Datasets:

---

vedangfake

/

space-erasing-artifacts

like 0

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
created_at: string
status: string
input_checks: struct<coco_rows: int64, unique_coco_image_ids: int64, unique_evaluation_seeds: int64, reference_ima (... 133 chars omitted)
  child 0, coco_rows: int64
  child 1, unique_coco_image_ids: int64
  child 2, unique_evaluation_seeds: int64
  child 3, reference_images: int64
  child 4, space_images: int64
  child 5, reference_ids_exact_match: bool
  child 6, space_ids_exact_match: bool
  child 7, reference_space_ids_exact_match: bool
fid: struct<canonical_torch_fidelity_native_preprocessing: double, torchmetrics_pre_resize_299_bilinear:  (... 192 chars omitted)
  child 0, canonical_torch_fidelity_native_preprocessing: double
  child 1, torchmetrics_pre_resize_299_bilinear: double
  child 2, absolute_difference: double
  child 3, canonical_library: string
  child 4, canonical_library_version: string
  child 5, torch_version: string
  child 6, cuda_used: bool
  child 7, black_images_included: int64
  child 8, black_fraction: double
paired_metric_checks: struct<n_pairs: int64, clip_drop_recomputed: double, clip_drop_reported: double, style_drop_recomput (... 414 chars omitted)
  child 0, n_pairs: int64
  child 1, clip_drop_recomputed: double
  child 2, clip_drop_reported: double
  child 3, style_drop_recomputed: double
  child 4, style_drop_reported: double
  child 5, style_target_hits: int64
  child 6, finite_metrics: struct<clip_vanilla: bool, clip_method: bool, clip_drop: bool, style_vanilla: bool, style_method: bo (... 167 chars omit
...
l
      child 1, clip_method: bool
      child 2, clip_drop: bool
      child 3, style_vanilla: bool
      child 4, style_method: bool
      child 5, style_drop: bool
      child 6, style_target_rate: bool
      child 7, clip_image_similarity: bool
      child 8, lpips: bool
      child 9, resnet_top1_agreement: bool
      child 10, resnet_top5_overlap: bool
      child 11, dino_similarity: bool
  child 7, clip_drop_identity_pass: bool
  child 8, style_drop_identity_pass: bool
metric_definitions: struct<clip_text_scores: string, clip_image_similarity: string, style_score: string, style_target_ra (... 56 chars omitted)
  child 0, clip_text_scores: string
  child 1, clip_image_similarity: string
  child 2, style_score: string
  child 3, style_target_rate: string
  child 4, lpips: string
  child 5, resnet: string
  child 6, dino: string
caveats: list<item: string>
  child 0, item: string
environment: struct<python: string, platform: string>
  child 0, python: string
  child 1, platform: string
stage2_steps: int64
neutral_image_template: string
artist: string
saliency_topk_blocks: double
target_prompts_path: string
method: string
erase_scale: double
lora_rank: int64
run_type: string
stage1_steps: int64
target_artist_filter: string
neutral_art_template: string
trajectory_bands: string
checkpoint: string
robust_prompt_mode: string
vulnerable_preserve_k: int64
style_basis_rank: int64
base_model_id: string
alpha_art: double
selected_modules: list<item: string>
  child 0, item: string
to
{'method': Value('string'), 'artist': Value('string'), 'run_type': Value('string'), 'base_model_id': Value('string'), 'checkpoint': Value('string'), 'target_prompts_path': Value('string'), 'target_artist_filter': Value('string'), 'neutral_art_template': Value('string'), 'neutral_image_template': Value('string'), 'alpha_art': Value('float64'), 'erase_scale': Value('float64'), 'style_basis_rank': Value('int64'), 'saliency_topk_blocks': Value('float64'), 'trajectory_bands': Value('string'), 'robust_prompt_mode': Value('string'), 'vulnerable_preserve_k': Value('int64'), 'lora_rank': Value('int64'), 'stage1_steps': Value('int64'), 'stage2_steps': Value('int64'), 'selected_modules': List(Value('string'))}
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
              created_at: string
              status: string
              input_checks: struct<coco_rows: int64, unique_coco_image_ids: int64, unique_evaluation_seeds: int64, reference_ima (... 133 chars omitted)
                child 0, coco_rows: int64
                child 1, unique_coco_image_ids: int64
                child 2, unique_evaluation_seeds: int64
                child 3, reference_images: int64
                child 4, space_images: int64
                child 5, reference_ids_exact_match: bool
