Working on EMNIST Lines dataset

1 files changed, 12 insertions, 9 deletions

diff --git a/text_recognizer/datasets/base_dataset.py b/text_recognizer/datasets/base_dataset.py
index 7322d7f..a004b8d 100644
--- a/text_recognizer/datasets/base_dataset.py
+++ b/text_recognizer/datasets/base_dataset.py
@@ -17,12 +17,14 @@ class BaseDataset(Dataset):
         target_transform (Callable): Fucntion that takes a target and applies
             target transforms.
     """
-    def __init__(self,
-            data: Union[Sequence, Tensor],
-            targets: Union[Sequence, Tensor],
-            transform: Callable = None,
-            target_transform: Callable = None,
-            ) -> None:
+
+    def __init__(
+        self,
+        data: Union[Sequence, Tensor],
+        targets: Union[Sequence, Tensor],
+        transform: Callable = None,
+        target_transform: Callable = None,
+    ) -> None:
         if len(data) != len(targets):
             raise ValueError("Data and targets must be of equal length.")
         self.data = data
@@ -30,11 +32,10 @@ class BaseDataset(Dataset):
         self.transform = transform
         self.target_transform = target_transform
 
-
     def __len__(self) -> int:
         """Return the length of the dataset."""
         return len(self.data)
-            
+
     def __getitem__(self, index: int) -> Tuple[Any, Any]:
         """Return a datum and its target, after processing by transforms.
 
@@ -56,7 +57,9 @@ class BaseDataset(Dataset):
         return datum, target
 
 
-def convert_strings_to_labels(strings: Sequence[str], mapping: Dict[str, int], length: int) -> Tensor:
+def convert_strings_to_labels(
+    strings: Sequence[str], mapping: Dict[str, int], length: int
+) -> Tensor:
     """
     Convert a sequence of N strings to (N, length) ndarray, with each string wrapped with <S> and </S> tokens,
     and padded wiht the <P> token.