model.py

import torch
import torch.nn as nn
# Define the model
class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.fc1 = nn.Linear(28*28, 128)  # MNIST images are 28x28
        self.fc2 = nn.Linear(128, 64)
        self.fc3 = nn.Linear(64, 10)  # There are 10 classes (0 through 9)

    def forward(self, x):
        x = x.view(x.shape[0], -1)  # Flatten the input
        x = torch.relu(self.fc1(x))
        x = torch.relu(self.fc2(x))
        return self.fc3(x)