Datasets:

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python4-gemma3-27b-rlvr-logs

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Arcadia Impact 7

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
difficulty: string
episode: struct<parameter_names: list<item: string>, problem_id: string, required_rules: list<item: string>,  (... 602 chars omitted)
  child 0, parameter_names: list<item: string>
      child 0, item: string
  child 1, problem_id: string
  child 2, required_rules: list<item: string>
      child 0, item: string
  child 3, tests: list<item: struct<args: list<item: null>, expected: string, kwargs: struct<x: int64, queries: list<i (... 494 chars omitted)
      child 0, item: struct<args: list<item: null>, expected: string, kwargs: struct<x: int64, queries: list<item: string (... 482 chars omitted)
          child 0, args: list<item: null>
              child 0, item: null
          child 1, expected: string
          child 2, kwargs: struct<x: int64, queries: list<item: string>, y: int64, n: int64, values: list<item: int64>, text: s (... 424 chars omitted)
              child 0, x: int64
              child 1, queries: list<item: string>
                  child 0, item: string
              child 2, y: int64
              child 3, n: int64
              child 4, values: list<item: int64>
                  child 0, item: int64
              child 5, text: string
              child 6, p: string
              child 7, s: string
              child 8, nums: list<item: int64>
                  child 0, item: int64
              child 9, word: string
              child 10, t: int64
              child 11, num1: int64
              child 12, num2: int64
           
...
nums1: list<item: int64>
                  child 0, item: int64
              child 24, nums2: list<item: int64>
                  child 0, item: int64
              child 25, operations: list<item: int64>
                  child 0, item: int64
family: string
messages: list<item: struct<content: string, role: string>>
  child 0, item: struct<content: string, role: string>
      child 0, content: string
      child 1, role: string
source_row_sha256: string
task_id: string
lora_manifest: struct<version: string, target_count: int64, language_layer_count: int64, trainable_tensors: int64,  (... 284 chars omitted)
  child 0, version: string
  child 1, target_count: int64
  child 2, language_layer_count: int64
  child 3, trainable_tensors: int64
  child 4, trainable_parameters: int64
  child 5, trainable_names: list<item: string>
      child 0, item: string
  child 6, rank: int64
  child 7, alpha: int64
  child 8, dropout: double
  child 9, targets: list<item: string>
      child 0, item: string
  child 10, vllm_frozen_sync_exclusions: list<item: string>
      child 0, item: string
  child 11, vllm_sync_skipped_parameter_count: int64
  child 12, vllm_sync_skipped_parameter_names: list<item: string>
      child 0, item: string
global_completions_per_step: int64
episodes_requested: int64
parameterization: string
dropped_overlong: int64
world_size: int64
effective_episodes: int64
zero_std_group_fraction: double
max_steps: int64
checkpoint_steps: list<item: int64>
  child 0, item: int64
to
{'episodes_requested': Value('int64'), 'max_steps': Value('int64'), 'effective_episodes': Value('int64'), 'world_size': Value('int64'), 'global_completions_per_step': Value('int64'), 'checkpoint_steps': List(Value('int64')), 'dropped_overlong': Value('int64'), 'parameterization': Value('string'), 'lora_manifest': {'version': Value('string'), 'target_count': Value('int64'), 'language_layer_count': Value('int64'), 'trainable_tensors': Value('int64'), 'trainable_parameters': Value('int64'), 'trainable_names': List(Value('string')), 'rank': Value('int64'), 'alpha': Value('int64'), 'dropout': Value('float64'), 'targets': List(Value('string')), 'vllm_frozen_sync_exclusions': List(Value('string')), 'vllm_sync_skipped_parameter_count': Value('int64'), 'vllm_sync_skipped_parameter_names': List(Value('string'))}, 'zero_std_group_fraction': 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
              difficulty: string
              episode: struct<parameter_names: list<item: string>, problem_id: string, required_rules: list<item: string>,  (... 602 chars omitted)
                child 0, parameter_names: list<item: string>
                    child 0, item: string
                child 1, problem_id: string
                child 2, required_rules: list<item: string>
                    child 0, item: string
                child 3, tests: list<item: struct<args: list<item: null>, expected: string, kwargs: struct<x: int64, queries: list<i (... 494 chars omitted)
                    child 0, item: struct<args: list<item: null>, expected: string, kwargs: struct<x: int64, queries: list<item: string (... 482 chars omitted)
                        child 0, args: list<item: null>
                            child 0, item: null
                        child 1, expected: string
                        child 2, kwargs: struct<x: int64, queries: list<item: string>, y: int64, n: int64, values: list<item: int64>, text: s (... 424 chars omitted)
                            child 0, x: int64
                            child 1, queries: list<item: string>
                                child 0, item: string
                            child 2, y: int64
                            child 3, n: int64
                            child 4, values: list<item: int64>
                                child 0, item: int64
                            child 5, text: string
                            child 6, p: string
                            child 7, s: string
                            child 8, nums: list<item: int64>
                                child 0, item: int64
                            child 9, word: string
                            child 10, t: int64
                            child 11, num1: int64
                            child 12, num2: int64
                         
              ...
              nums1: list<item: int64>
                                child 0, item: int64
                            child 24, nums2: list<item: int64>
                                child 0, item: int64
                            child 25, operations: list<item: int64>
                                child 0, item: int64
              family: string
              messages: list<item: struct<content: string, role: string>>
                child 0, item: struct<content: string, role: string>
                    child 0, content: string
                    child 1, role: string
              source_row_sha256: string
              task_id: string
              lora_manifest: struct<version: string, target_count: int64, language_layer_count: int64, trainable_tensors: int64,  (... 284 chars omitted)
                child 0, version: string
                child 1, target_count: int64
                child 2, language_layer_count: int64
                child 3, trainable_tensors: int64
                child 4, trainable_parameters: int64
                child 5, trainable_names: list<item: string>
                    child 0, item: string
                child 6, rank: int64
                child 7, alpha: int64
                child 8, dropout: double
                child 9, targets: list<item: string>
                    child 0, item: string
                child 10, vllm_frozen_sync_exclusions: list<item: string>
                    child 0, item: string
                child 11, vllm_sync_skipped_parameter_count: int64
                child 12, vllm_sync_skipped_parameter_names: list<item: string>
                    child 0, item: string
              global_completions_per_step: int64
              episodes_requested: int64
              parameterization: string
              dropped_overlong: int64
              world_size: int64
              effective_episodes: int64
              zero_std_group_fraction: double
              max_steps: int64
              checkpoint_steps: list<item: int64>
                child 0, item: int64
              to
              {'episodes_requested': Value('int64'), 'max_steps': Value('int64'), 'effective_episodes': Value('int64'), 'world_size': Value('int64'), 'global_completions_per_step': Value('int64'), 'checkpoint_steps': List(Value('int64')), 'dropped_overlong': Value('int64'), 'parameterization': Value('string'), 'lora_manifest': {'version': Value('string'), 'target_count': Value('int64'), 'language_layer_count': Value('int64'), 'trainable_tensors': Value('int64'), 'trainable_parameters': Value('int64'), 'trainable_names': List(Value('string')), 'rank': Value('int64'), 'alpha': Value('int64'), 'dropout': Value('float64'), 'targets': List(Value('string')), 'vllm_frozen_sync_exclusions': List(Value('string')), 'vllm_sync_skipped_parameter_count': Value('int64'), 'vllm_sync_skipped_parameter_names': List(Value('string'))}, 'zero_std_group_fraction': 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