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cf3c3e8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | import torch
import torch.nn as nn
NOISE_DIM = 256
class Generator(nn.Module):
def __init__(self):
super().__init__()
self.fc = nn.Linear(NOISE_DIM, 4*4*512)
self.net = nn.Sequential(
nn.BatchNorm2d(512),
nn.Upsample(scale_factor=2),
nn.Conv2d(512, 256, 3, padding=1),
nn.BatchNorm2d(256),
nn.ReLU(True),
nn.Upsample(scale_factor=2),
nn.Conv2d(256, 128, 3, padding=1),
nn.BatchNorm2d(128),
nn.ReLU(True),
nn.Upsample(scale_factor=2),
nn.Conv2d(128, 64, 3, padding=1),
nn.BatchNorm2d(64),
nn.ReLU(True),
nn.Upsample(scale_factor=2),
nn.Conv2d(64, 3, 3, padding=1),
nn.Tanh()
)
def forward(self, noise):
x = self.fc(noise)
x = x.view(-1, 512, 4, 4)
return self.net(x) |