import tensorflow as tf

                  filters=decoder_depth,
                  rate=1,
                  weight_decay=weight_decay,
                  scope='decoder_conv0')
              decoder_features = _split_separable_conv2d(
                  decoder_features,
                  filters=decoder_depth,
                  rate=1,
                  weight_decay=weight_decay,
                  scope='decoder_conv1')
            else:
              num_convs = 2
              decoder_features = slim.repeat(
                  tf.concat(decoder_features_list, 3),
                  num_convs,
                  slim.conv2d,
                  decoder_depth,
                  3,
                  scope='decoder_conv' + str(i))
          return decoder_features


def _get_branch_logits(features,
                       num_classes,
                       atrous_rates=None,
                       aspp_with_batch_norm=False,
