Datasets:

---

Ki-Seki

/

trace-structure-exp

like 0

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
result_schema_version: string
experiment_id: string
dataset: struct<repo_id: string, revision: string, config: string, source_schema_version: string, group_id: s (... 124 chars omitted)
  child 0, repo_id: string
  child 1, revision: string
  child 2, config: string
  child 3, source_schema_version: string
  child 4, group_id: string
  child 5, dataset_id: string
  child 6, source_subset: string
  child 7, split: string
  child 8, problem_id: string
  child 9, problem_text: string
  child 10, model_id: string
tree_run_signature: struct<experiment_id: string, tree_schema_version: string, dataset_repo_id: string, dataset_revision (... 613 chars omitted)
  child 0, experiment_id: string
  child 1, tree_schema_version: string
  child 2, dataset_repo_id: string
  child 3, dataset_revision: string
  child 4, dataset_config: string
  child 5, official_repository: string
  child 6, official_commit: string
  child 7, fidelity_policy: string
  child 8, annotator_model: string
  child 9, annotator_mode: string
  child 10, temperature: double
  child 11, split_words: list<item: string>
      child 0, item: string
  child 12, minimum_preceding_split_chars: int64
  child 13, assign_chunk_max_words: int64
  child 14, function_calls: string
  child 15, edge_encoding: string
  child 16, tokenizer_id: string
  child 17, tokenizer_revision: string
  child 18, node_feature_names: list<item: string>
      child 0, item: string
  child 19, prompt_sha256: struct<extract_sketch: string, assign_step:
...
   child 5, best_validation_accuracy: double
      child 6, best_validation_loss: double
      child 7, test_accuracy: double
      child 8, test_loss: double
      child 9, train_records: int64
      child 10, validation_records: int64
      child 11, test_records: int64
      child 12, elapsed_seconds: double
run_signature: struct<experiment_id: string, result_schema_version: string, dataset_repo_id: string, dataset_revisi (... 312 chars omitted)
  child 0, experiment_id: string
  child 1, result_schema_version: string
  child 2, dataset_repo_id: string
  child 3, dataset_revision: string
  child 4, dataset_config: string
  child 5, embedding_model_id: string
  child 6, embedding_model_revision: string
  child 7, segmentation_version: string
  child 8, trace_vector: string
  child 9, reader: string
  child 10, random_seed: int64
  child 11, package_versions: struct<datasets: string, numpy: string, scikit-learn: string, sentence-transformers: string, torch:  (... 7 chars omitted)
      child 0, datasets: string
      child 1, numpy: string
      child 2, scikit-learn: string
      child 3, sentence-transformers: string
      child 4, torch: string
positive: struct<extraction_mode: string, step_count: int64, status: string>
  child 0, extraction_mode: string
  child 1, step_count: int64
  child 2, status: string
negative: struct<extraction_mode: string, step_count: int64, status: string>
  child 0, extraction_mode: string
  child 1, step_count: int64
  child 2, status: string
to
{'result_schema_version': Value('string'), 'experiment_id': Value('string'), 'dataset': {'repo_id': Value('string'), 'revision': Value('string'), 'config': Value('string'), 'group_id': Value('string'), 'problem_id': Value('string')}, 'run_signature': {'experiment_id': Value('string'), 'result_schema_version': Value('string'), 'dataset_repo_id': Value('string'), 'dataset_revision': Value('string'), 'dataset_config': Value('string'), 'embedding_model_id': Value('string'), 'embedding_model_revision': Value('string'), 'segmentation_version': Value('string'), 'trace_vector': Value('string'), 'reader': Value('string'), 'random_seed': Value('int64'), 'package_versions': {'datasets': Value('string'), 'numpy': Value('string'), 'scikit-learn': Value('string'), 'sentence-transformers': Value('string'), 'torch': Value('string')}}, 'positive': {'extraction_mode': Value('string'), 'step_count': Value('int64'), 'status': Value('string')}, 'negative': {'extraction_mode': Value('string'), 'step_count': Value('int64'), 'status': Value('string')}, 'created_at_utc': Value('string'), 'cv': {'eligible': Value('bool'), 'strategy': Value('string'), 'group_key': Value('string'), 'n_splits': Value('int64'), 'fold': Value('int64')}, 'readers': {'embed_mean': {'positive_score': Value('float64'), 'negative_score': Value('float64'), 'difference': Value('float64')}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1816, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              result_schema_version: string
              experiment_id: string
              dataset: struct<repo_id: string, revision: string, config: string, source_schema_version: string, group_id: s (... 124 chars omitted)
                child 0, repo_id: string
                child 1, revision: string
                child 2, config: string
                child 3, source_schema_version: string
                child 4, group_id: string
                child 5, dataset_id: string
