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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowNotImplementedError
Message:      Cannot write struct type 'model_kwargs' with no child field to Parquet. Consider adding a dummy child field.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 620, in write_table
                  self._build_writer(inferred_schema=pa_table.schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer
                  self.pa_writer = self._WRITER_CLASS(self.stream, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
                  self.writer = _parquet.ParquetWriter(
                File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'model_kwargs' with no child field to Parquet. Consider adding a dummy child field.
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1886, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 639, in finalize
                  self._build_writer(self.schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer
                  self.pa_writer = self._WRITER_CLASS(self.stream, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
                  self.writer = _parquet.ParquetWriter(
                File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'model_kwargs' with no child field to Parquet. Consider adding a dummy child field.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1897, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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config
dict
report
dict
name
string
backend
dict
scenario
dict
launcher
dict
environment
dict
print_report
bool
log_report
bool
overall
dict
warmup
dict
train
dict
{ "name": "cpu_training_transformers_fill-mask_google-bert/bert-base-uncased", "backend": { "name": "pytorch", "version": "2.5.1+cpu", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "fill-mask", "library": "transformers", "model_type": "bert", "model": "google-bert/bert-base-uncased", "processor": "google-bert/bert-base-uncased", "device": "cpu", "device_ids": null, "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": true, "device_map": null, "torch_dtype": null, "eval_mode": true, "to_bettertransformer": false, "low_cpu_mem_usage": null, "attn_implementation": null, "cache_implementation": null, "autocast_enabled": false, "autocast_dtype": null, "torch_compile": false, "torch_compile_target": "forward", "torch_compile_config": {}, "quantization_scheme": null, "quantization_config": {}, "deepspeed_inference": false, "deepspeed_inference_config": {}, "peft_type": null, "peft_config": {} }, "scenario": { "name": "training", "_target_": "optimum_benchmark.scenarios.training.scenario.TrainingScenario", "max_steps": 5, "warmup_steps": 2, "dataset_shapes": { "dataset_size": 500, "sequence_length": 16, "num_choices": 1 }, "training_arguments": { "per_device_train_batch_size": 2, "gradient_accumulation_steps": 1, "output_dir": "./trainer_output", "evaluation_strategy": "no", "eval_strategy": "no", "save_strategy": "no", "do_train": true, "use_cpu": false, "max_steps": 5, "do_eval": false, "do_predict": false, "report_to": "none", "skip_memory_metrics": true, "ddp_find_unused_parameters": false }, "latency": true, "memory": true, "energy": true }, "launcher": { "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": false, "device_isolation_action": null, "numactl": false, "numactl_kwargs": {}, "start_method": "spawn" }, "environment": { "cpu": " AMD EPYC 7763 64-Core Processor", "cpu_count": 4, "cpu_ram_mb": 16766.779392, "system": "Linux", "machine": "x86_64", "platform": "Linux-6.8.0-1017-azure-x86_64-with-glibc2.39", "processor": "x86_64", "python_version": "3.10.15", "optimum_benchmark_version": "0.5.0.dev0", "optimum_benchmark_commit": "12b33198089c125596a4363f88200dc72e18e532", "transformers_version": "4.47.0", "transformers_commit": null, "accelerate_version": "1.2.0", "accelerate_commit": null, "diffusers_version": "0.31.0", "diffusers_commit": null, "optimum_version": null, "optimum_commit": null, "timm_version": "1.0.12", "timm_commit": null, "peft_version": null, "peft_commit": null }, "print_report": true, "log_report": true }
