Datasets:

---

muyo

/

ff-kv-sae-eval-results

like 0

Error code:   DatasetGenerationError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<architecture: string, d_in: int64, d_sae: int64, activation_fn_str: string, apply_b_dec_to_input: bool, finetuning_scaling_factor: bool, context_size: int64, model_name: string, hook_name: string, hook_layer: int64, hook_head_index: null, prepend_bos: bool, dataset_path: string, dataset_trust_remote_code: bool, normalize_activations: null, dtype: string, device: string, sae_lens_training_version: null, activation_fn_kwargs: struct<>, neuronpedia_id: string, model_from_pretrained_kwargs: struct<>, seqpos_slice: list<item: null>>
to
{'model_name': Value('string'), 'd_in': Value('int64'), 'd_sae': Value('int64'), 'hook_layer': Value('int64'), 'hook_name': Value('string'), 'is_transcoder': Value('bool'), 'input_hook_name': Value('string'), 'output_hook_name': Value('string'), 'context_size': Value('null'), 'hook_head_index': Value('null'), 'architecture': Value('string'), 'apply_b_dec_to_input': Value('null'), 'finetuning_scaling_factor': Value('null'), 'activation_fn_str': Value('string'), 'prepend_bos': Value('bool'), 'normalize_activations': Value('string'), 'dtype': Value('string'), 'device': Value('string'), 'dataset_path': Value('string'), 'dataset_trust_remote_code': Value('bool'), 'seqpos_slice': List(Value('null')), 'training_tokens': Value('int64'), 'sae_lens_training_version': Value('null'), 'neuronpedia_id': Value('null')}
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/table.py", line 2224, in cast_table_to_schema
                  cast_array_to_feature(
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/table.py", line 1795, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/table.py", line 2092, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<architecture: string, d_in: int64, d_sae: int64, activation_fn_str: string, apply_b_dec_to_input: bool, finetuning_scaling_factor: bool, context_size: int64, model_name: string, hook_name: string, hook_layer: int64, hook_head_index: null, prepend_bos: bool, dataset_path: string, dataset_trust_remote_code: bool, normalize_activations: null, dtype: string, device: string, sae_lens_training_version: null, activation_fn_kwargs: struct<>, neuronpedia_id: string, model_from_pretrained_kwargs: struct<>, seqpos_slice: list<item: null>>
              to
              {'model_name': Value('string'), 'd_in': Value('int64'), 'd_sae': Value('int64'), 'hook_layer': Value('int64'), 'hook_name': Value('string'), 'is_transcoder': Value('bool'), 'input_hook_name': Value('string'), 'output_hook_name': Value('string'), 'context_size': Value('null'), 'hook_head_index': Value('null'), 'architecture': Value('string'), 'apply_b_dec_to_input': Value('null'), 'finetuning_scaling_factor': Value('null'), 'activation_fn_str': Value('string'), 'prepend_bos': Value('bool'), 'normalize_activations': Value('string'), 'dtype': Value('string'), 'device': Value('string'), 'dataset_path': Value('string'), 'dataset_trust_remote_code': Value('bool'), 'seqpos_slice': List(Value('null')), 'training_tokens': Value('int64'), 'sae_lens_training_version': Value('null'), 'neuronpedia_id': Value('null')}
              
              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 1450, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 993, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 1858, 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