lint

torch_datasets.py

@@ -5,7 +5,7 @@
 
 from torch.utils.data import Dataset as TorchDataset
 from torch.utils.data import DataLoader
-from torch.utils.data import Sampler, BatchSampler, SequentialSampler, SubsetRandomSampler
+from torch.utils.data import BatchSampler, SequentialSampler
 
 from allennlp.common.registrable import Registrable
 from allennlp.common.util import add_noise_to_dict_values, lazy_groups_of
@@ -19,6 +19,7 @@
 
 logger = logging.getLogger(__name__)
 
+
 class Dataset(TorchDataset, Registrable):
  def __init__(self):
  self.vocab: Vocabulary = None
@@ -98,8 +99,13 @@ def text_to_instance(self, premise: str, hypothesis: str, label: str = None) ->
 
 
 class BatchInstanceSampler(BatchSampler):
-
- def __init__(self, data, batch_size: int, sorting_keys: List[Tuple[str, str]] = None, padding_noise: float = 0.1):
+ def __init__(
+ self,
+ data,
+ batch_size: int,
+ sorting_keys: List[Tuple[str, str]] = None,
+ padding_noise: float = 0.1,
+ ):
 
  self.vocab = data.vocab
  self._sorting_keys = sorting_keys
@@ -184,6 +190,7 @@ def allennlp_collocate(batch):
  batch = AllennlpBatch(batch)
  return batch.as_tensor_dict(batch.get_padding_lengths())
 
+
 batch_generator = DataLoader(data, batch_sampler=batch_sampler, collate_fn=allennlp_collocate)
 
 iterator = iter(batch_generator)