import tensorflow as tf

            conv.get_shape())
      else:
        self.top_layer = conv
        self.top_size = num_out_channels
        biased = self.batch_norm(**self.batch_norm_config)
      if activation == 'relu':
        conv1 = tf.nn.relu(biased)
      elif activation == 'linear' or activation is None:
        conv1 = biased
      elif activation == 'tanh':
        conv1 = tf.nn.tanh(biased)
      else:
