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| # model.py | |
| import torch.nn as nn | |
| import torch.nn.functional as F | |
| classes = ['airplane', 'automobile', 'bird', 'cat', 'deer', | |
| 'dog', 'frog', 'horse', 'ship', 'truck'] | |
| class Net(nn.Module): | |
| def __init__(self): | |
| super(Net, self).__init__() | |
| self.conv1 = nn.Conv2d(in_channels=3, out_channels=32, kernel_size=3, padding=1) | |
| self.bn1 = nn.BatchNorm2d(32) | |
| self.relu1 = nn.ReLU() | |
| self.conv2 = nn.Conv2d(in_channels=32, out_channels=64, kernel_size=3, padding=1) | |
| self.bn2 = nn.BatchNorm2d(64) | |
| self.relu2 = nn.ReLU() | |
| self.maxpool1 = nn.MaxPool2d(kernel_size=2, stride=2) | |
| self.conv3 = nn.Conv2d(in_channels=64, out_channels=128, kernel_size=3, padding=1) | |
| self.bn3 = nn.BatchNorm2d(128) | |
| self.relu3 = nn.ReLU() | |
| self.conv4 = nn.Conv2d(in_channels=128, out_channels=256, kernel_size=3, padding=1) | |
| self.bn4 = nn.BatchNorm2d(256) | |
| self.relu4 = nn.ReLU() | |
| self.maxpool2 = nn.MaxPool2d(kernel_size=2, stride=2) | |
| self.conv5 = nn.Conv2d(in_channels=256, out_channels=512, kernel_size=3, padding=1) | |
| self.bn5 = nn.BatchNorm2d(512) | |
| self.relu5 = nn.ReLU() | |
| self.conv6 = nn.Conv2d(in_channels=512, out_channels=1024, kernel_size=3, padding=1) | |
| self.bn6 = nn.BatchNorm2d(1024) | |
| self.relu6 = nn.ReLU() | |
| self.maxpool3 = nn.MaxPool2d(kernel_size=2, stride=2) | |
| self.fc1 = nn.Linear(in_features=4 * 4 * 1024, out_features=512) | |
| self.relu7 = nn.ReLU() | |
| self.dropout1 = nn.Dropout(p=0.5) | |
| self.fc2 = nn.Linear(in_features=512, out_features=10) | |
| def forward(self, x): | |
| x = self.conv1(x) | |
| x = self.bn1(x) | |
| x = self.relu1(x) | |
| x = self.conv2(x) | |
| x = self.bn2(x) | |
| x = self.relu2(x) | |
| x = self.maxpool1(x) | |
| x = self.conv3(x) | |
| x = self.bn3(x) | |
| x = self.relu3(x) | |
| x = self.conv4(x) | |
| x = self.bn4(x) | |
| x = self.relu4(x) | |
| x = self.maxpool2(x) | |
| x = self.conv5(x) | |
| x = self.bn5(x) | |
| x = self.relu5(x) | |
| x = self.conv6(x) | |
| x = self.bn6(x) | |
| x = self.relu6(x) | |
| x = self.maxpool3(x) | |
| x = x.view(x.size(0), -1) | |
| x = self.fc1(x) | |
| x = self.relu7(x) | |
| x = self.dropout1(x) | |
| x = self.fc2(x) | |
| return x | |
| model = Net() | |