{ "overall": { "memory": { "unit": "MB", "max_ram": 2519.744512, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 0.6863499510000111, 0.5503289600000016, 0.5707251910000082, 0.5524302560000365, 0.5464166680000062 ], "count": 5, "total": 2.9062510260000636, "mean": 0.5812502052000127, "p50": 0.5524302560000365, "p90": 0.6401000470000099, "p95": 0.6632249990000104, "p99": 0.681724960600011, "stdev": 0.05321056414210851, "stdev_": 9.154502427022514 }, "throughput": { "unit": "samples/s", "value": 17.20429500159733 }, "energy": { "unit": "kWh", "cpu": 0.00012068394508333333, "ram": 0.000005047231533780827, "gpu": 0, "total": 0.00012573117661711416 }, "efficiency": { "unit": "samples/kWh", "value": 79534.76829738687 } }, "warmup": { "memory": { "unit": "MB", "max_ram": 2519.744512, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 0.6863499510000111, 0.5503289600000016 ], "count": 2, "total": 1.2366789110000127, "mean": 0.6183394555000064, "p50": 0.6183394555000064, "p90": 0.6727478519000101, "p95": 0.6795489014500106, "p99": 0.684989741090011, "stdev": 0.06801049550000471, "stdev_": 10.99889306675563 }, "throughput": { "unit": "samples/s", "value": 6.468938645950532 }, "energy": null, "efficiency": null }, "train": { "memory": { "unit": "MB", "max_ram": 2519.744512, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 0.5707251910000082, 0.5524302560000365, 0.5464166680000062 ], "count": 3, "total": 1.6695721150000509, "mean": 0.5565240383333503, "p50": 0.5524302560000365, "p90": 0.5670662040000138, "p95": 0.568895697500011, "p99": 0.5703592923000087, "stdev": 0.010337483992887902, "stdev_": 1.8575089808961478 }, "throughput": { "unit": "samples/s", "value": 10.781205458740818 }, "energy": null, "efficiency": null } }
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cpu_training_transformers_fill-mask_google-bert/bert-base-uncased
{ "name": "pytorch", "version": "2.5.1+cpu", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "fill-mask", "library": "transformers", "model_type": "bert", "model": "google-bert/bert-base-uncased", "processor": "google-bert/bert-base-uncased", "device": "cpu", "device_ids": null, "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": true, "device_map": null, "torch_dtype": null, "eval_mode": true, "to_bettertransformer": false, "low_cpu_mem_usage": null, "attn_implementation": null, "cache_implementation": null, "autocast_enabled": false, "autocast_dtype": null, "torch_compile": false, "torch_compile_target": "forward", "torch_compile_config": {}, "quantization_scheme": null, "quantization_config": {}, "deepspeed_inference": false, "deepspeed_inference_config": {}, "peft_type": null, "peft_config": {} }
{ "name": "training", "_target_": "optimum_benchmark.scenarios.training.scenario.TrainingScenario", "max_steps": 5, "warmup_steps": 2, "dataset_shapes": { "dataset_size": 500, "sequence_length": 16, "num_choices": 1 }, "training_arguments": { "per_device_train_batch_size": 2, "gradient_accumulation_steps": 1, "output_dir": "./trainer_output", "evaluation_strategy": "no", "eval_strategy": "no", "save_strategy": "no", "do_train": true, "use_cpu": false, "max_steps": 5, "do_eval": false, "do_predict": false, "report_to": "none", "skip_memory_metrics": true, "ddp_find_unused_parameters": false }, "latency": true, "memory": true, "energy": true }
{ "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": false, "device_isolation_action": null, "numactl": false, "numactl_kwargs": {}, "start_method": "spawn" }
{ "cpu": " AMD EPYC 7763 64-Core Processor", "cpu_count": 4, "cpu_ram_mb": 16766.779392, "system": "Linux", "machine": "x86_64", "platform": "Linux-6.8.0-1017-azure-x86_64-with-glibc2.39", "processor": "x86_64", "python_version": "3.10.15", "optimum_benchmark_version": "0.5.0.dev0", "optimum_benchmark_commit": "12b33198089c125596a4363f88200dc72e18e532", "transformers_version": "4.47.0", "transformers_commit": null, "accelerate_version": "1.2.0", "accelerate_commit": null, "diffusers_version": "0.31.0", "diffusers_commit": null, "optimum_version": null, "optimum_commit": null, "timm_version": "1.0.12", "timm_commit": null, "peft_version": null, "peft_commit": null }
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{ "memory": { "unit": "MB", "max_ram": 2519.744512, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 0.6863499510000111, 0.5503289600000016, 0.5707251910000082, 0.5524302560000365, 0.5464166680000062 ], "count": 5, "total": 2.9062510260000636, "mean": 0.5812502052000127, "p50": 0.5524302560000365, "p90": 0.6401000470000099, "p95": 0.6632249990000104, "p99": 0.681724960600011, "stdev": 0.05321056414210851, "stdev_": 9.154502427022514 }, "throughput": { "unit": "samples/s", "value": 17.20429500159733 }, "energy": { "unit": "kWh", "cpu": 0.00012068394508333333, "ram": 0.000005047231533780827, "gpu": 0, "total": 0.00012573117661711416 }, "efficiency": { "unit": "samples/kWh", "value": 79534.76829738687 } }
