class_docstr: A convolution, batch norm, ReLU block.
  
  A block in a feedforward network that performs a
  convolution followed by batch normalization followed
  by a ReLU activation.
  
  For the convolution operation, a square filter size is used.
  
  Args:
      out_channels (int): The number of output channels.
      ksize (int): The size of the filter is ksize x ksize.
      pad (int): The padding to use for the convolution.
code: def __call__(self, x):
      h = self.conv(x)
      h = self.bn(h)
      return F.relu(h)
  
file_path: chainer/examples/static_graph_optimizations/cifar/models/VGG.py
imports: import chainer
  import chainer.functions
  import chainer.links
  from chainer import static_graph
label_desc: Use image node_id 2 for calling the Block obj's underlying member method code with example usage: obj.__call__(x) and returns: F