text: import torch
  import torch.nn as nn
  import torch.nn.functional as F
  
  
  class toy_conv(nn.Module):
      def __init__(self, in_channels=1, num_classes=10):
          super().__init__()
          self.conv1 = nn.Conv2d(in_channels, 32, 3, 1)
          self.conv2 = nn.Conv2d(32, 64, 3, 1)
          self.dropout1 = nn.Dropout(0.25)
          self.dropout2 = nn.Dropout(0.5)
          self.fc1 = nn.Linear(9216, 128)
          self.fc2 = nn.Linear(128, num_classes)
  
      def forward(self, x):
          x = self.conv1(x)
          x = F.relu(x)
          x = self.conv2(x)
          x = F.relu(x)
          x = F.max_pool2d(x, 2)
          x = self.dropout1(x)
          x = torch.flatten(x, 1)
          x = self.fc1(x)
          x = F.relu(x)
          x = self.dropout2(x)
          x = self.fc2(x)
          output = F.log_softmax(x, dim=1)
          return output
  