{ "memory": { "unit": "MB", "max_ram": 2519.744512, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 0.6863499510000111, 0.5503289600000016 ], "count": 2, "total": 1.2366789110000127, "mean": 0.6183394555000064, "p50": 0.6183394555000064, "p90": 0.6727478519000101, "p95": 0.6795489014500106, "p99": 0.684989741090011, "stdev": 0.06801049550000471, "stdev_": 10.99889306675563 }, "throughput": { "unit": "samples/s", "value": 6.468938645950532 }, "energy": null, "efficiency": null }
{ "memory": { "unit": "MB", "max_ram": 2519.744512, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 0.5707251910000082, 0.5524302560000365, 0.5464166680000062 ], "count": 3, "total": 1.6695721150000509, "mean": 0.5565240383333503, "p50": 0.5524302560000365, "p90": 0.5670662040000138, "p95": 0.568895697500011, "p99": 0.5703592923000087, "stdev": 0.010337483992887902, "stdev_": 1.8575089808961478 }, "throughput": { "unit": "samples/s", "value": 10.781205458740818 }, "energy": null, "efficiency": null }
{ "name": "cpu_training_transformers_fill-mask_google-bert/bert-base-uncased", "backend": { "name": "pytorch", "version": "2.3.0+cpu", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "fill-mask", "model": "google-bert/bert-base-uncased", "library": "transformers", "device": "cpu", "device_ids": null, "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": false }, "no_weights": true, "device_map": null, "torch_dtype": null, "eval_mode": true, "to_bettertransformer": false, "low_cpu_mem_usage": null, "attn_implementation": null, "cache_implementation": null, "autocast_enabled": false, "autocast_dtype": null, "torch_compile": false, "torch_compile_target": "forward", "torch_compile_config": {}, "quantization_scheme": null, "quantization_config": {}, "deepspeed_inference": false, "deepspeed_inference_config": {}, "peft_type": null, "peft_config": {} }, "scenario": { "name": "training", "_target_": "optimum_benchmark.scenarios.training.scenario.TrainingScenario", "max_steps": 5, "warmup_steps": 2, "dataset_shapes": { "dataset_size": 500, "sequence_length": 16, "num_choices": 1 }, "training_arguments": { "per_device_train_batch_size": 2, "gradient_accumulation_steps": 1, "output_dir": "./trainer_output", "do_train": true, "use_cpu": false, "max_steps": 5, "do_eval": false, "do_predict": false, "report_to": "none", "skip_memory_metrics": true, "ddp_find_unused_parameters": false }, "latency": true, "memory": true, "energy": false }, "launcher": { "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": false, "device_isolation_action": "error", "start_method": "spawn" }, "environment": { "cpu": " AMD EPYC 7763 64-Core Processor", "cpu_count": 4, "cpu_ram_mb": 16757.346304, "system": "Linux", "machine": "x86_64", "platform": "Linux-6.5.0-1018-azure-x86_64-with-glibc2.35", "processor": "x86_64", "python_version": "3.10.14", "optimum_benchmark_version": "0.2.0", "optimum_benchmark_commit": "2e77e02d1fd3ab0d2e788c3d89c12299219a25e8", "transformers_version": "4.40.2", "transformers_commit": null, "accelerate_version": "0.30.0", "accelerate_commit": null, "diffusers_version": "0.27.2", "diffusers_commit": null, "optimum_version": null, "optimum_commit": null, "timm_version": "0.9.16", "timm_commit": null, "peft_version": null, "peft_commit": null } }
{ "overall": { "memory": { "unit": "MB", "max_ram": 2488.782848, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "count": 5, "total": 2.738775005999969, "mean": 0.5477550011999938, "stdev": 0.03693447784258994, "p50": 0.5307143729999666, "p90": 0.5856752317999963, "p95": 0.6036043034000045, "p99": 0.6179475606800111, "values": [ 0.6215333750000127, 0.5307143729999666, 0.5270229210000252, 0.5276163199999928, 0.5318880169999716 ] }, "throughput": { "unit": "samples/s", "value": 18.25633719106628 }, "energy": null, "efficiency": null }, "warmup": { "memory": { "unit": "MB", "max_ram": 2488.782848, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "count": 2, "total": 1.1522477479999793, "mean": 0.5761238739999897, "stdev": 0.045409501000023056, "p50": 0.5761238739999897, "p90": 0.612451474800008, "p95": 