Format imports

Format imports

9 files changed, 17 insertions, 22 deletions

diff --git a/text_recognizer/networks/transformer/__init__.py b/text_recognizer/networks/transformer/__init__.py
index af08aa8..0d17deb 100644
--- a/text_recognizer/networks/transformer/__init__.py
+++ b/text_recognizer/networks/transformer/__init__.py
@@ -1,6 +1,6 @@
 """Transformer modules."""
 from text_recognizer.networks.transformer.attention import Attention
-from text_recognizer.networks.transformer.ff import FeedForward
-from text_recognizer.networks.transformer.norm import RMSNorm
 from text_recognizer.networks.transformer.decoder import Decoder, DecoderBlock
 from text_recognizer.networks.transformer.embeddings.rotary import RotaryEmbedding
+from text_recognizer.networks.transformer.ff import FeedForward
+from text_recognizer.networks.transformer.norm import RMSNorm
diff --git a/text_recognizer/networks/transformer/attention.py b/text_recognizer/networks/transformer/attention.py
index 3df5333..fca260d 100644
--- a/text_recognizer/networks/transformer/attention.py
+++ b/text_recognizer/networks/transformer/attention.py
@@ -1,12 +1,10 @@
 """Implementes the attention module for the transformer."""
 from typing import Optional, Tuple
 
-from einops import rearrange
 import torch
-from torch import einsum
-from torch import nn
-from torch import Tensor
 import torch.nn.functional as F
+from einops import rearrange
+from torch import Tensor, einsum, nn
 
 from text_recognizer.networks.transformer.embeddings.rotary import (
     RotaryEmbedding,
@@ -35,7 +33,7 @@ class Attention(nn.Module):
         self.dropout_rate = dropout_rate
         self.rotary_embedding = rotary_embedding
 
-        self.scale = self.dim ** -0.5
+        self.scale = self.dim**-0.5
         inner_dim = self.num_heads * self.dim_head
 
         self.to_q = nn.Linear(self.dim, inner_dim, bias=False)
diff --git a/text_recognizer/networks/transformer/decoder.py b/text_recognizer/networks/transformer/decoder.py
index 8ea021b..efa1e89 100644
--- a/text_recognizer/networks/transformer/decoder.py
+++ b/text_recognizer/networks/transformer/decoder.py
@@ -2,7 +2,7 @@
 from copy import deepcopy
 from typing import Optional, Type
 
-from torch import nn, Tensor
+from torch import Tensor, nn
 
 from text_recognizer.networks.transformer.attention import Attention
 from text_recognizer.networks.transformer.ff import FeedForward
diff --git a/text_recognizer/networks/transformer/embeddings/absolute.py b/text_recognizer/networks/transformer/embeddings/absolute.py
index e5cdc18..9274b55 100644
--- a/text_recognizer/networks/transformer/embeddings/absolute.py
+++ b/text_recognizer/networks/transformer/embeddings/absolute.py
@@ -1,9 +1,9 @@
 """Absolute positional embedding."""
 
-from einops import rearrange
 import torch
-from torch import nn
 import torch.nn.functional as F
+from einops import rearrange
+from torch import nn
 
 
 def l2norm(t, groups=1):
@@ -15,7 +15,7 @@ def l2norm(t, groups=1):
 class AbsolutePositionalEmbedding(nn.Module):
     def __init__(self, dim, max_seq_len, l2norm_embed=False):
         super().__init__()
-        self.scale = dim ** -0.5 if not l2norm_embed else 1.0
+        self.scale = dim**-0.5 if not l2norm_embed else 1.0
         self.max_seq_len = max_seq_len
         self.l2norm_embed = l2norm_embed
         self.emb = nn.Embedding(max_seq_len, dim)
diff --git a/text_recognizer/networks/transformer/embeddings/axial.py b/text_recognizer/networks/transformer/embeddings/axial.py
index 7b84e12..25d8f60 100644
--- a/text_recognizer/networks/transformer/embeddings/axial.py
+++ b/text_recognizer/networks/transformer/embeddings/axial.py
@@ -3,10 +3,11 @@
 Stolen from:
     https://github.com/lucidrains/axial-attention/blob/eff2c10c2e76c735a70a6b995b571213adffbbb7/axial_attention/axial_attention.py#L100
 """
+from functools import reduce
+from operator import mul
+
 import torch
 from torch import nn
-from operator import mul
-from functools import reduce
 
 
 class AxialPositionalEmbedding(nn.Module):
diff --git a/text_recognizer/networks/transformer/embeddings/fourier.py b/text_recognizer/networks/transformer/embeddings/fourier.py
index 7843c60..28da7a1 100644
--- a/text_recognizer/networks/transformer/embeddings/fourier.py
+++ b/text_recognizer/networks/transformer/embeddings/fourier.py
@@ -1,8 +1,7 @@
 """Fourier positional embedding."""
 import numpy as np
 import torch
-from torch import nn
-from torch import Tensor
+from torch import Tensor, nn
 
 
 class PositionalEncoding(nn.Module):
diff --git a/text_recognizer/networks/transformer/embeddings/rotary.py b/text_recognizer/networks/transformer/embeddings/rotary.py
index 722478e..cc91206 100644
--- a/text_recognizer/networks/transformer/embeddings/rotary.py
+++ b/text_recognizer/networks/transformer/embeddings/rotary.py
@@ -7,8 +7,7 @@ Explanation of roatary:
     https://blog.eleuther.ai/rotary-embeddings/
 """
 import torch
-from torch import nn
-from torch import Tensor
+from torch import Tensor, nn
 
 
 class RotaryEmbedding(nn.Module):
diff --git a/text_recognizer/networks/transformer/ff.py b/text_recognizer/networks/transformer/ff.py
index 4028ab3..3ccf5b5 100644
--- a/text_recognizer/networks/transformer/ff.py
+++ b/text_recognizer/networks/transformer/ff.py
@@ -5,9 +5,8 @@ Stolen from lucidrains:
 """
 from typing import Optional
 
-from torch import nn
-from torch import Tensor
 import torch.nn.functional as F
+from torch import Tensor, nn
 
 
 class GEGLU(nn.Module):
diff --git a/text_recognizer/networks/transformer/norm.py b/text_recognizer/networks/transformer/norm.py
index 4cd3b5b..0bd2e16 100644
--- a/text_recognizer/networks/transformer/norm.py
+++ b/text_recognizer/networks/transformer/norm.py
@@ -7,8 +7,7 @@ Copied from lucidrains:
 from typing import Dict, Optional, Type
 
 import torch
-from torch import nn
-from torch import Tensor
+from torch import Tensor, nn
 
 
 class RMSNorm(nn.Module):
@@ -16,7 +15,7 @@ class RMSNorm(nn.Module):
 
     def __init__(self, dim: int, eps: float = 1e-8) -> None:
         super().__init__()
-        self.scale = dim ** -0.5
+        self.scale = dim**-0.5
         self.eps = eps
         self.g = nn.Parameter(torch.ones(dim))