black reformatting

2 files changed, 7 insertions, 4 deletions

diff --git a/text_recognizer/networks/transformer/__init__.py b/text_recognizer/networks/transformer/__init__.py
index 139cd23..652e82e 100644
--- a/text_recognizer/networks/transformer/__init__.py
+++ b/text_recognizer/networks/transformer/__init__.py
@@ -1,3 +1,7 @@
 """Transformer modules."""
-from .positional_encoding import PositionalEncoding, PositionalEncoding2D, target_padding_mask
+from .positional_encoding import (
+    PositionalEncoding,
+    PositionalEncoding2D,
+    target_padding_mask,
+)
 from .transformer import Decoder, Encoder, EncoderLayer, Transformer
diff --git a/text_recognizer/networks/transformer/positional_encoding.py b/text_recognizer/networks/transformer/positional_encoding.py
index dbde887..5874e97 100644
--- a/text_recognizer/networks/transformer/positional_encoding.py
+++ b/text_recognizer/networks/transformer/positional_encoding.py
@@ -71,12 +71,11 @@ class PositionalEncoding2D(nn.Module):
         x += self.pe[:, : x.shape[2], : x.shape[3]]
         return x
 
+
 def target_padding_mask(trg: Tensor, pad_index: int) -> Tensor:
     """Returns causal target mask."""
     trg_pad_mask = (trg != pad_index)[:, None, None]
     trg_len = trg.shape[1]
-    trg_sub_mask = torch.tril(
-        torch.ones((trg_len, trg_len), device=trg.device)
-    ).bool()
+    trg_sub_mask = torch.tril(torch.ones((trg_len, trg_len), device=trg.device)).bool()
     trg_mask = trg_pad_mask & trg_sub_mask
     return trg_mask