Datasets:

---

petersonco

/

worldsimprobe_validation

Like 0

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
canonical_action_fps: double
canonical_video_fps: double
episode: int64
large_magnitude: double
model_input: struct<action_trajectories: struct<large: struct<duration_sec: double, fps: double, frame_action_ali (... 310 chars omitted)
  child 0, action_trajectories: struct<large: struct<duration_sec: double, fps: double, frame_action_alignment: string, frames: int6 (... 281 chars omitted)
      child 0, large: struct<duration_sec: double, fps: double, frame_action_alignment: string, frames: int64, key: string (... 15 chars omitted)
          child 0, duration_sec: double
          child 1, fps: double
          child 2, frame_action_alignment: string
          child 3, frames: int64
          child 4, key: string
          child 5, path: string
      child 1, original: struct<duration_sec: double, fps: double, frame_action_alignment: string, frames: int64, key: string (... 15 chars omitted)
          child 0, duration_sec: double
          child 1, fps: double
          child 2, frame_action_alignment: string
          child 3, frames: int64
          child 4, key: string
          child 5, path: string
      child 2, small: struct<duration_sec: double, fps: double, frame_action_alignment: string, frames: int64, key: string (... 15 chars omitted)
          child 0, duration_sec: double
          child 1, fps: double
          child 2, frame_action_alignment: string
          child 3, frames: int64
          child 4, key: string
          child 5, path: string
oracle_reference:
...
      child 1, evaluation_manifest: string
      child 2, evaluation_rows: int64
      child 3, manifest: string
      child 4, samples: int64
  child 2, task3: struct<artifact_manifest: string, categories_per_group: int64, episode_groups: int64, evaluation_man (... 56 chars omitted)
      child 0, artifact_manifest: string
      child 1, categories_per_group: int64
      child 2, episode_groups: int64
      child 3, evaluation_manifest: string
      child 4, evaluation_rows: int64
      child 5, manifest: string
  child 3, task4: struct<artifact_manifest: string, evaluation_manifest: string, evaluation_rows: int64, manifest: str (... 102 chars omitted)
      child 0, artifact_manifest: string
      child 1, evaluation_manifest: string
      child 2, evaluation_rows: int64
      child 3, manifest: string
      child 4, samples: int64
      child 5, subsets: struct<distractor: int64, no_gripper_close: int64, target_shift: int64>
          child 0, distractor: int64
          child 1, no_gripper_close: int64
          child 2, target_shift: int64
  child 4, task5: struct<actions: int64, artifact_manifest: string, evaluation_manifest: string, evaluation_rows: int6 (... 36 chars omitted)
      child 0, actions: int64
      child 1, artifact_manifest: string
      child 2, evaluation_manifest: string
      child 3, evaluation_rows: int64
      child 4, manifest: string
      child 5, samples: int64
action_video_timing_audited_pairs: int64
official_evaluator_preflight_videos: int64
to
{'action_representation': Value('string'), 'action_video_timing_audited_pairs': Value('int64'), 'action_video_timing_pass': Value('bool'), 'canonical_action_fps': Value('float64'), 'canonical_video_fps': Value('float64'), 'complete': Value('bool'), 'evaluation_reference_rows': Value('int64'), 'evaluation_schema_version': Value('string'), 'official_evaluator_preflight_videos': Value('int64'), 'official_evaluator_reference_pass': Value('bool'), 'official_evaluator_reference_rows': Value('int64'), 'release_layout': Value('string'), 'task1_official_mse_direction_passes': Value('int64'), 'tasks': {'task1': {'artifact_manifest': Value('string'), 'evaluation_manifest': Value('string'), 'evaluation_rows': Value('int64'), 'manifest': Value('string'), 'samples': Value('int64')}, 'task2': {'artifact_manifest': Value('string'), 'evaluation_manifest': Value('string'), 'evaluation_rows': Value('int64'), 'manifest': Value('string'), 'samples': Value('int64')}, 'task3': {'artifact_manifest': Value('string'), 'categories_per_group': Value('int64'), 'episode_groups': Value('int64'), 'evaluation_manifest': Value('string'), 'evaluation_rows': Value('int64'), 'manifest': Value('string')}, 'task4': {'artifact_manifest': Value('string'), 'evaluation_manifest': Value('string'), 'evaluation_rows': Value('int64'), 'manifest': Value('string'), 'samples': Value('int64'), 'subsets': {'distractor': Value('int64'), 'no_gripper_close': Value('int64'), 'target_shift': Value('int64')}}, 'task5': {'actions': Value('int64'), 'artifact_manifest': Value('string'), 'evaluation_manifest': Value('string'), 'evaluation_rows': Value('int64'), 'manifest': Value('string'), 'samples': Value('int64')}}, 'validation_root': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              canonical_action_fps: double
              canonical_video_fps: double
              episode: int64
              large_magnitude: double
              model_input: struct<action_trajectories: struct<large: struct<duration_sec: double, fps: double, frame_action_ali (... 310 chars omitted)
                child 0, action_trajectories: struct<large: struct<duration_sec: double, fps: double, frame_action_alignment: string, frames: int6 (... 281 chars omitted)
