import torch.nn as nn

# Define CNN Model
class CatDogClassifier(nn.Module):
    def __init__(self, img_size=128):
        super(CatDogClassifier, self).__init__()
        self.conv1 = nn.Conv2d(3, 32, kernel_size=3, padding=1)
        self.conv2 = nn.Conv2d(32, 64, kernel_size=3, padding=1)
        self.pool = nn.MaxPool2d(2, 2)
        self.fc1 = nn.Linear(64 * (img_size//4) * (img_size//4), 128)
        self.fc2 = nn.Linear(128, 2)
        self.relu = nn.ReLU()

    def forward(self, x):
        x = self.pool(self.relu(self.conv1(x)))
        x = self.pool(self.relu(self.conv2(x)))
        x = x.view(x.size(0), -1) # Flattening
        x = self.relu(self.fc1(x))
        x = self.fc2(x)
        return x