Upload folder using huggingface_hub

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-29-54/.hydra/config.yaml

@@ -0,0 +1,96 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-generation
+  model: meta-llama/Llama-3.1-8B-Instruct
+  processor: meta-llama/Llama-3.1-8B-Instruct
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: false
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/text_generation
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs:
+    max_new_tokens: 10
+    min_new_tokens: 10
+  call_kwargs: {}
+experiment_name: text_generation
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-29-54/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: ./runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-29-54
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=./runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-29-54
+    - hydra.mode=RUN
+    task:
+    - backend.model=meta-llama/Llama-3.1-8B-Instruct
+    - backend.processor=meta-llama/Llama-3.1-8B-Instruct
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=meta-llama/Llama-3.1-8B-Instruct,backend.processor=meta-llama/Llama-3.1-8B-Instruct
+    id: ???
+    num: ???
+    config_name: text_generation
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-29-54
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-29-54/.hydra/overrides.yaml

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

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-29-54/cli.log

@@ -0,0 +1,17 @@
+[2024-10-23 20:29:57,163][launcher][INFO] - ََAllocating process launcher
+[2024-10-23 20:29:57,163][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-10-23 20:29:57,173][process][INFO] - 	+ Launched benchmark in isolated process 200.
+[PROC-0][2024-10-23 20:29:59,693][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-10-23 20:30:00,603][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-10-23 20:30:00,603][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-10-23 20:30:01,832][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCausalLM
+[PROC-0][2024-10-23 20:30:01,832][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-10-23 20:30:01,832][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-10-23 20:30:01,832][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-10-23 20:30:01,833][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-10-23 20:30:01,833][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-10-23 20:30:01,852][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-10-23 20:30:01,853][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-10-23 20:30:01,853][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-10-23 20:30:01,854][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[2024-10-23 20:30:02,845][experiment][ERROR] - Error during experiment

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-29-54/error.log

@@ -0,0 +1,50 @@
+Error executing job with overrides: ['backend.model=meta-llama/Llama-3.1-8B-Instruct', 'backend.processor=meta-llama/Llama-3.1-8B-Instruct']
+Traceback (most recent call last):
+  File "/optimum-benchmark/optimum_benchmark/cli.py", line 65, in benchmark_cli
+    benchmark_report: BenchmarkReport = launch(experiment_config=experiment_config)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch
+    raise error
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch
+    report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch
+    while not process_context.join():
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join
+    raise ProcessRaisedException(msg, error_index, failed_process.pid)
+torch.multiprocessing.spawn.ProcessRaisedException: 
+
+-- Process 0 terminated with the following error:
+Traceback (most recent call last):
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap
+    fn(i, *args)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint
+    worker_output = worker(*worker_args)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 55, in run
+    backend: Backend = backend_factory(backend_config)
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 81, in __init__
+    self.load_model_with_no_weights()
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 246, in load_model_with_no_weights
+    self.load_model_from_pretrained()
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 204, in load_model_from_pretrained
+    self.pretrained_model = self.automodel_class.from_pretrained(
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/auto/auto_factory.py", line 564, in from_pretrained
+    return model_class.from_pretrained(
+  File "/opt/conda/lib/python3.9/site-packages/transformers/modeling_utils.py", line 3810, in from_pretrained
+    model = cls(config, *model_args, **model_kwargs)
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 1116, in __init__
+    self.model = LlamaModel(config)
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 902, in __init__
+    [LlamaDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 902, in <listcomp>
+    [LlamaDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 691, in __init__
+    self.mlp = LlamaMLP(config)
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 287, in __init__
+    self.up_proj = nn.Linear(self.hidden_size, self.intermediate_size, bias=config.mlp_bias)
+  File "/opt/conda/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 99, in __init__
+    self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
+  File "/opt/conda/lib/python3.9/site-packages/torch/utils/_device.py", line 79, in __torch_function__
+    return func(*args, **kwargs)
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 224.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 69.50 MiB is free. Process 28476 has 22.12 GiB memory in use. Of the allocated memory 21.83 GiB is allocated by PyTorch, and 1.24 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
+
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-29-54/experiment_config.json

@@ -0,0 +1,110 @@
+{
+    "experiment_name": "text_generation",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-generation",
+        "model": "meta-llama/Llama-3.1-8B-Instruct",
+        "processor": "meta-llama/Llama-3.1-8B-Instruct",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": false,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/text_generation",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {
+            "max_new_tokens": 10,
+            "min_new_tokens": 10
+        },
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-30-04/.hydra/config.yaml

