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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 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 583, 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 404, 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 2027, 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 602, in finalize
                  self._build_writer(self.schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, 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 1529, 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 1154, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2038, 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": "pytorch-llama-3.1-8b-Pruned-8-Layers", "backend": { "name": "pytorch", "version": "2.3.1", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "text-generation", "library": "transformers", "model_type": "llama", "model": "Na0s/Llama-3.1-8b-Pruned-8-Layers", "processor": "Na0s/Llama-3.1-8b-Pruned-8-Layers", "device": "cuda", "device_ids": "0,1", "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": false, "device_map": null, "torch_dtype": "bfloat16", "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": 10, "duration": 10, "warmup_runs": 10, "input_shapes": { "batch_size": 1, "num_choices": 2, "sequence_length": 128 }, "new_tokens": null, "memory": true, "latency": true, "energy": false, "forward_kwargs": {}, "generate_kwargs": { "max_new_tokens": 32, "min_new_tokens": 32 }, "call_kwargs": {} }, "launcher": { "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": true, "device_isolation_action": "warn", "numactl": false, "numactl_kwargs": {}, "start_method": "spawn" }, "environment": { "cpu": " Intel(R) Xeon(R) Gold 6326 CPU @ 2.90GHz", "cpu_count": 64, "cpu_ram_mb": 540228.182016, "system": "Linux", "machine": "x86_64", "platform": "Linux-5.10.194-release-94a7f6a-81353a4-x86_64-with-glibc2.31", "processor": "x86_64", "python_version": "3.9.5", "gpu": [ "NVIDIA A100 80GB PCIe", "NVIDIA A100-SXM4-80GB", "NVIDIA A100-SXM4-80GB" ], "gpu_count": 3, "gpu_vram_mb": 257698037760, "optimum_benchmark_version": "0.4.0", "optimum_benchmark_commit": null, "transformers_version": "4.43.3", "transformers_commit": null, "accelerate_version": "0.30.1", "accelerate_commit": null, "diffusers_version": null, "diffusers_commit": null, "optimum_version": null, "optimum_commit": null, "timm_version": null, "timm_commit": null, "peft_version": "0.12.0", "peft_commit": null } }
{ "load": { "memory": { "unit": "MB", "max_ram": 11876.569088, "max_global_vram": 14558.363648, "max_process_vram": 12666.79808, "max_reserved": 12232.687616, "max_allocated": 12134.518784 }, "latency": { "unit": "s", "count": 1, "total": 301.71565625, "mean": 301.71565625, "stdev": 0, "p50": 301.71565625, "p90": 301.71565625, "p95": 301.71565625, "p99": 301.71565625, "values": [ 301.71565625 ] }, "throughput": null, "energy": null, "efficiency": null }, "prefill": { "memory": { "unit": "MB", "max_ram": 1389.682688, "max_global_vram": 14799.536128, "max_process_vram": 12907.97056, "max_reserved": 12375.293952, "max_allocated": 12255.37536 }, "latency": { "unit": "s", "count": 16, "total": 0.341931324005127, "mean": 0.021370707750320433, "stdev": 0.002389243384095591, "p50": 0.02158123207092285, "p90": 0.024290399551391603, "p95": 0.024340367794036866, "p99": 0.024457142162322996, "values": [ 0.018755231857299805, 0.024289087295532228, 0.021667360305786133, 0.02304252815246582, 0.020193567276000978, 0.017117919921875, 0.020714111328125, 0.02448633575439453, 0.023028736114501954, 0.02385055923461914, 0.01711801528930664, 0.022670303344726563, 0.019730655670166016, 0.019480096817016603, 0.02149510383605957, 0.024291711807250975 ] }, "throughput": { "unit": "tokens/s", "value": 5989.506828480248 }, "energy": null, "efficiency": null }, "decode": { "memory": { "unit": "MB", "max_ram": 1438.65856, "max_global_vram": 14799.536128, "max_process_vram": 12907.97056, "max_reserved": 12375.293952, "max_allocated": 12255.376896 }, "latency": { "unit": "s", "count": 16, "total": 9.814378601074218, "mean": 0.6133986625671387, "stdev": 0.04584221611709868, "p50": 0.6375702514648438, "p90": 0.6548684692382812, "p95": 0.6558433990478515, "p99": 0.6560217071533203, "values": [ 0.6469893798828125, 0.6527512817382812, 0.5436505126953125, 0.6539678344726563, 0.5943348388671875, 0.61285888671875, 0.65270849609375, 0.5438873291015625, 0.6530720825195313, 0.628151123046875, 0.5757323608398438, 0.6557691040039062, 0.5473909912109375, 0.6560662841796875, 0.6536150512695312, 0.5434330444335937 ] }, "throughput": { "unit": "tokens/s", "value": 50.538095192874565 }, "energy": null, "efficiency": null }, "per_token": { "memory": null, "latency": { "unit": "s", "count": 496, "total": 9.804428284645084, "mean": 0.019766992509365082, "stdev": 0.0029064483104260996, "p50": 0.02035916805267334, "p90": 0.023079423904418944, "p95": 0.023419392108917234, "p99": 0.023630847454071045, "values": [ 0.01701171112060547, 0.01785241508483887, 0.023173120498657225, 0.01905971145629883, 0.022991872787475585, 0.019346431732177736, 0.022803455352783202, 0.019487743377685548, 0.02228121566772461, 0.019903488159179687, 0.021995519638061522, 0.020215808868408205, 0.02166988754272461, 0.02028339195251465, 0.021517311096191406, 0.02104832077026367, 0.02087936019897461, 0.021202943801879884, 0.020706304550170897, 0.02171801567077637, 0.020732927322387695, 0.022220800399780274, 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