models.py

import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision import models

class SimpleCNN(nn.Module):
    def __init__(self):
        super(SimpleCNN, self).__init__()
        self.conv1 = nn.Conv2d(1, 32, kernel_size=3)
        self.conv2 = nn.Conv2d(32, 64, kernel_size=3)
        self.fc1 = nn.Linear(64 * 12 * 12, 128)
        self.fc2 = nn.Linear(128, 10)

    def forward(self, x):
        x = F.relu(self.conv1(x))
        x = F.relu(self.conv2(x))
        x = F.max_pool2d(x, 2)
        x = torch.flatten(x, 1)
        x = F.relu(self.fc1(x))
        x = self.fc2(x)
        return x
    
def get_resnet18_for_cifar10():
    torch.manual_seed(42)
    model = models.resnet18()
    
    num_ftrs = model.fc.in_features
    model.fc = nn.Linear(num_ftrs, 10)

    return model