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0288ed5 47a1d55 0288ed5 | 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 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | # 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()
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