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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 5 new columns ({'experiment_name', 'backend', 'environment', 'launcher', 'benchmark'}) and 1 missing columns ({'forward'}).

This happened while the json dataset builder was generating data using

hf://datasets/IlyasMoutawwakil/optimum-benchmarks-ci/test_api_push_to_hub_mixin/experiment_config.json (at revision 335baeadc78a580f719398da485c6f12328e814b)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
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 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              experiment_name: string
              backend: struct<name: string, version: string, _target_: string, task: string, model: string, library: string, device: string, device_ids: null, seed: int64, inter_op_num_threads: null, intra_op_num_threads: null, hub_kwargs: struct<revision: string, force_download: bool, local_files_only: bool, trust_remote_code: bool>, no_weights: bool, device_map: null, torch_dtype: null, amp_autocast: bool, amp_dtype: null, eval_mode: bool, to_bettertransformer: bool, low_cpu_mem_usage: null, attn_implementation: null, cache_implementation: null, torch_compile: bool, torch_compile_config: struct<>, quantization_scheme: null, quantization_config: struct<>, deepspeed_inference: bool, deepspeed_inference_config: struct<>, peft_type: null, peft_config: struct<>>
                child 0, name: string
                child 1, version: string
                child 2, _target_: string
                child 3, task: string
                child 4, model: string
                child 5, library: string
                child 6, device: string
                child 7, device_ids: null
                child 8, seed: int64
                child 9, inter_op_num_threads: null
                child 10, intra_op_num_threads: null
                child 11, hub_kwargs: struct<revision: string, force_download: bool, local_files_only: bool, trust_remote_code: bool>
                    child 0, revision: string
                    child 1, force_download: bool
                    child 2, local_files_only: bool
                    child 3, trust_remote_code: bool
                child 12, no_weights: bool
                child 13, device_map: null
                child 14, torch_dtype: null
                child 15, amp_autocast: bool
                child 16, amp_dtype: null
              ...
              nerate_kwargs: struct<>
                child 11, call_kwargs: struct<>
              environment: struct<cpu: string, cpu_count: int64, cpu_ram_mb: double, system: string, machine: string, platform: string, processor: string, python_version: string, gpu: list<item: string>, gpu_count: int64, gpu_vram_mb: int64, optimum_benchmark_version: string, optimum_benchmark_commit: string, transformers_version: string, transformers_commit: null, accelerate_version: string, accelerate_commit: null, diffusers_version: string, diffusers_commit: null, optimum_version: null, optimum_commit: null, timm_version: string, timm_commit: null, peft_version: string, peft_commit: null>
                child 0, cpu: string
                child 1, cpu_count: int64
                child 2, cpu_ram_mb: double
                child 3, system: string
                child 4, machine: string
                child 5, platform: string
                child 6, processor: string
                child 7, python_version: string
                child 8, gpu: list<item: string>
                    child 0, item: string
                child 9, gpu_count: int64
                child 10, gpu_vram_mb: int64
                child 11, optimum_benchmark_version: string
                child 12, optimum_benchmark_commit: string
                child 13, transformers_version: string
                child 14, transformers_commit: null
                child 15, accelerate_version: string
                child 16, accelerate_commit: null
                child 17, diffusers_version: string
                child 18, diffusers_commit: null
                child 19, optimum_version: null
                child 20, optimum_commit: null
                child 21, timm_version: string
                child 22, timm_commit: null
                child 23, peft_version: string
                child 24, peft_commit: null
              to
              {'forward': {'memory': {'unit': Value(dtype='string', id=None), 'max_ram': Value(dtype='float64', id=None), 'max_vram': Value(dtype='null', id=None), 'max_reserved': Value(dtype='null', id=None), 'max_allocated': Value(dtype='null', id=None)}, 'latency': {'unit': Value(dtype='string', id=None), 'mean': Value(dtype='float64', id=None), 'stdev': Value(dtype='float64', id=None), 'values': Sequence(feature=Value(dtype='float64', id=None), length=-1, id=None)}, 'throughput': {'unit': Value(dtype='string', id=None), 'value': Value(dtype='float64', id=None)}, 'energy': Value(dtype='null', id=None), 'efficiency': Value(dtype='null', id=None)}}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, 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 935, 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 2013, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 5 new columns ({'experiment_name', 'backend', 'environment', 'launcher', 'benchmark'}) and 1 missing columns ({'forward'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/IlyasMoutawwakil/optimum-benchmarks-ci/test_api_push_to_hub_mixin/experiment_config.json (at revision 335baeadc78a580f719398da485c6f12328e814b)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

