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fix typo (ShuffingConfig -> ShufflingConfig) #2766

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Merged
albertvillanova merged 1 commit into from
Aug 10, 2021
Merged

fix typo (ShuffingConfig -> ShufflingConfig) #2766

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8 changes: 4 additions & 4 deletions src/datasets/iterable_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -293,7 +293,7 @@ def wrapper(**kwargs):


@dataclass
class ShuffingConfig:
class ShufflingConfig:
seed: Optional[int] = None


Expand All @@ -306,7 +306,7 @@ def __init__(
info: Optional[DatasetInfo] = None,
split: Optional[NamedSplit] = None,
format_type: Optional[str] = None,
shuffling: Optional[ShuffingConfig] = None,
shuffling: Optional[ShufflingConfig] = None,
):
info = info.copy() if info is not None else DatasetInfo()
DatasetInfoMixin.__init__(self, info=info, split=split)
Expand Down Expand Up @@ -425,7 +425,7 @@ def shuffle(self, buffer_size, seed=None) -> "IterableDataset":
buffer_size (:obj:`int`): size of the buffer.
seed (:obj:`int`, optional, default None): random seed that will be used to create the distribution.
"""
shuffling = ShuffingConfig(seed=seed)
shuffling = ShufflingConfig(seed=seed)
return iterable_dataset(
ex_iterable=BufferShuffledExamplesIterable(self._ex_iterable, buffer_size, seed=seed).shuffle_data_sources(
seed=seed
Expand Down Expand Up @@ -477,7 +477,7 @@ def iterable_dataset(
info: Optional[DatasetInfo] = None,
split: Optional[NamedSplit] = None,
format_type: Optional[str] = None,
shuffling: Optional[ShuffingConfig] = None,
shuffling: Optional[ShufflingConfig] = None,
):
if format_type is not None and format_type == "torch":
import torch
Expand Down
4 changes: 2 additions & 2 deletions tests/test_iterable_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@
IterableDataset,
MappedExamplesIterable,
RandomlyCyclingMultiSourcesExamplesIterable,
ShuffingConfig,
ShufflingConfig,
SkipExamplesIterable,
TakeExamplesIterable,
_batch_to_examples,
Expand Down Expand Up @@ -296,7 +296,7 @@ def test_iterable_dataset_shuffle(dataset: IterableDataset, generate_examples_fn
buffer_size = 3
dataset._ex_iterable.kwargs["filepaths"] = ["0.txt", "1.txt"]
dataset = dataset.shuffle(buffer_size, seed=seed)
assert isinstance(dataset._shuffling, ShuffingConfig)
assert isinstance(dataset._shuffling, ShufflingConfig)
assert dataset._shuffling.seed == seed
# Effective seed is sum of seed and epoch
if epoch is None:
Expand Down