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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
load_model
dict
forward
dict
{ "name": "test_api_push_to_hub_mixin", "backend": { "name": "pytorch", "version": "2.4.1+cpu", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "model": "google-bert/bert-base-uncased", "processor": "google-bert/bert-base-uncased", "task": "fill-mask", "library": "transformers", "model_type": "bert", "device": "cpu", "device_ids": null, "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": false, "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": "inference", "_target_": "optimum_benchmark.scenarios.inference.scenario.InferenceScenario", "iterations": 1, "duration": 1, "warmup_runs": 1, "input_shapes": { "batch_size": 2, "sequence_length": 16, "num_choices": 2 }, "new_tokens": null, "memory": true, "latency": true, "energy": false, "forward_kwargs": {}, "generate_kwargs": {}, "call_kwargs": {} }, "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": "AMD64 Family 25 Model 1 Stepping 1, AuthenticAMD", "cpu_count": 4, "cpu_ram_mb": 17179.398144, "system": "Windows", "machine": "AMD64", "platform": "Windows-10-10.0.20348-SP0", "processor": "AMD64 Family 25 Model 1 Stepping 1, AuthenticAMD", "python_version": "3.8.10", "optimum_benchmark_version": "0.5.0.dev0", "optimum_benchmark_commit": "7cec62e016d76fe612308e4c2c074fc7f09289fd", "transformers_version": "4.46.3", "transformers_commit": null, "accelerate_version": "1.0.1", "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 }
{ "load_model": { "memory": { "unit": "MB", "max_ram": 460.791808, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 2.432603799999999 ], "count": 1, "total": 2.432603799999999, "mean": 2.432603799999999, "p50": 2.432603799999999, "p90": 2.432603799999999, "p95": 2.432603799999999, "p99": 2.432603799999999, "stdev": 0, "stdev_": 0 }, "throughput": null, "energy": null, "efficiency": null }, "forward": { "memory": { "unit": "MB", "max_ram": 919.51104, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 0.12024900000000116, 0.11798019999999809, 0.1035388000000026, 0.10325509999999838, 0.08399550000000033, 0.09575519999999926, 0.11496830000000102, 0.1183563999999997, 0.08443339999999822, 0.08353849999999952 ], "count": 10, "total": 1.0260703999999983, "mean": 0.10260703999999983, "p50": 0.10339695000000049, "p90": 0.11854565999999984, "p95": 0.1193973300000005, "p99": 0.12007866600000103, "stdev": 0.014272111230732758, "stdev_": 13.909485383003723 }, "throughput": { "unit": "samples/s", "value": 19.49183993612917 }, "energy": null, "efficiency": null } }
null
null
null
null
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test_api_push_to_hub_mixin
{ "name": "pytorch", "version": "2.4.1+cpu", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "model": "google-bert/bert-base-uncased", "processor": "google-bert/bert-base-uncased", "task": "fill-mask", "library": "transformers", "model_type": "bert", "device": "cpu", "device_ids": null, "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": false, "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": "inference", "_target_": "optimum_benchmark.scenarios.inference.scenario.InferenceScenario", "iterations": 1, "duration": 1, "warmup_runs": 1, "input_shapes": { "batch_size": 2, "sequence_length": 16, "num_choices": 2 }, "new_tokens": null, "memory": true, "latency": true, "energy": false, "forward_kwargs": {}, "generate_kwargs": {}, "call_kwargs": {} }
{ "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": false, "device_isolation_action": null, "numactl": false, "numactl_kwargs": {}, "start_method": "spawn" }
{ "cpu": "AMD64 Family 25 Model 1 Stepping 1, AuthenticAMD", "cpu_count": 4, "cpu_ram_mb": 17179.398144, "system": "Windows", "machine": "AMD64", "platform": "Windows-10-10.0.20348-SP0", "processor": "AMD64 Family 25 Model 1 Stepping 1, AuthenticAMD", "python_version": "3.8.10", "optimum_benchmark_version": "0.5.0.dev0", "optimum_benchmark_commit": "7cec62e016d76fe612308e4c2c074fc7f09289fd", "transformers_version": "4.46.3", "transformers_commit": null, "accelerate_version": "1.0.1", "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 }
true
true
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{ "memory": { "unit": "MB", "max_ram": 460.791808, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 2.432603799999999 ], "count": 1, "total": 2.432603799999999, "mean": 2.432603799999999, "p50": 2.432603799999999, "p90": 2.432603799999999, "p95": 2.432603799999999, "p99": 2.432603799999999, "stdev": 0, "stdev_": 0 }, "throughput": null, "energy": null, "efficiency": null }
{ "memory": { "unit": "MB", "max_ram": 919.51104, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 0.12024900000000116, 0.11798019999999809, 0.1035388000000026, 0.10325509999999838, 0.08399550000000033, 0.09575519999999926, 0.11496830000000102, 0.1183563999999997, 0.08443339999999822, 0.08353849999999952 ], "count": 10, "total": 1.0260703999999983, "mean": 0.10260703999999983, "p50": 0.10339695000000049, "p90": 0.11854565999999984, "p95": 0.1193973300000005, "p99": 0.12007866600000103, "stdev": 0.014272111230732758, "stdev_": 13.909485383003723 }, "throughput": { "unit": "samples/s", "value": 19.49183993612917 }, "energy": null, "efficiency": null }

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