simple_model.py

import torch.nn as nn

class SimpleCNN(nn.Module):
    """Simple CNN for testing Conv2d and BatchNorm support"""
    def __init__(self):
        super().__init__()
        self.conv1 = nn.Conv2d(3, 16, kernel_size=3, padding=1)
        self.bn1 = nn.BatchNorm2d(16)
        self.relu1 = nn.ReLU()
        self.conv2 = nn.Conv2d(16, 32, kernel_size=3, padding=1)
        self.relu2 = nn.ReLU()
        self.fc = nn.Linear(32 * 8 * 8, 10)  # Assuming 8x8 after operations

    def forward(self, x):
        x = self.relu1(self.bn1(self.conv1(x)))
        x = self.relu2(self.conv2(x))
        x = x.view(x.size(0), -1)  # Flatten
        x = self.fc(x)
        return x

class SimpleModel(nn.Module):
    """Original simple model for backward compatibility"""
    def __init__(self):
        super().__init__()
        self.fc1 = nn.Linear(4, 4)
        self.relu = nn.ReLU()
        self.fc2 = nn.Linear(4, 2)

    def forward(self, x):
        return self.fc2(self.relu(self.fc1(x)))