Ignore .pth files

.gitignore

@@ -0,0 +1 @@
+*.pth

Generator_Discriminator.py

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+import torch.nn as nn
+
+class Generator(nn.Module):
+    def __init__(self, noise_dim, img_channels):
+        super(Generator, self).__init__()
+        self.model = nn.Sequential(
+            nn.Linear(noise_dim, 256),
+            nn.ReLU(True),
+            nn.BatchNorm1d(256),
+            nn.Linear(256, 512),
+            nn.ReLU(True),
+            nn.BatchNorm1d(512),
+            nn.Linear(512, 1024),
+            nn.ReLU(True),
+            nn.BatchNorm1d(1024),
+            nn.Linear(1024, img_channels * 80 * 80),
+            nn.Tanh()
+        )
+
+    def forward(self, x):
+        x = self.model(x)
+        return x.view(-1, 3, 80, 80) 
+
+class Discriminator(nn.Module):
+    def __init__(self, img_channels):
+        super(Discriminator, self).__init__()
+        self.model = nn.Sequential(
+            nn.Conv2d(img_channels, 80, kernel_size=5, stride=2, padding=2),
+            nn.LeakyReLU(0.2),
+            nn.Dropout(0.3),
+            nn.Conv2d(80, 128, kernel_size=5, stride=2, padding=2),
+            nn.LeakyReLU(0.2),
+            nn.Dropout(0.3),
+            nn.Flatten(),
+            nn.Linear(128 * 20 * 20, 1),
+            nn.Sigmoid()
+        )
+
+    def forward(self, x):
+        return self.model(x)