                child 6, source_subset: string
                child 7, split: string
                child 8, problem_id: string
                child 9, problem_text: string
                child 10, model_id: string
              tree_run_signature: struct<experiment_id: string, tree_schema_version: string, dataset_repo_id: string, dataset_revision (... 613 chars omitted)
                child 0, experiment_id: string
                child 1, tree_schema_version: string
                child 2, dataset_repo_id: string
                child 3, dataset_revision: string
                child 4, dataset_config: string
                child 5, official_repository: string
                child 6, official_commit: string
                child 7, fidelity_policy: string
                child 8, annotator_model: string
                child 9, annotator_mode: string
                child 10, temperature: double
                child 11, split_words: list<item: string>
                    child 0, item: string
                child 12, minimum_preceding_split_chars: int64
                child 13, assign_chunk_max_words: int64
                child 14, function_calls: string
                child 15, edge_encoding: string
                child 16, tokenizer_id: string
                child 17, tokenizer_revision: string
                child 18, node_feature_names: list<item: string>
                    child 0, item: string
                child 19, prompt_sha256: struct<extract_sketch: string, assign_step:
              ...
                 child 5, best_validation_accuracy: double
                    child 6, best_validation_loss: double
                    child 7, test_accuracy: double
                    child 8, test_loss: double
                    child 9, train_records: int64
                    child 10, validation_records: int64
                    child 11, test_records: int64
                    child 12, elapsed_seconds: double
              run_signature: struct<experiment_id: string, result_schema_version: string, dataset_repo_id: string, dataset_revisi (... 312 chars omitted)
                child 0, experiment_id: string
                child 1, result_schema_version: string
                child 2, dataset_repo_id: string
                child 3, dataset_revision: string
                child 4, dataset_config: string
                child 5, embedding_model_id: string
                child 6, embedding_model_revision: string
                child 7, segmentation_version: string
                child 8, trace_vector: string
                child 9, reader: string
                child 10, random_seed: int64
                child 11, package_versions: struct<datasets: string, numpy: string, scikit-learn: string, sentence-transformers: string, torch:  (... 7 chars omitted)
                    child 0, datasets: string
                    child 1, numpy: string
                    child 2, scikit-learn: string
                    child 3, sentence-transformers: string
                    child 4, torch: string
              positive: struct<extraction_mode: string, step_count: int64, status: string>
                child 0, extraction_mode: string
                child 1, step_count: int64
                child 2, status: string
              negative: struct<extraction_mode: string, step_count: int64, status: string>
                child 0, extraction_mode: string
                child 1, step_count: int64
                child 2, status: string
              to
              {'result_schema_version': Value('string'), 'experiment_id': Value('string'), 'dataset': {'repo_id': Value('string'), 'revision': Value('string'), 'config': Value('string'), 'group_id': Value('string'), 'problem_id': Value('string')}, 'run_signature': {'experiment_id': Value('string'), 'result_schema_version': Value('string'), 'dataset_repo_id': Value('string'), 'dataset_revision': Value('string'), 'dataset_config': Value('string'), 'embedding_model_id': Value('string'), 'embedding_model_revision': Value('string'), 'segmentation_version': Value('string'), 'trace_vector': Value('string'), 'reader': Value('string'), 'random_seed': Value('int64'), 'package_versions': {'datasets': Value('string'), 'numpy': Value('string'), 'scikit-learn': Value('string'), 'sentence-transformers': Value('string'), 'torch': Value('string')}}, 'positive': {'extraction_mode': Value('string'), 'step_count': Value('int64'), 'status': Value('string')}, 'negative': {'extraction_mode': Value('string'), 'step_count': Value('int64'), 'status': Value('string')}, 'created_at_utc': Value('string'), 'cv': {'eligible': Value('bool'), 'strategy': Value('string'), 'group_key': Value('string'), 'n_splits': Value('int64'), 'fold': Value('int64')}, 'readers': {'embed_mean': {'positive_score': Value('float64'), 'negative_score': Value('float64'), 'difference': Value('float64')}}}
              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 1683, 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 1869, 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