0.6169924249000104, "p99": 0.6206251849800123, "values": [ 0.6215333750000127, 0.5307143729999666 ] }, "throughput": { "unit": "samples/s", "value": 6.942951300088064 }, "energy": null, "efficiency": null }, "train": { "memory": { "unit": "MB", "max_ram": 2488.782848, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "count": 3, "total": 1.5865272579999896, "mean": 0.5288424193333299, "stdev": 0.0021671455040491463, "p50": 0.5276163199999928, "p90": 0.5310336775999758, "p95": 0.5314608472999737, "p99": 0.531802583059972, "values": [ 0.5270229210000252, 0.5276163199999928, 0.5318880169999716 ] }, "throughput": { "unit": "samples/s", "value": 11.345534663357242 }, "energy": null, "efficiency": null } }
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cpu_training_transformers_token-classification_microsoft/deberta-v3-base
{ "name": "pytorch", "version": "2.5.1+cpu", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "token-classification", "library": "transformers", "model_type": "deberta-v2", "model": "microsoft/deberta-v3-base", "processor": "microsoft/deberta-v3-base", "device": "cpu", "device_ids": null, "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": true, "device_map": null, "torch_dtype": null, "eval_mode": true, "to_bettertransformer": false, "low_cpu_mem_usage": null, "attn_implementation": null, "cache_implementation": null, "autocast_enabled": false, "autocast_dtype": null, "torch_compile": false, "torch_compile_target": "forward", "torch_compile_config": {}, "quantization_scheme": null, "quantization_config": {}, "deepspeed_inference": false, "deepspeed_inference_config": {}, "peft_type": null, "peft_config": {} }
{ "name": "training", "_target_": "optimum_benchmark.scenarios.training.scenario.TrainingScenario", "max_steps": 5, "warmup_steps": 2, "dataset_shapes": { "dataset_size": 500, "sequence_length": 16, "num_choices": 1 }, "training_arguments": { "per_device_train_batch_size": 2, "gradient_accumulation_steps": 1, "output_dir": "./trainer_output", "evaluation_strategy": "no", "eval_strategy": "no", "save_strategy": "no", "do_train": true, "use_cpu": false, "max_steps": 5, "do_eval": false, "do_predict": false, "report_to": "none", "skip_memory_metrics": true, "ddp_find_unused_parameters": false }, "latency": true, "memory": true, "energy": true }
{ "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": false, "device_isolation_action": null, "numactl": false, "numactl_kwargs": {}, "start_method": "spawn" }
{ "cpu": " AMD EPYC 7763 64-Core Processor", "cpu_count": 4, "cpu_ram_mb": 16766.779392, "system": "Linux", "machine": "x86_64", "platform": "Linux-6.8.0-1017-azure-x86_64-with-glibc2.39", "processor": "x86_64", "python_version": "3.10.15", "optimum_benchmark_version": "0.5.0.dev0", "optimum_benchmark_commit": "12b33198089c125596a4363f88200dc72e18e532", "transformers_version": "4.47.0", "transformers_commit": null, "accelerate_version": "1.2.0", "accelerate_commit": null, "diffusers_version": "0.31.0", "diffusers_commit": null, "optimum_version": null, "optimum_commit": null, "timm_version": "1.0.12", "timm_commit": null, "peft_version": null, "peft_commit": null }
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{ "memory": { "unit": "MB", "max_ram": 4362.715136, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 1.3893911569999773, 1.1545377269999904, 1.156441610999991, 1.1526474670000084, 1.1748442610000325 ], "count": 5, "total": 6.027862223, "mean": 1.2055724446, "p50": 1.156441610999991, "p90": 1.3035723985999994, "p95": 1.3464817777999882, "p99": 1.3808092811599795, "stdev": 0.09225288587403972, "stdev_": 7.652205911578259 }, "throughput": { "unit": "samples/s", "value": 8.294814670650444 }, "energy": { "unit": "kWh", "cpu": 0.00024157405844444467, "ram": 0.00001010374289347771, "gpu": 0, "total": 0.00025167780133792235 }, "efficiency": { "unit": "samples/kWh", "value": 39733.34138664544 } }
{ "memory": { "unit": "MB", "max_ram": 4362.715136, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 1.3893911569999773, 1.1545377269999904 ], "count": 2, "total": 2.5439288839999676, "mean": 1.2719644419999838, "p50": 1.2719644419999838, "p90": 1.3659058139999787, "p95": 1.377648485499978, "p99": 1.3870426226999775, "stdev": 0.11742671499999346, "stdev_": 9.231918057029691 }, "throughput": { "unit": "samples/s", "value": 3.1447419974339588 }, "energy": null, "efficiency": null }