                child 6, space_ids_exact_match: bool
                child 7, reference_space_ids_exact_match: bool
              fid: struct<canonical_torch_fidelity_native_preprocessing: double, torchmetrics_pre_resize_299_bilinear:  (... 192 chars omitted)
                child 0, canonical_torch_fidelity_native_preprocessing: double
                child 1, torchmetrics_pre_resize_299_bilinear: double
                child 2, absolute_difference: double
                child 3, canonical_library: string
                child 4, canonical_library_version: string
                child 5, torch_version: string
                child 6, cuda_used: bool
                child 7, black_images_included: int64
                child 8, black_fraction: double
              paired_metric_checks: struct<n_pairs: int64, clip_drop_recomputed: double, clip_drop_reported: double, style_drop_recomput (... 414 chars omitted)
                child 0, n_pairs: int64
                child 1, clip_drop_recomputed: double
                child 2, clip_drop_reported: double
                child 3, style_drop_recomputed: double
                child 4, style_drop_reported: double
                child 5, style_target_hits: int64
                child 6, finite_metrics: struct<clip_vanilla: bool, clip_method: bool, clip_drop: bool, style_vanilla: bool, style_method: bo (... 167 chars omit
              ...
              l
                    child 1, clip_method: bool
                    child 2, clip_drop: bool
                    child 3, style_vanilla: bool
                    child 4, style_method: bool
                    child 5, style_drop: bool
                    child 6, style_target_rate: bool
                    child 7, clip_image_similarity: bool
                    child 8, lpips: bool
                    child 9, resnet_top1_agreement: bool
                    child 10, resnet_top5_overlap: bool
                    child 11, dino_similarity: bool
                child 7, clip_drop_identity_pass: bool
                child 8, style_drop_identity_pass: bool
              metric_definitions: struct<clip_text_scores: string, clip_image_similarity: string, style_score: string, style_target_ra (... 56 chars omitted)
                child 0, clip_text_scores: string
                child 1, clip_image_similarity: string
                child 2, style_score: string
                child 3, style_target_rate: string
                child 4, lpips: string
                child 5, resnet: string
                child 6, dino: string
              caveats: list<item: string>
                child 0, item: string
              environment: struct<python: string, platform: string>
                child 0, python: string
                child 1, platform: string
              stage2_steps: int64
              neutral_image_template: string
              artist: string
              saliency_topk_blocks: double
              target_prompts_path: string
              method: string
              erase_scale: double
              lora_rank: int64
              run_type: string
              stage1_steps: int64
              target_artist_filter: string
              neutral_art_template: string
              trajectory_bands: string
              checkpoint: string
              robust_prompt_mode: string
              vulnerable_preserve_k: int64
              style_basis_rank: int64
              base_model_id: string
              alpha_art: double
              selected_modules: list<item: string>
                child 0, item: string
              to
              {'method': Value('string'), 'artist': Value('string'), 'run_type': Value('string'), 'base_model_id': Value('string'), 'checkpoint': Value('string'), 'target_prompts_path': Value('string'), 'target_artist_filter': Value('string'), 'neutral_art_template': Value('string'), 'neutral_image_template': Value('string'), 'alpha_art': Value('float64'), 'erase_scale': Value('float64'), 'style_basis_rank': Value('int64'), 'saliency_topk_blocks': Value('float64'), 'trajectory_bands': Value('string'), 'robust_prompt_mode': Value('string'), 'vulnerable_preserve_k': Value('int64'), 'lora_rank': Value('int64'), 'stage1_steps': Value('int64'), 'stage2_steps': Value('int64'), 'selected_modules': List(Value('string'))}
              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