005 kWh. Total GPU Power : 81.8805876937801 W
580
+ [codecarbon DEBUG @ 21:41:46] GPU : 81.88 W during 5.49 s [measurement time: 0.0039]
581
+ [codecarbon INFO @ 21:41:46] Energy consumed for all CPUs : 0.000530 kWh. Total CPU Power : 42.5 W
582
+ [codecarbon DEBUG @ 21:41:46] CPU : 42.50 W during 5.50 s [measurement time: 0.0000]
583
+ [codecarbon INFO @ 21:41:46] 0.001540 kWh of electricity used since the beginning.
584
+ [codecarbon DEBUG @ 21:41:46] last_duration=5.490556205040775
585
+ ------------------------
586
+ [codecarbon DEBUG @ 21:41:46] EmissionsData(timestamp='2024-12-04T21:41:46', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.495387717033736, emissions=0.0005685374313765645, emissions_rate=0.00010345720095677723, cpu_power=42.5, gpu_power=81.8805876937801, ram_power=0.4219350814819336, cpu_energy=0.0005301400033585702, gpu_energy=0.001004795803836167, ram_energy=5.255151515821446e-06, energy_consumed=0.0015401909587105587, 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)
587
+ [codecarbon DEBUG @ 21:41:46] EmissionsData(timestamp='2024-12-04T21:41:46', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.0020296149887144566, emissions=0.0005685374313765645, emissions_rate=0.28012082810674943, cpu_power=42.5, gpu_power=81.8805876937801, ram_power=0.4219350814819336, cpu_energy=0.0005301400033585702, gpu_energy=0.001004795803836167, ram_energy=5.255151515821446e-06, energy_consumed=0.0015401909587105587, 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)
588
+
589
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642
+ [codecarbon WARNING @ 21:41:51] Background scheduler didn't run for a long period (5s), results might be inaccurate
643
+ [codecarbon INFO @ 21:41:51] Energy consumed for RAM : 0.000006 kWh. RAM Power : 0.4219365119934082 W
644
+ [codecarbon DEBUG @ 21:41:51] RAM : 0.42 W during 5.34 s [measurement time: 0.0004]
645
+ [codecarbon INFO @ 21:41:51] Energy consumed for all GPUs : 0.001128 kWh. Total GPU Power : 83.2974686771808 W
646
+ [codecarbon DEBUG @ 21:41:51] GPU : 83.30 W during 5.34 s [measurement time: 0.0023]
647
+ [codecarbon INFO @ 21:41:51] Energy consumed for all CPUs : 0.000593 kWh. Total CPU Power : 42.5 W
648
+ [codecarbon DEBUG @ 21:41:51] CPU : 42.50 W during 5.34 s [measurement time: 0.0000]
649
+ [codecarbon INFO @ 21:41:51] 0.001727 kWh of electricity used since the beginning.
650
+ [codecarbon DEBUG @ 21:41:51] last_duration=5.335901124984957
651
+ ------------------------
652
+ [codecarbon DEBUG @ 21:41:51] EmissionsData(timestamp='2024-12-04T21:41:51', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.339070877991617, emissions=0.0006376158133681719, emissions_rate=0.00011942448938007394, cpu_power=42.5, gpu_power=83.2974686771808, ram_power=0.4219365119934082, cpu_energy=0.0005931695293567626, gpu_energy=0.001128277013732415, ram_energy=5.880553919651026e-06, energy_consumed=0.0017273270970088286, 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)
653
+ [codecarbon DEBUG @ 21:41:51] EmissionsData(timestamp='2024-12-04T21:41:51', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=0.002015664998907596, emissions=0.0006376158133681719, emissions_rate=0.3163302501723909, cpu_power=42.5, gpu_power=83.2974686771808, ram_power=0.4219365119934082, cpu_energy=0.0005931695293567626, gpu_energy=0.001128277013732415, ram_energy=5.880553919651026e-06, energy_consumed=0.0017273270970088286, 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)
654
+
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  99%|█████████▉| 988/1000 [00:05<00:00, 187.53it/s]
708
+ [codecarbon WARNING @ 21:41:56] Background scheduler didn't run for a long period (5s), results might be inaccurate
709
+ [codecarbon INFO @ 21:41:56] Energy consumed for RAM : 0.000007 kWh. RAM Power : 0.4219365119934082 W
710
+ [codecarbon DEBUG @ 21:41:56] RAM : 0.42 W during 5.39 s [measurement time: 0.0004]
711
+ [codecarbon INFO @ 21:41:56] Energy consumed for all GPUs : 0.001251 kWh. Total GPU Power : 81.94900456059085 W
712
+ [codecarbon DEBUG @ 21:41:56] GPU : 81.95 W during 5.39 s [measurement time: 0.0023]
713
+ [codecarbon INFO @ 21:41:56] Energy consumed for all CPUs : 0.000657 kWh. Total CPU Power : 42.5 W
714
+ [codecarbon DEBUG @ 21:41:56] CPU : 42.50 W during 5.40 s [measurement time: 0.0000]
715
+ [codecarbon INFO @ 21:41:56] 0.001914 kWh of electricity used since the beginning.
