Datasets:

---

AIsekai

/

GEAS

like 0

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
status: string
archive_path: string
archive_sha256: string
manifest_path: string
manifest_sha256: string
extract_root: string
runs_root: string
expected_file_count: int64
actual_file_count: int64
expected_total_bytes: int64
manifest_total_bytes: int64
missing_count: int64
size_mismatch_count: int64
hash_mismatch_count: int64
extra_count: int64
sample_missing: list<item: null>
  child 0, item: null
sample_size_bad: list<item: null>
  child 0, item: null
sample_hash_bad: list<item: null>
  child 0, item: null
sample_extra: list<item: null>
  child 0, item: null
checks: struct<manifest_file_count: bool, manifest_total_bytes: bool, actual_file_count: bool, missing_files (... 72 chars omitted)
  child 0, manifest_file_count: bool
  child 1, manifest_total_bytes: bool
  child 2, actual_file_count: bool
  child 3, missing_files: bool
  child 4, size_mismatches: bool
  child 5, hash_mismatches: bool
  child 6, extra_files: bool
elapsed_minutes: double
candidates: list<item: struct<run_root: string, run_name: string, model_name: string, latest_checkpoint: string, (... 307 chars omitted)
  child 0, item: struct<run_root: string, run_name: string, model_name: string, latest_checkpoint: string, latest_che (... 295 chars omitted)
      child 0, run_root: string
      child 1, run_name: string
      child 2, model_name: string
      child 3, latest_checkpoint: string
      child 4, latest_checkpoint_name: string
      child 5, checkpoint_epoch: int64
      child 6, history_last_epoch: int64
      child 7, target_epochs: int64
      child 8, checkpoint_count: int64
      child 9, has_interrupted_checkpoint: bool
      child 10, has_final_metrics: bool
      child 11, resume_recommended: bool
      child 12, reason: string
      child 13, run_mtime_utc: string
      child 14, checkpoint_mtime_utc: string
      child 15, candidate_id: int64
to
{'candidates': List({'run_root': Value('string'), 'run_name': Value('string'), 'model_name': Value('string'), 'latest_checkpoint': Value('string'), 'latest_checkpoint_name': Value('string'), 'checkpoint_epoch': Value('int64'), 'history_last_epoch': Value('int64'), 'target_epochs': Value('int64'), 'checkpoint_count': Value('int64'), 'has_interrupted_checkpoint': Value('bool'), 'has_final_metrics': Value('bool'), 'resume_recommended': Value('bool'), 'reason': Value('string'), 'run_mtime_utc': Value('string'), 'checkpoint_mtime_utc': Value('string'), 'candidate_id': 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
              status: string
              archive_path: string
              archive_sha256: string
              manifest_path: string
              manifest_sha256: string
              extract_root: string
              runs_root: string
              expected_file_count: int64
              actual_file_count: int64
              expected_total_bytes: int64
              manifest_total_bytes: int64
              missing_count: int64
              size_mismatch_count: int64
              hash_mismatch_count: int64
              extra_count: int64
              sample_missing: list<item: null>
                child 0, item: null
              sample_size_bad: list<item: null>
                child 0, item: null
              sample_hash_bad: list<item: null>
                child 0, item: null
              sample_extra: list<item: null>
                child 0, item: null
              checks: struct<manifest_file_count: bool, manifest_total_bytes: bool, actual_file_count: bool, missing_files (... 72 chars omitted)
                child 0, manifest_file_count: bool
                child 1, manifest_total_bytes: bool
                child 2, actual_file_count: bool
                child 3, missing_files: bool
                child 4, size_mismatches: bool
                child 5, hash_mismatches: bool
                child 6, extra_files: bool
              elapsed_minutes: double
              candidates: list<item: struct<run_root: string, run_name: string, model_name: string, latest_checkpoint: string, (... 307 chars omitted)
                child 0, item: struct<run_root: string, run_name: string, model_name: string, latest_checkpoint: string, latest_che (... 295 chars omitted)
                    child 0, run_root: string
                    child 1, run_name: string
                    child 2, model_name: string
                    child 3, latest_checkpoint: string
                    child 4, latest_checkpoint_name: string
                    child 5, checkpoint_epoch: int64
                    child 6, history_last_epoch: int64
                    child 7, target_epochs: int64
                    child 8, checkpoint_count: int64
                    child 9, has_interrupted_checkpoint: bool
                    child 10, has_final_metrics: bool
                    child 11, resume_recommended: bool
                    child 12, reason: string
                    child 13, run_mtime_utc: string
                    child 14, checkpoint_mtime_utc: string
                    child 15, candidate_id: int64
              to
              {'candidates': List({'run_root': Value('string'), 'run_name': Value('string'), 'model_name': Value('string'), 'latest_checkpoint': Value('string'), 'latest_checkpoint_name': Value('string'), 'checkpoint_epoch': Value('int64'), 'history_last_epoch': Value('int64'), 'target_epochs': Value('int64'), 'checkpoint_count': Value('int64'), 'has_interrupted_checkpoint': Value('bool'), 'has_final_metrics': Value('bool'), 'resume_recommended': Value('bool'), 'reason': Value('string'), 'run_mtime_utc': Value('string'), 'checkpoint_mtime_utc': Value('string'), 'candidate_id': 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