                    child 0, large: struct<duration_sec: double, fps: double, frame_action_alignment: string, frames: int64, key: string (... 15 chars omitted)
                        child 0, duration_sec: double
                        child 1, fps: double
                        child 2, frame_action_alignment: string
                        child 3, frames: int64
                        child 4, key: string
                        child 5, path: string
                    child 1, original: struct<duration_sec: double, fps: double, frame_action_alignment: string, frames: int64, key: string (... 15 chars omitted)
                        child 0, duration_sec: double
                        child 1, fps: double
                        child 2, frame_action_alignment: string
                        child 3, frames: int64
                        child 4, key: string
                        child 5, path: string
                    child 2, small: struct<duration_sec: double, fps: double, frame_action_alignment: string, frames: int64, key: string (... 15 chars omitted)
                        child 0, duration_sec: double
                        child 1, fps: double
                        child 2, frame_action_alignment: string
                        child 3, frames: int64
                        child 4, key: string
                        child 5, path: string
              oracle_reference:
              ...
                    child 1, evaluation_manifest: string
                    child 2, evaluation_rows: int64
                    child 3, manifest: string
                    child 4, samples: int64
                child 2, task3: struct<artifact_manifest: string, categories_per_group: int64, episode_groups: int64, evaluation_man (... 56 chars omitted)
                    child 0, artifact_manifest: string
                    child 1, categories_per_group: int64
                    child 2, episode_groups: int64
                    child 3, evaluation_manifest: string
                    child 4, evaluation_rows: int64
                    child 5, manifest: string
                child 3, task4: struct<artifact_manifest: string, evaluation_manifest: string, evaluation_rows: int64, manifest: str (... 102 chars omitted)
                    child 0, artifact_manifest: string
                    child 1, evaluation_manifest: string
                    child 2, evaluation_rows: int64
                    child 3, manifest: string
                    child 4, samples: int64
                    child 5, subsets: struct<distractor: int64, no_gripper_close: int64, target_shift: int64>
                        child 0, distractor: int64
                        child 1, no_gripper_close: int64
                        child 2, target_shift: int64
                child 4, task5: struct<actions: int64, artifact_manifest: string, evaluation_manifest: string, evaluation_rows: int6 (... 36 chars omitted)
                    child 0, actions: int64
                    child 1, artifact_manifest: string
                    child 2, evaluation_manifest: string
                    child 3, evaluation_rows: int64
                    child 4, manifest: string
                    child 5, samples: int64
              action_video_timing_audited_pairs: int64
              official_evaluator_preflight_videos: int64
              to
              {'action_representation': Value('string'), 'action_video_timing_audited_pairs': Value('int64'), 'action_video_timing_pass': Value('bool'), 'canonical_action_fps': Value('float64'), 'canonical_video_fps': Value('float64'), 'complete': Value('bool'), 'evaluation_reference_rows': Value('int64'), 'evaluation_schema_version': Value('string'), 'official_evaluator_preflight_videos': Value('int64'), 'official_evaluator_reference_pass': Value('bool'), 'official_evaluator_reference_rows': Value('int64'), 'release_layout': Value('string'), 'task1_official_mse_direction_passes': Value('int64'), 'tasks': {'task1': {'artifact_manifest': Value('string'), 'evaluation_manifest': Value('string'), 'evaluation_rows': Value('int64'), 'manifest': Value('string'), 'samples': Value('int64')}, 'task2': {'artifact_manifest': Value('string'), 'evaluation_manifest': Value('string'), 'evaluation_rows': Value('int64'), 'manifest': Value('string'), 'samples': Value('int64')}, 'task3': {'artifact_manifest': Value('string'), 'categories_per_group': Value('int64'), 'episode_groups': Value('int64'), 'evaluation_manifest': Value('string'), 'evaluation_rows': Value('int64'), 'manifest': Value('string')}, 'task4': {'artifact_manifest': Value('string'), 'evaluation_manifest': Value('string'), 'evaluation_rows': Value('int64'), 'manifest': Value('string'), 'samples': Value('int64'), 'subsets': {'distractor': Value('int64'), 'no_gripper_close': Value('int64'), 'target_shift': Value('int64')}}, 'task5': {'actions': Value('int64'), 'artifact_manifest': Value('string'), 'evaluation_manifest': Value('string'), 'evaluation_rows': Value('int64'), 'manifest': Value('string'), 'samples': Value('int64')}}, 'validation_root': Value('string')}
              because column names don't match
              
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, 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