title: How to define specific number of convolutional kernels/filters in pytorch?
body: <p>On pytorch website they have the following model in their tutorial</p>
  
  <pre><code>class BasicCNN(nn.Module):
      def __init__(self):
          super(BasicCNN, self).__init__()
          self.conv1 = nn.Conv2d(3, 6, 5)
          self.pool = nn.MaxPool2d(2, 2)
          self.conv2 = nn.Conv2d(6, 16, 5)
          self.fc1 = nn.Linear(16 * 5 * 5, 120)
          self.fc2 = nn.Linear(120, 84)
          self.fc3 = nn.Linear(84, 10)
  
      def forward(self, x):
          x = x.permute(0, 3, 1, 2)
          x = self.pool(F.relu(self.conv1(x)))
          x = self.pool(F.relu(self.conv2(x)))
          x = x.view(-1, 16 * 5 * 5)
          x = F.relu(self.fc1(x))
          x = F.relu(self.fc2(x))
          x = self.fc3(x)
          return x
  </code></pre>
  
  <p>How many kernels/filters this model has? Is it two - e.g conv1 and conv2. How do I easily create many filters by specifying the number of them? For example 100 filters.</p>
  
  <p>Thanks!</p>