model.py

import torch
import torch.nn as nn


class CatDogCNN(nn.Module):
    def __init__(self, input_channels=3, num_classes=2):
        super().__init__()

        self.features = nn.Sequential(
            nn.Conv2d(input_channels, 32, kernel_size=3, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(2),
            nn.Conv2d(32, 64, kernel_size=3, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(2),
            nn.Conv2d(64, 128, kernel_size=3, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(2),
        )

        self.classifier = nn.Sequential(
            nn.Flatten(),
            nn.Linear(128 * 8 * 8, 256),
            nn.ReLU(),
            nn.Dropout(0.3),
            nn.Linear(256, num_classes),
        )

    def forward(self, x):
        x = self.features(x)
        x = self.classifier(x)
        return x