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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 1869, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 578, 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 399, 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 1885, 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 597, in finalize
self._build_writer(self.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 399, 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 1392, 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 1041, 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 999, 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 1740, 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 1896, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
config
dict | report
dict | name
string | backend
dict | scenario
dict | launcher
dict | environment
dict | print_report
bool | log_report
bool | load
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",
"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": {},
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"no_weights": false,
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"eval_mode": true,
"to_bettertransformer": false,
"low_cpu_mem_usage": null,
"attn_implementation": null,
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"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": {
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"sequence_length": 16
},
"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": " AMD EPYC 7763 64-Core Processor",
"cpu_count": 4,
"cpu_ram_mb": 16766.779392,
"system": "Linux",
"machine": "x86_64",
"platform": "Linux-6.8.0-1015-azure-x86_64-with-glibc2.34",
"processor": "x86_64",
"python_version": "3.8.18",
"optimum_benchmark_version": "0.5.0.dev0",
"optimum_benchmark_commit": "08c9f59440cf4e5a5d6711ec19e8329ab2de652d",
"transformers_version": "4.45.2",
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"accelerate_version": "1.0.1",
"accelerate_commit": null,
"diffusers_version": "0.30.3",
"diffusers_commit": null,
"optimum_version": null,
"optimum_commit": null,
"timm_version": "1.0.9",
"timm_commit": null,
"peft_version": null,
"peft_commit": null
},
"print_report": true,
"log_report": true
} | {
"load": {
"memory": {
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"max_ram": 550.465536,
"max_global_vram": null,
"max_process_vram": null,
"max_reserved": null,
"max_allocated": null
},
"latency": {
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"values": [
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],
"count": 1,
"total": 1.6214233000000036,
"mean": 1.6214233000000036,
"p50": 1.6214233000000036,
"p90": 1.6214233000000036,
"p95": 1.6214233000000036,
"p99": 1.6214233000000036,
"stdev": 0,
"stdev_": 0
},
"throughput": null,
"energy": null,
"efficiency": null
},
"forward": {
"memory": {
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"max_ram": 924.143616,
"max_global_vram": null,
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"max_reserved": null,
"max_allocated": null
},
"latency": {
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"values": [
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"total": 1.0445814419999806,
"mean": 0.09496194927272551,
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"stdev": 0.00544947890213703,
"stdev_": 5.738592082273317
},
"throughput": {
"unit": "samples/s",
"value": 21.06106725185379
},
"energy": null,
"efficiency": null
}
} | null | null | null | null | null | null | null | null | null |
null | null | test_api_push_to_hub_mixin | {
"name": "pytorch",
"version": "2.4.1+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": false,
"device_map": null,
"torch_dtype": null,
"eval_mode": true,
"to_bettertransformer": false,
"low_cpu_mem_usage": null,
"attn_implementation": null,
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"autocast_enabled": false,
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"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,
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"sequence_length": 16
},
"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": " AMD EPYC 7763 64-Core Processor",
"cpu_count": 4,
"cpu_ram_mb": 16766.779392,
"system": "Linux",
"machine": "x86_64",
"platform": "Linux-6.8.0-1015-azure-x86_64-with-glibc2.34",
"processor": "x86_64",
"python_version": "3.8.18",
"optimum_benchmark_version": "0.5.0.dev0",
"optimum_benchmark_commit": "08c9f59440cf4e5a5d6711ec19e8329ab2de652d",
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"accelerate_version": "1.0.1",
"accelerate_commit": null,
"diffusers_version": "0.30.3",
"diffusers_commit": null,
"optimum_version": null,
"optimum_commit": null,
"timm_version": "1.0.9",
"timm_commit": null,
"peft_version": null,
"peft_commit": null
} | true | true | null | null |
null | null | null | null | null | null | null | null | null | {
"memory": {
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"max_reserved": null,
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},
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],
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"stdev_": 0
},
"throughput": null,
"energy": null,
"efficiency": null
} | {
"memory": {
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},
"latency": {
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"value": 21.06106725185379
},
"energy": null,
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} |