Created
May 8, 2020 15:32
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| class Net(nn.Module): | |
| def __init__(self): | |
| super(Net, self).__init__() | |
| self.conv1 = nn.Conv2d(3, 32, 3, 1) | |
| torch.nn.init.kaiming_uniform_(self.conv1.weight, mode='fan_in', nonlinearity='relu') | |
| self.conv2 = nn.Conv2d(32, 32, 3, 1) | |
| torch.nn.init.kaiming_uniform_(self.conv2.weight, mode='fan_in', nonlinearity='relu') | |
| self.conv3 = nn.Conv2d(32, 64, 3, 1) | |
| torch.nn.init.kaiming_uniform_(self.conv3.weight, mode='fan_in', nonlinearity='relu') | |
| self.conv4 = nn.Conv2d(64, 64, 3, 1) | |
| torch.nn.init.kaiming_uniform_(self.conv4.weight, mode='fan_in', nonlinearity='relu') | |
| self.pool1 = torch.nn.MaxPool2d(2) | |
| self.pool2 = torch.nn.MaxPool2d(2) | |
| self.fc1 = nn.Linear(1600, 512) | |
| self.fc2 = nn.Linear(512, 128) | |
| self.fc3 = nn.Linear(128, 10) | |
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