Format files

2 files changed, 4 insertions, 2 deletions

diff --git a/text_recognizer/networks/transformer/attention.py b/text_recognizer/networks/transformer/attention.py
index b86636e..87792a9 100644
--- a/text_recognizer/networks/transformer/attention.py
+++ b/text_recognizer/networks/transformer/attention.py
@@ -20,7 +20,6 @@ class Attention(nn.Module):
     """Standard attention."""
 
     def __attrs_pre_init__(self) -> None:
-        """Pre init constructor."""
         super().__init__()
 
     dim: int = attr.ib()
@@ -34,7 +33,6 @@ class Attention(nn.Module):
     fc: nn.Linear = attr.ib(init=False)
 
     def __attrs_post_init__(self) -> None:
-        """Post init configuration."""
         self.scale = self.dim ** -0.5
         inner_dim = self.num_heads * self.dim_head
 
diff --git a/text_recognizer/networks/transformer/norm.py b/text_recognizer/networks/transformer/norm.py
index c59744a..98f4d7f 100644
--- a/text_recognizer/networks/transformer/norm.py
+++ b/text_recognizer/networks/transformer/norm.py
@@ -12,6 +12,8 @@ from torch import Tensor
 
 
 class ScaleNorm(nn.Module):
+    """Scaled normalization."""
+
     def __init__(self, normalized_shape: int, eps: float = 1.0e-5) -> None:
         super().__init__()
         self.scale = normalized_shape ** -0.5
@@ -25,6 +27,8 @@ class ScaleNorm(nn.Module):
 
 
 class PreNorm(nn.Module):
+    """Applies layer normalization then function."""
+
     def __init__(self, normalized_shape: int, fn: Type[nn.Module]) -> None:
         super().__init__()
         self.norm = nn.LayerNorm(normalized_shape)