{ "memory": { "unit": "MB", "max_ram": 4362.715136, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 1.156441610999991, 1.1526474670000084, 1.1748442610000325 ], "count": 3, "total": 3.483933339000032, "mean": 1.1613111130000107, "p50": 1.156441610999991, "p90": 1.1711637310000242, "p95": 1.1730039960000282, "p99": 1.1744762080000317, "stdev": 0.009693931203456517, "stdev_": 0.834740242725674 }, "throughput": { "unit": "samples/s", "value": 5.16657417020683 }, "energy": null, "efficiency": null }
{ "name": "cpu_training_transformers_token-classification_microsoft/deberta-v3-base", "backend": { "name": "pytorch", "version": "2.3.0+cpu", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "token-classification", "model": "microsoft/deberta-v3-base", "library": "transformers", "device": "cpu", "device_ids": null, "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": false }, "no_weights": true, "device_map": null, "torch_dtype": null, "eval_mode": true, "to_bettertransformer": false, "low_cpu_mem_usage": null, "attn_implementation": null, "cache_implementation": null, "autocast_enabled": false, "autocast_dtype": null, "torch_compile": false, "torch_compile_target": "forward", "torch_compile_config": {}, "quantization_scheme": null, "quantization_config": {}, "deepspeed_inference": false, "deepspeed_inference_config": {}, "peft_type": null, "peft_config": {} }, "scenario": { "name": "training", "_target_": "optimum_benchmark.scenarios.training.scenario.TrainingScenario", "max_steps": 5, "warmup_steps": 2, "dataset_shapes": { "dataset_size": 500, "sequence_length": 16, "num_choices": 1 }, "training_arguments": { "per_device_train_batch_size": 2, "gradient_accumulation_steps": 1, "output_dir": "./trainer_output", "do_train": true, "use_cpu": false, "max_steps": 5, "do_eval": false, "do_predict": false, "report_to": "none", "skip_memory_metrics": true, "ddp_find_unused_parameters": false }, "latency": true, "memory": true, "energy": false }, "launcher": { "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": false, "device_isolation_action": "error", "start_method": "spawn" }, "environment": { "cpu": " AMD EPYC 7763 64-Core Processor", "cpu_count": 4, "cpu_ram_mb": 16757.346304, "system": "Linux", "machine": "x86_64", "platform": "Linux-6.5.0-1018-azure-x86_64-with-glibc2.35", "processor": "x86_64", "python_version": "3.10.14", "optimum_benchmark_version": "0.2.0", "optimum_benchmark_commit": "2e77e02d1fd3ab0d2e788c3d89c12299219a25e8", "transformers_version": "4.40.2", "transformers_commit": null, "accelerate_version": "0.30.0", "accelerate_commit": null, "diffusers_version": "0.27.2", "diffusers_commit": null, "optimum_version": null, "optimum_commit": null, "timm_version": "0.9.16", "timm_commit": null, "peft_version": null, "peft_commit": null } }
{ "overall": { "memory": { "unit": "MB", "max_ram": 4374.970368, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "count": 5, "total": 5.583659903000068, "mean": 1.1167319806000138, "stdev": 0.07853258776030796, "p50": 1.0731834320000075, "p90": 1.2025418994000006, "p95": 1.2374836681999908, "p99": 1.265437083239983, "values": [ 1.2724254369999812, 1.0731834320000075, 1.0977165930000297, 1.0711078369999996, 1.0692266040000504 ] }, "throughput": { "unit": "samples/s", "value": 8.954700119385008 }, "energy": null, "efficiency": null }, "warmup": { "memory": { "unit": "MB", "max_ram": 4374.970368, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "count": 2, "total": 2.3456088689999888, "mean": 1.1728044344999944, "stdev": 0.09962100249998684, "p50": 1.1728044344999944, "p90": 1.252501236499984, "p95": 1.2624633367499825, "p99": 1.2704330169499816, "values": [ 1.2724254369999812, 1.0731834320000075 ] }, "throughput": { "unit": "samples/s", "value": 3.4106283045436583 }, "energy": null, "efficiency": null }, "train": { "memory": { "unit": "MB", "max_ram": 4374.970368, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "count": 3, "total": 3.2380510340000797, "mean": 1.0793503446666932, "stdev": 0.01300958794585394, "p50": 1.0711078369999996, "p90": 1.0923948418000236, "p95": 1.0950557174000266, "p99": 1.097184417880029, "values": [ 1.0977165930000297, 1.0711078369999996, 1.0692266040000504 ] }, "throughput": { "unit": "samples/s", "value": 5.558899415419021 }, "energy": null, "efficiency": null } }
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