716
+ [codecarbon DEBUG @ 21:41:56] last_duration=5.393976785999257
717
+ ------------------------
718
+ [codecarbon DEBUG @ 21:41:56] EmissionsData(timestamp='2024-12-04T21:41:56', project_name='codecarbon', run_id='67a1e19b-dda1-45b5-badc-b2407c0fbf10', duration=5.397134728031233, emissions=0.0007066997495961405, emissions_rate=0.0001309398014331079, cpu_power=42.5, gpu_power=81.94900456059085, ram_power=0.4219365119934082, cpu_energy=0.0006568845176676809, gpu_energy=0.0012510810008645734, ram_energy=6.5127634263995326e-06, energy_consumed=0.001914478281958654, 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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+ run:
3
+ dir: /runs/text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52
4
+ sweep:
5
+ dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
6
+ subdir: ${hydra.job.num}
7
+ launcher:
8
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
9
+ sweeper:
10
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
11
+ max_batch_size: null
12
+ params: null
13
+ help:
14
+ app_name: ${hydra.job.name}
15
+ header: '${hydra.help.app_name} is powered by Hydra.
16
+
17
+ '
18
+ footer: 'Powered by Hydra (https://hydra.cc)
19
+
20
+ Use --hydra-help to view Hydra specific help
21
+
22
+ '
23
+ template: '${hydra.help.header}
24
+
25
+ == Configuration groups ==
26
+
27
+ Compose your configuration from those groups (group=option)
28
+
29
+
30
+ $APP_CONFIG_GROUPS
31
+
32
+
33
+ == Config ==
34
+
35
+ Override anything in the config (foo.bar=value)
36
+
37
+
38
+ $CONFIG
39
+
40
+
41
+ ${hydra.help.footer}
42
+
43
+ '
44
+ hydra_help:
45
+ template: 'Hydra (${hydra.runtime.version})
46
+
47
+ See https://hydra.cc for more info.
48
+
49
+
50
+ == Flags ==
51
+
52
+ $FLAGS_HELP
53
+
54
+
55
+ == Configuration groups ==
56
+
57
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
58
+ to command line)
59
+
60
+
61
+ $HYDRA_CONFIG_GROUPS
62
+
63
+
64
+ Use ''--cfg hydra'' to Show the Hydra config.
65
+
66
+ '
67
+ hydra_help: ???
