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ryanjin333
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lehome-groot-n17-data

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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
identity: struct<invocation: struct<asset_revision: string, code_revision: string, execution_mode: string, gro (... 534 chars omitted)
  child 0, invocation: struct<asset_revision: string, code_revision: string, execution_mode: string, groot_python: string,  (... 469 chars omitted)
      child 0, asset_revision: string
      child 1, code_revision: string
      child 2, execution_mode: string
      child 3, groot_python: string
      child 4, groot_python_sha256: string
      child 5, groot_python_version: string
      child 6, groot_revision: string
      child 7, groot_root: string
      child 8, image_identity: string
      child 9, kind: string
      child 10, matrix_sha256: string
      child 11, max_steps: int64
      child 12, policy_artifact_sha256: string
      child 13, policy_device_pool: list<item: string>
          child 0, item: string
      child 14, policy_repo: string
      child 15, policy_revision: string
      child 16, policy_step: int64
      child 17, schema_version: int64
      child 18, selected_trial_ids: list<item: string>
          child 0, item: string
      child 19, simulator_device: string
      child 20, simulator_version: string
      child 21, strategy: string
      child 22, workers: int64
  child 1, kind: string
  child 2, trial_ids: list<item: string>
      child 0, item: string
metrics: struct<episodes: int64, official_successes: int64, per_category: struct<top_long: struct<episodes: i (... 253 chars omitted)
  child 0, episodes: int64
  child 1, official_successes: int64
  child 2, per_category: struct<top_long: struct<episodes: int64, official_successes: int64, success_rate: double, visible_co (... 135 chars omitted)
      child 0, top_long: struct<episodes: int64, official_successes: int64, success_rate: double, visible_contact_count: int6 (... 2 chars omitted)
          child 0, episodes: int64
          child 1, official_successes: int64
          child 2, success_rate: double
          child 3, visible_contact_count: int64
      child 1, top_short: struct<episodes: int64, official_successes: int64, success_rate: double, visible_contact_count: int6 (... 2 chars omitted)
          child 0, episodes: int64
          child 1, official_successes: int64
          child 2, success_rate: double
          child 3, visible_contact_count: int64
  child 3, success_rate: double
  child 4, visible_contact_count: int64
release_id: string
remote_prefix: string
schema_version: int64
validation_episode_count: int64
valid: bool
loader_integration: string
train_episode_count: int64
trainer_validation_split: string
modality_contract_sha256: string
dataset_manifest_sha256: string
to
{'dataset_manifest_sha256': Value('string'), 'loader_integration': Value('string'), 'modality_contract_sha256': Value('string'), 'schema_version': Value('int64'), 'train_episode_count': Value('int64'), 'trainer_validation_split': Value('string'), 'valid': Value('bool'), 'validation_episode_count': Value('int64')}
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
              identity: struct<invocation: struct<asset_revision: string, code_revision: string, execution_mode: string, gro (... 534 chars omitted)
                child 0, invocation: struct<asset_revision: string, code_revision: string, execution_mode: string, groot_python: string,  (... 469 chars omitted)
                    child 0, asset_revision: string
                    child 1, code_revision: string
                    child 2, execution_mode: string
                    child 3, groot_python: string
                    child 4, groot_python_sha256: string
                    child 5, groot_python_version: string
                    child 6, groot_revision: string
                    child 7, groot_root: string
                    child 8, image_identity: string
                    child 9, kind: string
                    child 10, matrix_sha256: string
                    child 11, max_steps: int64
                    child 12, policy_artifact_sha256: string
                    child 13, policy_device_pool: list<item: string>
                        child 0, item: string
                    child 14, policy_repo: string
                    child 15, policy_revision: string
                    child 16, policy_step: int64
                    child 17, schema_version: int64
                    child 18, selected_trial_ids: list<item: string>
                        child 0, item: string
                    child 19, simulator_device: string
                    child 20, simulator_version: string
                    child 21, strategy: string
                    child 22, workers: int64
                child 1, kind: string
                child 2, trial_ids: list<item: string>
                    child 0, item: string
              metrics: struct<episodes: int64, official_successes: int64, per_category: struct<top_long: struct<episodes: i (... 253 chars omitted)
                child 0, episodes: int64
                child 1, official_successes: int64
                child 2, per_category: struct<top_long: struct<episodes: int64, official_successes: int64, success_rate: double, visible_co (... 135 chars omitted)
                    child 0, top_long: struct<episodes: int64, official_successes: int64, success_rate: double, visible_contact_count: int6 (... 2 chars omitted)
                        child 0, episodes: int64
                        child 1, official_successes: int64
                        child 2, success_rate: double
                        child 3, visible_contact_count: int64
                    child 1, top_short: struct<episodes: int64, official_successes: int64, success_rate: double, visible_contact_count: int6 (... 2 chars omitted)
                        child 0, episodes: int64
                        child 1, official_successes: int64
                        child 2, success_rate: double
                        child 3, visible_contact_count: int64
                child 3, success_rate: double
                child 4, visible_contact_count: int64
              release_id: string
              remote_prefix: string
              schema_version: int64
              validation_episode_count: int64
              valid: bool
              loader_integration: string
              train_episode_count: int64
              trainer_validation_split: string
              modality_contract_sha256: string
              dataset_manifest_sha256: string
              to
              {'dataset_manifest_sha256': Value('string'), 'loader_integration': Value('string'), 'modality_contract_sha256': Value('string'), 'schema_version': Value('int64'), 'train_episode_count': Value('int64'), 'trainer_validation_split': Value('string'), 'valid': Value('bool'), 'validation_episode_count': Value('int64')}
              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
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dataset_manifest_sha256 string	loader_integration string	modality_contract_sha256 string	schema_version int64	train_episode_count int64	trainer_validation_split string	valid bool	validation_episode_count int64
03f635b37dd7e21a062dab83dcfb60cc383c60cb95404d51331b6e751672c507	not_run_no_pinned_runtime	966e169c097c2340858f2331dcfc635b9fbf51394fc5f7b1b3f96b51e8f81f26	1	135	offline_only	true	15
LeHome GR00T N1.7 prepared data

Private, immutable prepared training data for the LeHome GR00T N1.7 pipeline. Artifacts are published only after deterministic conversion, train-only normalization, complete validation, and hash verification.
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