Update README.md

README.md

@@ -20,29 +20,6 @@ import matplotlib.pyplot as plt
 import numpy as np
 from torch import nn
 
-class Generator(nn.Module):
-    def __init__(self):
-        super(Generator, self).__init__()
-        self.main = nn.Sequential(
-            nn.ConvTranspose2d(100, 64 * 8, 4, 1, 0, bias=False),
-            nn.BatchNorm2d(64 * 8),
-            nn.ReLU(True),
-            nn.ConvTranspose2d(64 * 8, 64 * 4, 4, 2, 1, bias=False),
-            nn.BatchNorm2d(64 * 4),
-            nn.ReLU(True),
-            nn.ConvTranspose2d(64 * 4, 64 * 2, 4, 2, 1, bias=False),
-            nn.BatchNorm2d(64 * 2),
-            nn.ReLU(True),
-            nn.ConvTranspose2d(64 * 2, 64, 4, 2, 1, bias=False),
-            nn.BatchNorm2d(64),
-            nn.ReLU(True),
-            nn.ConvTranspose2d(64, 3, 4, 2, 1, bias=False),
-            nn.Tanh()
-        )
-
-    def forward(self, input):
-        return self.main(input)
-
 path = hf_hub_download('huggan/ArtGAN', 'ArtGAN.pt')
 model = torch.load(path, map_location=torch.device('cpu'))
 device = 'cuda' if torch.cuda.is_available() else 'cpu'