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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 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
dict
prefill
dict
decode
dict
per_token
dict
{ "name": "2024-10-10-13-15-21/openvino", "backend": { "name": "openvino", "version": "2024.4.0", "_target_": "optimum_benchmark.backends.openvino.backend.OVBackend", "task": "text-generation", "library": "transformers", "model_type": "llama", "model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "processor": "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "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": true, "use_cache": true, "use_merged": true, "openvino_config": {}, "half": false, "reshape": false, "quantization": false, "quantization_config": {}, "calibration": false, "calibration_config": {} }, "scenario": { "name": "inference", "_target_": "optimum_benchmark.scenarios.inference.scenario.InferenceScenario", "iterations": 10, "duration": 10, "warmup_runs": 10, "input_shapes": { "batch_size": 2, "num_choices": 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": {} }, "launcher": { "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" }, "environment": { "cpu": " AMD EPYC 7R13 Processor", "cpu_count": 64, "cpu_ram_mb": 529717.026816, "system": "Linux", "machine": "x86_64", "platform": "Linux-5.10.205-195.807.amzn2.x86_64-x86_64-with-glibc2.36", "processor": "", "python_version": "3.10.15", "optimum_benchmark_version": "0.5.0", "optimum_benchmark_commit": null, "transformers_version": "4.44.2", "transformers_commit": null, "accelerate_version": "0.34.2", "accelerate_commit": null, "diffusers_version": null, "diffusers_commit": null, "optimum_version": "1.22.0", "optimum_commit": null, "timm_version": null, "timm_commit": null, "peft_version": null, "peft_commit": null }, "print_report": false, "log_report": true }
{ "load": { "memory": { "unit": "MB", "max_ram": 4841.96352, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 25.399079136550426 ], "count": 1, "total": 25.399079136550426, "mean": 25.399079136550426, "p50": 25.399079136550426, "p90": 25.399079136550426, "p95": 25.399079136550426, "p99": 25.399079136550426, "stdev": 0, "stdev_": 0 }, "throughput": null, "energy": null, "efficiency": null }, "prefill": { "memory": { "unit": "MB", "max_ram": 3465.314304, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 0.20681462809443474, 0.14498980715870857, 0.1491953432559967, 0.14298798888921738, 0.27635738253593445, 0.14056112617254257, 0.2304190769791603, 0.27384644746780396, 0.17013894766569138, 0.17990026250481606 ], "count": 10, "total": 1.915211010724306, "mean": 0.19152110107243062, "p50": 0.17501960508525372, "p90": 0.274097540974617, "p95": 0.27522746175527574, "p99": 0.2761313983798027, "stdev": 0.05022236084794941, "stdev_": 26.22288644265679 }, "throughput": { "unit": "tokens/s", "value": 167.08341702723422 }, "energy": null, "efficiency": null }, "decode": { "memory": { "unit": "MB", "max_ram": 3465.314304, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 3.7909555956721306, 1.7467840760946274, 1.8483475632965565, 3.0832476131618023, 3.204444296658039, 3.070590779185295, 4.489215832203627, 2.3151063695549965, 2.322327557951212, 2.0380597300827503 ], "count": 10, "total": 27.909079413861036, "mean": 2.7909079413861035, "p50": 2.6964591685682535, "p90": 3.8607816193252797, "p95": 4.1749987257644525, "p99": 4.426372410915792, "stdev": 0.8491402797309818, "stdev_": 30.425234280900593 }, "throughput": { "unit": "tokens/s", "value": 22.214992863292984 }, "energy": null, "efficiency": null }, "per_token": { 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0.09655871242284775, 0.0676942951977253, 0.03991246968507767, 0.056575048714876175, 0.09936098754405975, 0.0999956950545311, 0.03706963360309601, 0.06787383928894997, 0.09511307999491692, 0.027143824845552444, 0.0967935062944889, 0.02895590290427208, 0.07179578021168709, 0.031422000378370285, 0.08785632625222206, 0.06475986167788506, 0.03221173584461212, 0.09412364661693573, 0.09305229783058167, 0.09938482940196991, 0.1084253266453743, 0.07635966688394547, 0.09564392268657684, 0.02892351895570755, 0.07740995660424232, 0.03868601471185684, 0.06123805791139603, 0.034528590738773346, 0.05639708787202835, 0.03693850338459015 ], "count": 310, "total": 27.817084301263094, "mean": 0.0897325300040745, "p50": 0.07614360377192497, "p90": 0.17336186543107035, "p95": 0.1786521352827549, "p99": 0.1821156838908792, "stdev": 0.04931600958951952, "stdev_": 54.958897946241144 }, "throughput": { "unit": "tokens/s", "value": 22.288461050960958 }, "energy": null, "efficiency": null } }
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2024-10-10-13-15-21/openvino