forward
dict
experiment_name
string
backend
dict
launcher
dict
benchmark
dict
environment
dict
{ "memory": { "unit": "MB", "max_ram": 1084.637184, "max_vram": null, "max_reserved": null, "max_allocated": null }, "latency": { "unit": "s", "mean": 0.039569467664338075, "stdev": 0.002033212140164305, "values": [ 0.041925519704818726, 0.04176455829292536, 0.041776430793106556, 0.041355191729962826, 0.04157991334795952, 0.04103707615286112, 0.04141983296722174, 0.04134945012629032, 0.04154875408858061, 0.04141546320170164, 0.04227675963193178, 0.03971706051379442, 0.038739739917218685, 0.0426051439717412, 0.0376142505556345, 0.03715469967573881, 0.037393887527287006, 0.03790341317653656, 0.03759381361305714, 0.03753022290766239, 0.03781145066022873, 0.0375981405377388, 0.03772352542728186, 0.03696391265839338, 0.038118516094982624, 0.03688943199813366 ] }, "throughput": { "unit": "samples/s", "value": 50.544020884124684 }, "energy": null, "efficiency": null }
null
null
null
null
null
null
test_api_push_to_hub_mixin
{ "name": "pytorch", "version": "2.2.2+cu118", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "fill-mask", "model": "google-bert/bert-base-uncased", "library": "transformers", "device": "cpu", "device_ids": null, "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "hub_kwargs": { "revision": "main", "force_download": false, "local_files_only": false, "trust_remote_code": false }, "no_weights": false, "device_map": null, "torch_dtype": null, "amp_autocast": false, "amp_dtype": null, "eval_mode": true, "to_bettertransformer": false, "low_cpu_mem_usage": null, "attn_implementation": null, "cache_implementation": null, "torch_compile": false, "torch_compile_config": {}, "quantization_scheme": null, "quantization_config": {}, "deepspeed_inference": false, "deepspeed_inference_config": {}, "peft_type": null, "peft_config": {} }
{ "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": false, "start_method": "spawn" }
{ "name": "inference", "_target_": "optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark", "duration": 1, "warmup_runs": 1, "input_shapes": { "batch_size": 2, "num_choices": 2, "sequence_length": 16 }, "new_tokens": null, "latency": true, "memory": true, "energy": false, "forward_kwargs": {}, "generate_kwargs": {}, "call_kwargs": {} }
{ "cpu": " AMD EPYC 7742 64-Core Processor", "cpu_count": 128, "cpu_ram_mb": 540671.627264, "system": "Linux", "machine": "x86_64", "platform": "Linux-5.4.0-166-generic-x86_64-with-glibc2.35", "processor": "x86_64", "python_version": "3.10.12", "gpu": [ "NVIDIA A100-SXM4-80GB", "NVIDIA A100-SXM4-80GB", "NVIDIA A100-SXM4-80GB", "NVIDIA DGX Display", "NVIDIA A100-SXM4-80GB" ], "gpu_count": 5, "gpu_vram_mb": 347892350976, "optimum_benchmark_version": "0.2.0", "optimum_benchmark_commit": "379b5ada9deda73c472324db992fcbbba8f48fa4", "transformers_version": "4.39.3", "transformers_commit": null, "accelerate_version": "0.29.1", "accelerate_commit": null, "diffusers_version": "0.27.2", "diffusers_commit": null, "optimum_version": null, "optimum_commit": null, "timm_version": "0.9.16", "timm_commit": null, "peft_version": "0.10.0", "peft_commit": null }