text: # -*- coding: utf-8 -*-
  """model.ipynb
  
  Automatically generated by Colaboratory.
  
  Original file is located at
      https://colab.research.google.com/drive/1SJW_nBi2kM2KOmN643w3i1juC3O76JSL
  """
  
  import torch.nn as nn
  import torch.nn.functional as F
  import torch.optim as optim
  
  
  class Net(nn.Module):
      def __init__(self):
          super(Net, self).__init__()
          self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
          self.conv2 = nn.Conv2d(10, 20, kernel_size=5)
          self.conv2_drop = nn.Dropout2d()
          self.fc1 = nn.Linear(320, 50)
          self.fc2 = nn.Linear(50, 10)
  
      def forward(self, x):
          x = F.relu(F.max_pool2d(self.conv1(x), 2))
          x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))
          x = x.view(-1, 320)
          x = F.relu(self.fc1(x))
          x = F.dropout(x, training=self.training)
          x = self.fc2(x)
          return F.log_softmax(x)
  