Datasets:

---

HuggingFaceM4

/

PGM

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HuggingFaceM4 787

Throws ValueError

Code:

loader = DataLoader(
    pgm_dataset['train'],
    batch_size = 1
)

Error:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[22], line 1
----> 1 for i in loader:
      2     print(i)

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/torch/utils/data/dataloader.py:732, in _BaseDataLoaderIter.__next__(self)
    729 if self._sampler_iter is None:
    730     # TODO(https://github.com/pytorch/pytorch/issues/76750)
    731     self._reset()  # type: ignore[call-arg]
--> 732 data = self._next_data()
    733 self._num_yielded += 1
    734 if (
    735     self._dataset_kind == _DatasetKind.Iterable
    736     and self._IterableDataset_len_called is not None
    737     and self._num_yielded > self._IterableDataset_len_called
    738 ):

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/torch/utils/data/dataloader.py:788, in _SingleProcessDataLoaderIter._next_data(self)
    786 def _next_data(self):
    787     index = self._next_index()  # may raise StopIteration
--> 788     data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
    789     if self._pin_memory:
    790         data = _utils.pin_memory.pin_memory(data, self._pin_memory_device)

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/torch/utils/data/_utils/fetch.py:50, in _MapDatasetFetcher.fetch(self, possibly_batched_index)
     48 if self.auto_collation:
     49     if hasattr(self.dataset, "__getitems__") and self.dataset.__getitems__:
---> 50         data = self.dataset.__getitems__(possibly_batched_index)
     51     else:
     52         data = [self.dataset[idx] for idx in possibly_batched_index]

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/datasets/arrow_dataset.py:2880, in Dataset.__getitems__(self, keys)
   2878 def __getitems__(self, keys: list) -> list:
   2879     """Can be used to get a batch using a list of integers indices."""
-> 2880     batch = self.__getitem__(keys)
   2881     n_examples = len(batch[next(iter(batch))])
   2882     return [{col: array[i] for col, array in batch.items()} for i in range(n_examples)]

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/datasets/arrow_dataset.py:2876, in Dataset.__getitem__(self, key)
   2874     if self._format_type is None or self._format_type not in ("arrow", "pandas", "polars"):
   2875         return Column(self, key)
-> 2876 return self._getitem(key)

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/datasets/arrow_dataset.py:2858, in Dataset._getitem(self, key, **kwargs)
   2856 formatter = get_formatter(format_type, features=self._info.features, **format_kwargs)
   2857 pa_subtable = query_table(self._data, key, indices=self._indices)
-> 2858 formatted_output = format_table(
   2859     pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
   2860 )
   2861 return formatted_output

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/datasets/formatting/formatting.py:658, in format_table(table, key, formatter, format_columns, output_all_columns)
    656 python_formatter = PythonFormatter(features=formatter.features)
    657 if format_columns is None:
--> 658     return formatter(pa_table, query_type=query_type)
    659 elif query_type == "column":
    660     if key in format_columns:

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/datasets/formatting/formatting.py:415, in Formatter.__call__(self, pa_table, query_type)
    413     return self.format_column(pa_table)
    414 elif query_type == "batch":
--> 415     return self.format_batch(pa_table)

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/datasets/formatting/formatting.py:471, in PythonFormatter.format_batch(self, pa_table)
    469 if self.lazy:
    470     return LazyBatch(pa_table, self)
--> 471 batch = self.python_arrow_extractor().extract_batch(pa_table)
    472 batch = self.python_features_decoder.decode_batch(batch)
    473 return batch

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/datasets/formatting/formatting.py:150, in PythonArrowExtractor.extract_batch(self, pa_table)
    149 def extract_batch(self, pa_table: pa.Table) -> dict:
--> 150     return pa_table.to_pydict()

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/pyarrow/table.pxi:2311, in pyarrow.lib._Tabular.to_pydict()

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/pyarrow/table.pxi:1384, in pyarrow.lib.ChunkedArray.to_pylist()

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/datasets/features/features.py:831, in ArrayExtensionArray.to_pylist(self, maps_as_pydicts)
    829 def to_pylist(self, maps_as_pydicts: Optional[Literal["lossy", "strict"]] = None):
    830     zero_copy_only = _is_zero_copy_only(self.storage.type, unnest=True)
--> 831     numpy_arr = self.to_numpy(zero_copy_only=zero_copy_only)
    832     if self.type.shape[0] is None and numpy_arr.dtype == object:
    833         return [arr.tolist() for arr in numpy_arr.tolist()]

File ~/Projects/Research/ARC_AGI/.venv/lib/python3.13/site-packages/datasets/features/features.py:797, in ArrayExtensionArray.to_numpy(self, zero_copy_only)
    795     storage = storage.flatten()
    796 numpy_arr = storage.to_numpy(zero_copy_only=zero_copy_only)
--> 797 numpy_arr = numpy_arr.reshape(len(self) - len(null_indices), *self.type.shape)
    799 if len(null_indices):
    800     numpy_arr = np.insert(numpy_arr.astype(np.float64), null_indices, np.nan, axis=0)

ValueError: cannot reshape array of size 6 into shape (1,1,3)

Anyone know how to fix this? Thank you.