Fixed Input-Target Dimention Mismatch

iSiddharth20 · Dec 24, 2023 · 747e92c · 747e92c
1 parent af153e8
commit 747e92c
Showing 1 changed file with 8 additions and 8 deletions.
diff --git a/Code/autoencoder_model.py b/Code/autoencoder_model.py
@@ -18,13 +18,13 @@ def __init__(self):
         Encoder takes 1-Chanel Grayscale image (1 channel) as input and outputs High-Dimentional-Representation
         '''
         self.encoder = nn.Sequential(
-            nn.Conv2d(1, 64, kernel_size=3, stride=2, padding=1),
+            nn.Conv2d(1, 64, kernel_size=3, stride=1, padding=1),
             nn.ReLU(),
-            nn.Conv2d(64, 128, kernel_size=3, stride=2, padding=1),
+            nn.Conv2d(64, 128, kernel_size=3, stride=1, padding=1),
             nn.ReLU(),
-            nn.Conv2d(128, 256, kernel_size=3, stride=2, padding=1),
+            nn.Conv2d(128, 256, kernel_size=3, stride=1, padding=1),
             nn.ReLU(),
-            nn.Conv2d(256, 512, kernel_size=3, stride=2, padding=1),
+            nn.Conv2d(256, 512, kernel_size=3, stride=1, padding=1),
             nn.ReLU()
         )
 
@@ -34,13 +34,13 @@ def __init__(self):
         Decoder takes High-Dimentional-Representation as input and outputs 3-Chanel RGB image
         '''
         self.decoder = nn.Sequential(
-            nn.ConvTranspose2d(512, 256, kernel_size=3, stride=2, padding=1, output_padding=1),
+            nn.ConvTranspose2d(512, 256, kernel_size=3, stride=1, padding=1, output_padding=0),
             nn.ReLU(),
-            nn.ConvTranspose2d(256, 128, kernel_size=3, stride=2, padding=1, output_padding=1),
+            nn.ConvTranspose2d(256, 128, kernel_size=3, stride=1, padding=1, output_padding=0),
             nn.ReLU(),
-            nn.ConvTranspose2d(128, 64, kernel_size=3, stride=2, padding=1, output_padding=1),
+            nn.ConvTranspose2d(128, 64, kernel_size=3, stride=1, padding=1, output_padding=0),
             nn.ReLU(),
-            nn.ConvTranspose2d(64, 3, kernel_size=3, stride=2, padding=1, output_padding=1),
+            nn.ConvTranspose2d(64, 3, kernel_size=3, stride=1, padding=1, output_padding=0),
             nn.Sigmoid()
         )