Datasets:

IlyasMoutawwakil

/

optimum-benchmarks-ci

like 0

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)