Rename mlp to ff

Rename mlp to ff

2 files changed, 8 insertions, 6 deletions

diff --git a/text_recognizer/networks/conformer/block.py b/text_recognizer/networks/conformer/block.py
index d9782e8..4b31aec 100644
--- a/text_recognizer/networks/conformer/block.py
+++ b/text_recognizer/networks/conformer/block.py
@@ -5,7 +5,7 @@ from typing import Optional
 from torch import nn, Tensor
 from text_recognizer.networks.conformer.conv import ConformerConv
 
-from text_recognizer.networks.conformer.mlp import MLP
+from text_recognizer.networks.conformer.ff import Feedforward
 from text_recognizer.networks.conformer.scale import Scale
 from text_recognizer.networks.transformer.attention import Attention
 from text_recognizer.networks.transformer.norm import PreNorm
@@ -15,7 +15,7 @@ class ConformerBlock(nn.Module):
     def __init__(
         self,
         dim: int,
-        ff: MLP,
+        ff: Feedforward,
         attn: Attention,
         conv: ConformerConv,
     ) -> None:
diff --git a/text_recognizer/networks/conformer/mlp.py b/text_recognizer/networks/conformer/ff.py
index 031bde9..2ef4245 100644
--- a/text_recognizer/networks/conformer/mlp.py
+++ b/text_recognizer/networks/conformer/ff.py
@@ -2,14 +2,16 @@
 from torch import nn, Tensor
 
 
-class MLP(nn.Module):
-    def __init__(self, dim: int, mult: int = 4, dropout: float = 0.0) -> None:
+class Feedforward(nn.Module):
+    def __init__(
+        self, dim: int, expansion_factor: int = 4, dropout: float = 0.0
+    ) -> None:
         super().__init__()
         self.layers = nn.Sequential(
-            nn.Linear(dim, mult * dim),
+            nn.Linear(dim, expansion_factor * dim),
             nn.Mish(inplace=True),
             nn.Dropout(dropout),
-            nn.Linear(mult * dim, dim),
+            nn.Linear(expansion_factor * dim, dim),
             nn.Dropout(dropout),
         )