Datasets:

---

sabbbbir

/

inter_intra

Like 0

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'base_class \\ patch_class'}) and 1 missing columns ({'true_class \\ predicted_class'}).

This happened while the csv dataset builder was generating data using

hf://datasets/sabbbbir/inter_intra/results/cifar100_cutmix/resnet18_cifar/cutmix_nxn_pooled_base_accuracy.csv (at revision 74467f80e5b14fb591ff5d8b883e93963919fc4c), ['hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/confusion_matrix_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/cutmix_nxn_pooled_base_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/cutmix_nxn_pooled_patch_hijack.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/cutmix_nxn_testonly_base_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/cutmix_nxn_testonly_patch_hijack.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/predictions.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/confusion_matrix_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_base_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_patch_hijack.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_pooled_base_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_pooled_patch_hijack.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_testonly_base_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_testonly_patch_hijack.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/predictions.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/resnet18_cifar/intraclass_vs_baseline_report.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._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
              base_class \ patch_class: string
              apple: double
              aquarium_fish: double
              baby: double
              bear: double
              beaver: double
              bed: double
              bee: double
              beetle: double
              bicycle: double
              bottle: double
              bowl: double
              boy: double
              bridge: double
              bus: double
              butterfly: double
              camel: double
              can: double
              castle: double
              caterpillar: double
              cattle: double
              chair: double
              chimpanzee: double
              clock: double
              cloud: double
              cockroach: double
              couch: double
              crab: double
              crocodile: double
              cup: double
              dinosaur: double
              dolphin: double
              elephant: double
              flatfish: double
              forest: double
              fox: double
              girl: double
              hamster: double
              house: double
              kangaroo: double
              keyboard: double
              lamp: double
              lawn_mower: double
              leopard: double
              lion: double
              lizard: double
              lobster: double
              man: double
              maple_tree: double
              motorcycle: double
              mountain: double
              mouse: double
              mushroom: double
              oak_tree: double
              orange: double
              orchid: double
              otter: double
              palm_tree: double
              pear: double
              pickup_truck: double
              pine_tree: double
              plain: double
              plate: double
              poppy: double
              porcupine: double
              possum: double
              rabbit: double
              raccoon: double
              ray: double
              road: double
              rocket: double
              rose: double
              sea: double
              seal: double
              shark: double
              shrew: double
              skunk: double
              skyscraper: double
              snail: double
              snake: double
              spider: double
              squirrel: double
              streetcar: double
              sunflower: double
              sweet_pepper: double
              table: double
              tank: double
              telephone: double
              television: double
              tiger: double
              tractor: double
              train: double
              trout: double
              tulip: double
              turtle: double
              wardrobe: double
              whale: double
              willow_tree: double
              wolf: double
              woman: double
              worm: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 11779
              to
              {'true_class \\ predicted_class': Value('string'), 'apple': Value('float64'), 'aquarium_fish': Value('float64'), 'baby': Value('float64'), 'bear': Value('float64'), 'beaver': Value('float64'), 'bed': Value('float64'), 'bee': Value('float64'), 'beetle': Value('float64'), 'bicycle': Value('float64'), 'bottle': Value('float64'), 'bowl': Value('float64'), 'boy': Value('float64'), 'bridge': Value('float64'), 'bus': Value('float64'), 'butterfly': Value('float64'), 'camel': Value('float64'), 'can': Value('float64'), 'castle': Value('float64'), 'caterpillar': Value('float64'), 'cattle': Value('float64'), 'chair': Value('float64'), 'chimpanzee': Value('float64'), 'clock': Value('float64'), 'cloud': Value('float64'), 'cockroach': Value('float64'), 'couch': Value('float64'), 'crab': Value('float64'), 'crocodile': Value('float64'), 'cup': Value('float64'), 'dinosaur': Value('float64'), 'dolphin': Value('float64'), 'elephant': Value('float64'), 'flatfish': Value('float64'), 'forest': Value('float64'), 'fox': Value('float64'), 'girl': Value('float64'), 'hamster': Value('float64'), 'house': Value('float64'), 'kangaroo': Value('float64'), 'keyboard': Value('float64'), 'lamp': Value('float64'), 'lawn_mower': Value('float64'), 'leopard': Value('float64'), 'lion': Value('float64'), 'lizard': Value('float64'), 'lobster': Value('float64'), 'man': Value('float64'), 'maple_tree': Value('float64'), 'motorcycle': Value('float64'), 'mountain': Value('float64'), 'mouse': Value('float64'), 'mushroom': Value('float64'), 'oak_tree': Value('float64'), 'orange': Value('float64'), 'orchid': Value('float64'), 'otter': Value('float64'), 'palm_tree': Value('float64'), 'pear': Value('float64'), 'pickup_truck': Value('float64'), 'pine_tree': Value('float64'), 'plain': Value('float64'), 'plate': Value('float64'), 'poppy': Value('float64'), 'porcupine': Value('float64'), 'possum': Value('float64'), 'rabbit': Value('float64'), 'raccoon': Value('float64'), 'ray': Value('float64'), 'road': Value('float64'), 'rocket': Value('float64'), 'rose': Value('float64'), 'sea': Value('float64'), 'seal': Value('float64'), 'shark': Value('float64'), 'shrew': Value('float64'), 'skunk': Value('float64'), 'skyscraper': Value('float64'), 'snail': Value('float64'), 'snake': Value('float64'), 'spider': Value('float64'), 'squirrel': Value('float64'), 'streetcar': Value('float64'), 'sunflower': Value('float64'), 'sweet_pepper': Value('float64'), 'table': Value('float64'), 'tank': Value('float64'), 'telephone': Value('float64'), 'television': Value('float64'), 'tiger': Value('float64'), 'tractor': Value('float64'), 'train': Value('float64'), 'trout': Value('float64'), 'tulip': Value('float64'), 'turtle': Value('float64'), 'wardrobe': Value('float64'), 'whale': Value('float64'), 'willow_tree': Value('float64'), 'wolf': Value('float64'), 'woman': Value('float64'), 'worm': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              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 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'base_class \\ patch_class'}) and 1 missing columns ({'true_class \\ predicted_class'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/sabbbbir/inter_intra/results/cifar100_cutmix/resnet18_cifar/cutmix_nxn_pooled_base_accuracy.csv (at revision 74467f80e5b14fb591ff5d8b883e93963919fc4c), ['hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/confusion_matrix_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/cutmix_nxn_pooled_base_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/cutmix_nxn_pooled_patch_hijack.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/cutmix_nxn_testonly_base_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/cutmix_nxn_testonly_patch_hijack.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar100_cutmix/resnet18_cifar/predictions.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/confusion_matrix_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_base_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_patch_hijack.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_pooled_base_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_pooled_patch_hijack.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_testonly_base_accuracy.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/cutmix_10x10_testonly_patch_hijack.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/predictions.csv', 'hf://datasets/sabbbbir/inter_intra@74467f80e5b14fb591ff5d8b883e93963919fc4c/results/cifar10_cutmix/resnet18_cifar/intraclass_vs_baseline_report.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)