@@ -0,0 +1,96 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-generation
+  model: meta-llama/Llama-3.1-8B-Instruct
+  processor: meta-llama/Llama-3.1-8B-Instruct
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: false
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/text_generation
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs:
+    max_new_tokens: 10
+    min_new_tokens: 10
+  call_kwargs: {}
+experiment_name: text_generation
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-30-04/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: ./runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-30-04
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=./runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-30-04
+    - hydra.mode=RUN
+    task:
+    - backend.model=meta-llama/Llama-3.1-8B-Instruct
+    - backend.processor=meta-llama/Llama-3.1-8B-Instruct
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=meta-llama/Llama-3.1-8B-Instruct,backend.processor=meta-llama/Llama-3.1-8B-Instruct
+    id: ???
+    num: ???
+    config_name: text_generation
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-30-04
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-30-04/.hydra/overrides.yaml

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

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-30-04/cli.log

@@ -0,0 +1,17 @@
+[2024-10-23 20:30:07,112][launcher][INFO] - ََAllocating process launcher
+[2024-10-23 20:30:07,113][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-10-23 20:30:07,123][process][INFO] - 	+ Launched benchmark in isolated process 421.
+[PROC-0][2024-10-23 20:30:09,639][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-10-23 20:30:10,573][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-10-23 20:30:10,573][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-10-23 20:30:11,062][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCausalLM
+[PROC-0][2024-10-23 20:30:11,062][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-10-23 20:30:11,062][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-10-23 20:30:11,062][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-10-23 20:30:11,063][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-10-23 20:30:11,063][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-10-23 20:30:11,084][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-10-23 20:30:11,085][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-10-23 20:30:11,085][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-10-23 20:30:11,086][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[2024-10-23 20:30:12,070][experiment][ERROR] - Error during experiment

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-30-04/error.log

@@ -0,0 +1,50 @@
+Error executing job with overrides: ['backend.model=meta-llama/Llama-3.1-8B-Instruct', 'backend.processor=meta-llama/Llama-3.1-8B-Instruct']
+Traceback (most recent call last):
+  File "/optimum-benchmark/optimum_benchmark/cli.py", line 65, in benchmark_cli
+    benchmark_report: BenchmarkReport = launch(experiment_config=experiment_config)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch
+    raise error
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch
+    report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch
+    while not process_context.join():
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join
+    raise ProcessRaisedException(msg, error_index, failed_process.pid)
+torch.multiprocessing.spawn.ProcessRaisedException: 
+
+-- Process 0 terminated with the following error:
+Traceback (most recent call last):
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap
+    fn(i, *args)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint
+    worker_output = worker(*worker_args)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 55, in run
+    backend: Backend = backend_factory(backend_config)
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 81, in __init__
+    self.load_model_with_no_weights()
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 246, in load_model_with_no_weights
+    self.load_model_from_pretrained()
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 204, in load_model_from_pretrained
+    self.pretrained_model = self.automodel_class.from_pretrained(
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/auto/auto_factory.py", line 564, in from_pretrained
+    return model_class.from_pretrained(
+  File "/opt/conda/lib/python3.9/site-packages/transformers/modeling_utils.py", line 3810, in from_pretrained
+    model = cls(config, *model_args, **model_kwargs)
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 1116, in __init__
+    self.model = LlamaModel(config)
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 902, in __init__
+    [LlamaDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 902, in <listcomp>
+    [LlamaDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 691, in __init__
+    self.mlp = LlamaMLP(config)
+  File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 287, in __init__
+    self.up_proj = nn.Linear(self.hidden_size, self.intermediate_size, bias=config.mlp_bias)
+  File "/opt/conda/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 99, in __init__
+    self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
+  File "/opt/conda/lib/python3.9/site-packages/torch/utils/_device.py", line 79, in __torch_function__
+    return func(*args, **kwargs)
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 224.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 69.50 MiB is free. Process 28976 has 22.12 GiB memory in use. Of the allocated memory 21.83 GiB is allocated by PyTorch, and 1.24 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
+
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

runs/text_generation/meta-llama/Llama-3.1-8B-Instruct/2024-10-23-20-30-04/experiment_config.json

@@ -0,0 +1,110 @@
+{
+    "experiment_name": "text_generation",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-generation",
+        "model": "meta-llama/Llama-3.1-8B-Instruct",
+        "processor": "meta-llama/Llama-3.1-8B-Instruct",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": false,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/text_generation",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {
+            "max_new_tokens": 10,
+            "min_new_tokens": 10
+        },
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}