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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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name
string
backend
dict
scenario
dict
launcher
dict
environment
dict
print_report
bool
log_report
bool
load_model
dict
prefill
dict
decode
dict
per_token
dict
2024-12-14-01:08:37/openvino
{ "name": "openvino", "version": "2024.5.0", "_target_": "optimum_benchmark.backends.openvino.backend.OVBackend", "task": "text-generation", "library": "transformers", "model_type": "gpt2", "model": "openai-community/gpt2", "processor": "openai-community/gpt2", "device": "cpu", "device_ids": null, "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": false, "export": null, "use_cache": null, "use_merged": null, "load_in_8bit": null, "load_in_4bit": null, "ov_config": {}, "half": false, "compile": false, "reshape": false, "reshape_kwargs": { "batch_size": 2, "sequence_length": 16 } }
{ "name": "inference", "_target_": "optimum_benchmark.scenarios.inference.scenario.InferenceScenario", "iterations": 10, "duration": 10, "warmup_runs": 10, "input_shapes": { "batch_size": 2, "sequence_length": 16 }, "new_tokens": null, "memory": true, "latency": true, "energy": false, "forward_kwargs": {}, "generate_kwargs": { "max_new_tokens": 32, "min_new_tokens": 32 }, "call_kwargs": { "num_inference_steps": 5 } }
{ "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": false, "device_isolation_action": null, "numactl": true, "numactl_kwargs": { "cpunodebind": 0, "membind": 0 }, "start_method": "spawn" }
{ "cpu": " AMD EPYC 7R13 Processor", "cpu_count": 64, "cpu_ram_mb": 529717.02272, "system": "Linux", "machine": "x86_64", "platform": "Linux-5.10.205-195.807.amzn2.x86_64-x86_64-with-glibc2.36", "processor": "", "python_version": "3.10.16", "optimum_benchmark_version": "0.5.0.dev0", "optimum_benchmark_commit": null, "transformers_version": "4.46.3", "transformers_commit": null, "accelerate_version": "1.2.0", "accelerate_commit": null, "diffusers_version": "0.31.0", "diffusers_commit": null, "optimum_version": "1.23.3", "optimum_commit": null, "timm_version": null, "timm_commit": null, "peft_version": null, "peft_commit": null }
false
true
null
null
null
null
null
null
null
null
null
null
null
{ "memory": { "unit": "MB", "max_ram": 2404.78208, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 13.756473794579506 ], "count": 1, "total": 13.756473794579506, "mean": 13.756473794579506, "p50": 13.756473794579506, "p90": 13.756473794579506, "p95": 13.756473794579506, "p99": 13.756473794579506, "stdev": 0, "stdev_": 0 }, "throughput": null, "energy": null, "efficiency": null }
{ "memory": { "unit": "MB", "max_ram": 2689.736704, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 0.07398736849427223, 0.029373228549957275, 0.024510670453310013, 0.0912763960659504, 0.07204390689730644, 0.08473370596766472, 0.20285411551594734, 0.07881861552596092, 0.02134433016180992, 0.09493869543075562 ], "count": 10, "total": 0.7738810330629349, "mean": 0.07738810330629349, "p50": 0.07640299201011658, "p90": 0.10573023743927475, "p95": 0.15429217647761095, "p99": 0.19314172770828011, "stdev": 0.04957934395182921, "stdev_": 64.06584711812833 }, "throughput": { "unit": "samples/s", "value": 25.843765573168564 }, "energy": null, "efficiency": null }
{ "memory": { "unit": "MB", "max_ram": 2689.736704, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 1.6019481234252453, 1.6740308925509453, 1.4961739405989647, 1.7275701612234116, 1.1958188526332378, 1.2044326961040497, 1.410125881433487, 1.5079566836357117, 1.7068905420601368, 1.6233145780861378 ], "count": 10, "total": 15.148262351751328, "mean": 1.5148262351751327, "p50": 1.5549524035304785, "p90": 1.7089585039764643, "p95": 1.7182643325999378, "p99": 1.7257089954987168, "stdev": 0.1833908026750199, "stdev_": 12.106392034715299 }, "throughput": { "unit": "tokens/s", "value": 40.92878678776779 }, "energy": null, "efficiency": null }
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2024-12-14-01:08:37/pytorch
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