block2.py

import torch.nn.functional as F

class MyCNNClassifier(nn.Module):
    def __init__(self, in_c, n_classes):
        super().__init__()
        self.conv1 = nn.Conv2d(in_c, 32, kernel_size=3, stride=1, padding=1)
        self.bn1 = nn.BatchNorm2d(32)
        
        self.conv2 = nn.Conv2d(32, 64, kernel_size=3, stride=1, padding=1)
        self.bn2 = nn.BatchNorm2d(32)

        self.fc1 = nn.Linear(32 * 28 * 28, 1024)
        self.fc2 = nn.Linear(1024, n_classes)
        
    def forward(self, x):
        x = self.conv1(x)
        x = self.bn1(x)
        x = F.relu(x)
        
        x = self.conv2(x)
        x = self.bn2(x)
        x = F.relu(x)

        x = x.view(x.size(0), -1) # flat
        
        x = self.fc1(x)
        x = F.sigmoid(x)
        x = self.fc2(x)
        
        return x