import tensorflow as tf

      self.top_size = depth
      return output

  def inception_module(self, name, cols, input_layer=None, in_size=None):
    if input_layer is None:
      input_layer = self.top_layer
    if in_size is None:
      in_size = self.top_size
    name += str(self.counts[name])
    self.counts[name] += 1
    with tf.variable_scope(name):
      col_layers = []
      col_layer_sizes = []
      for c, col in enumerate(cols):
        col_layers.append([])
        col_layer_sizes.append([])
        for l, layer in enumerate(col):
          ltype, args = layer[0], layer[1:]
          kwargs = {
              'input_layer': input_layer,
