# 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()