import tensorflow as tf

          depth_bottleneck,
          1,
          1,
          stride,
          stride,
          input_layer=input_layer,
          num_channels_in=in_size)
      self.conv(depth_bottleneck, 3, 3, 1, 1, mode='SAME_RESNET')
      res = self.conv(depth, 1, 1, 1, 1, activation=None)
      output = tf.nn.relu(shortcut + res)
      self.top_layer = output
      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:
