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import torch.nn as nn
class SimpleCNN(nn.Module):
def __init__(self):
super(SimpleCNN, self).__init__()
self.conv1 = nn.Conv2d(3, 16, kernel_size=3, padding=1)
self.relu1 = nn.ReLU()
self.pool1 = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(16, 16, kernel_size=3, padding=1)
self.relu2 = nn.ReLU()
self.pool2 = nn.MaxPool2d(2, 2)
self.conv3 = nn.Conv2d(16, 16, kernel_size=3, padding=1)
self.relu3 = nn.ReLU()
self.pool3 = nn.MaxPool2d(2, 2)
self.conv4 = nn.Conv2d(16, 32, kernel_size=3, padding=1)
self.relu4 = nn.ReLU()
self.pool4 = nn.MaxPool2d(2, 2)
self.fc1 = nn.Linear(32 * 2 * 2, 256)
self.fc2 = nn.Linear(256, 10)
def forward(self, x):
x = self.pool1(self.relu1(self.conv1(x)))
x = self.pool2(self.relu2(self.conv2(x)))
x = self.pool3(self.relu3(self.conv3(x)))
x = self.pool4(self.relu4(self.conv4(x)))
x = x.view(-1, 32 * 2 * 2)
x = self.relu4(self.fc1(x))
x = self.fc2(x)
return x