{ "name": "openvino", "version": "2024.4.0", "_target_": "optimum_benchmark.backends.openvino.backend.OVBackend", "task": "text-generation", "library": "transformers", "model_type": "llama", "model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "processor": "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "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": true, "use_cache": true, "use_merged": true, "openvino_config": {}, "half": false, "reshape": false, "quantization": false, "quantization_config": {}, "calibration": false, "calibration_config": {} }
{ "name": "inference", "_target_": "optimum_benchmark.scenarios.inference.scenario.InferenceScenario", "iterations": 10, "duration": 10, "warmup_runs": 10, "input_shapes": { "batch_size": 2, "num_choices": 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": {} }
{ "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": 529717.026816, "system": "Linux", "machine": "x86_64", "platform": "Linux-5.10.205-195.807.amzn2.x86_64-x86_64-with-glibc2.36", "processor": "", "python_version": "3.10.15", "optimum_benchmark_version": "0.5.0", "optimum_benchmark_commit": null, "transformers_version": "4.44.2", "transformers_commit": null, "accelerate_version": "0.34.2", "accelerate_commit": null, "diffusers_version": null, "diffusers_commit": null, "optimum_version": "1.22.0", "optimum_commit": null, "timm_version": null, "timm_commit": null, "peft_version": null, "peft_commit": null }
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{ "memory": { "unit": "MB", "max_ram": 4841.96352, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 25.399079136550426 ], "count": 1, "total": 25.399079136550426, "mean": 25.399079136550426, "p50": 25.399079136550426, "p90": 25.399079136550426, "p95": 25.399079136550426, "p99": 25.399079136550426, "stdev": 0, "stdev_": 0 }, "throughput": null, "energy": null, "efficiency": null }
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2024-10-10-13-15-21/pytorch
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2024-10-10-13-27-38/openvino
{ "name": "openvino", "version": "2024.4.0", "_target_": "optimum_benchmark.backends.openvino.backend.OVBackend", "task": "text-generation", "library": "transformers", "model_type": "qwen2", "model": "Qwen/Qwen2.5-7B-Instruct", "processor": "Qwen/Qwen2.5-7B-Instruct", "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": true, "use_cache": true, "use_merged": true, "openvino_config": {}, "half": false, "reshape": false, "quantization": false, "quantization_config": {}, "calibration": false, "calibration_config": {} }
{ "name": "inference", "_target_": "optimum_benchmark.scenarios.inference.scenario.InferenceScenario", "iterations": 10, "duration": 10, "warmup_runs": 10, "input_shapes": { "batch_size": 2, "num_choices": 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": {} }
{ "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" }
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2024-10-10-13-27-38/pytorch
{ "name": "pytorch", "version": "2.4.1", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "text-generation", "library": "transformers", "model_type": "qwen2", "model": "Qwen/Qwen2.5-7B-Instruct", "processor": "Qwen/Qwen2.5-7B-Instruct", "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": "float32", "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": 10, "duration": 10, "warmup_runs": 10, "input_shapes": { "batch_size": 2, "num_choices": 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": {} }
{ "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": 529717.026816, "system": "Linux", "machine": "x86_64", "platform": "Linux-5.10.205-195.807.amzn2.x86_64-x86_64-with-glibc2.36", "processor": "", "python_version": "3.10.15", "optimum_benchmark_version": "0.5.0", "optimum_benchmark_commit": null, "transformers_version": "4.44.2", "transformers_commit": null, "accelerate_version": "0.34.2", "accelerate_commit": null, "diffusers_version": null, "diffusers_commit": null, "optimum_version": "1.22.0", "optimum_commit": null, "timm_version": null, "timm_commit": null, "peft_version": null, "peft_commit": null }
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{ "memory": { "unit": "MB", "max_ram": 32586.477568, "max_global_vram": null, "max_process_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "values": [ 7.114257633686066, 6.9122952707111835, 7.246219478547573, 7.030736085027456, 7.265082646161318, 6.757320333272219, 6.376978535205126, 7.046132210642099, 6.656667198985815, 6.604565516114235 ], "count": 10, "total": 69.01025490835309, "mean": 6.901025490835309, "p50": 6.97151567786932, "p90": 7.248105795308947, "p95": 7.256594220735133, "p99": 7.263384961076081, "stdev": 0.27893514120336665, "stdev_": 4.041937558031016 }, "throughput": { "unit": "tokens/s", "value": 4.63699200104341 }, "energy": null, "efficiency": null }
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