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