68
+ hydra_logging:
69
+ version: 1
70
+ formatters:
71
+ colorlog:
72
+ (): colorlog.ColoredFormatter
73
+ format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
74
+ handlers:
75
+ console:
76
+ class: logging.StreamHandler
77
+ formatter: colorlog
78
+ stream: ext://sys.stdout
79
+ root:
80
+ level: INFO
81
+ handlers:
82
+ - console
83
+ disable_existing_loggers: false
84
+ job_logging:
85
+ version: 1
86
+ formatters:
87
+ simple:
88
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
89
+ colorlog:
90
+ (): colorlog.ColoredFormatter
91
+ format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
92
+ - %(message)s'
93
+ log_colors:
94
+ DEBUG: purple
95
+ INFO: green
96
+ WARNING: yellow
97
+ ERROR: red
98
+ CRITICAL: red
99
+ handlers:
100
+ console:
101
+ class: logging.StreamHandler
102
+ formatter: colorlog
103
+ stream: ext://sys.stdout
104
+ file:
105
+ class: logging.FileHandler
106
+ formatter: simple
107
+ filename: ${hydra.job.name}.log
108
+ root:
109
+ level: INFO
110
+ handlers:
111
+ - console
112
+ - file
113
+ disable_existing_loggers: false
114
+ env: {}
115
+ mode: RUN
116
+ searchpath: []
117
+ callbacks: {}
118
+ output_subdir: .hydra
119
+ overrides:
120
+ hydra:
121
+ - hydra.run.dir=/runs/text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52
122
+ - hydra.mode=RUN
123
+ task:
124
+ - backend.model=bartowski/Meta-Llama-3.1-8B-Instruct-GGUF
125
+ - backend.processor=bartowski/Meta-Llama-3.1-8B-Instruct-GGUF
126
+ job:
127
+ name: cli
128
+ chdir: true
129
+ override_dirname: backend.model=bartowski/Meta-Llama-3.1-8B-Instruct-GGUF,backend.processor=bartowski/Meta-Llama-3.1-8B-Instruct-GGUF
130
+ id: ???
131
+ num: ???
132
+ config_name: text_generation
133
+ env_set:
134
+ OVERRIDE_BENCHMARKS: '1'
135
+ env_copy: []
136
+ config:
137
+ override_dirname:
138
+ kv_sep: '='
139
+ item_sep: ','
140
+ exclude_keys: []
141
+ runtime:
142
+ version: 1.3.2
143
+ version_base: '1.3'
144
+ cwd: /
145
+ config_sources:
146
+ - path: hydra.conf
147
+ schema: pkg
148
+ provider: hydra
149
+ - path: optimum_benchmark
150
+ schema: pkg
151
+ provider: main
152
+ - path: hydra_plugins.hydra_colorlog.conf
153
+ schema: pkg
154
+ provider: hydra-colorlog
155
+ - path: /optimum-benchmark/examples/energy_star
156
+ schema: file
157
+ provider: command-line
158
+ - path: ''
159
+ schema: structured
160
+ provider: schema
161
+ output_dir: /runs/text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52
162
+ choices:
163
+ benchmark: energy_star
164
+ launcher: process
165
+ backend: pytorch
166
+ hydra/env: default
167
+ hydra/callbacks: null
168
+ hydra/job_logging: colorlog
169
+ hydra/hydra_logging: colorlog
170
+ hydra/hydra_help: default
171
+ hydra/help: default
172
+ hydra/sweeper: basic
173
+ hydra/launcher: basic
174
+ hydra/output: default
175
+ verbose: false
text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52/.hydra/overrides.yaml ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ - backend.model=bartowski/Meta-Llama-3.1-8B-Instruct-GGUF
2
+ - backend.processor=bartowski/Meta-Llama-3.1-8B-Instruct-GGUF
text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52/cli.log ADDED
File without changes
text_generation/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/2024-12-05-00-36-52/error.log ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ Error executing job with overrides: ['backend.model=bartowski/Meta-Llama-3.1-8B-Instruct-GGUF', 'backend.processor=bartowski/Meta-Llama-3.1-8B-Instruct-GGUF']
2
+ Traceback (most recent call last):
3
+ File "/optimum-benchmark/optimum_benchmark/cli.py", line 62, in benchmark_cli
4
+ experiment_config: ExperimentConfig = OmegaConf.to_object(experiment_config)
5
+ KeyError: 'Could not find the proper library name for bartowski/Meta-Llama-3.1-8B-Instruct-GGUF.'
6
+
7
+ Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.