Lint files

1 files changed, 14 insertions, 5 deletions

diff --git a/text_recognizer/data/base_dataset.py b/text_recognizer/data/base_dataset.py
index 8640d92..e08130d 100644
--- a/text_recognizer/data/base_dataset.py
+++ b/text_recognizer/data/base_dataset.py
@@ -9,8 +9,7 @@ from torch.utils.data import Dataset
 
 @attr.s
 class BaseDataset(Dataset):
-    """
-    Base Dataset class that processes data and targets through optional transfroms.
+    r"""Base Dataset class that processes data and targets through optional transfroms.
 
     Args:
         data (Union[Sequence, Tensor]): Torch tensors, numpy arrays, or PIL images.
@@ -26,9 +25,11 @@ class BaseDataset(Dataset):
     target_transform: Optional[Callable] = attr.ib(default=None)
 
     def __attrs_pre_init__(self) -> None:
+        """Pre init constructor."""
         super().__init__()
 
     def __attrs_post_init__(self) -> None:
+        """Post init constructor."""
         if len(self.data) != len(self.targets):
             raise ValueError("Data and targets must be of equal length.")
 
@@ -60,9 +61,17 @@ class BaseDataset(Dataset):
 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.
+    r"""Convert a sequence of N strings to (N, length) ndarray.
+
+    Add each string with <s> and </s> tokens, and padded wiht the <p> token.
+
+    Args:
+        strings (Sequence[str]): Sequence of strings.
+        mapping (Dict[str, int]): Mapping of characters and digits to integers.
+        length (int): Max lenght of all strings.
+
+    Returns:
+        Tensor: Target with emnist mapping indices.
     """
     labels = torch.ones((len(strings), length), dtype=torch.long) * mapping["<p>"]
     for i, string in enumerate(strings):