import tensorflow as tf

              aspp_features = split_separable_conv2d(
                  features,
                  filters=depth,
                  rate=rate,
                  weight_decay=weight_decay,
                  scope=scope)
            else:
              aspp_features = slim.conv2d(
                  features, depth, 3, rate=rate, scope=scope)
            branch_logits.append(aspp_features)

        # Merge branch logits.
        concat_logits = tf.concat(branch_logits, 3)
        if model_options.aspp_with_concat_projection:
          concat_logits = slim.conv2d(
              concat_logits, depth, 1, scope=CONCAT_PROJECTION_SCOPE)
          concat_logits = slim.dropout(
              concat_logits,
              keep_prob=0.9,
              is_training=is_training,
              scope=CONCAT_PROJECTION_SCOPE + '_dropout')
        if model_options.aspp_with_squeeze_and_excitation:
          concat_logits *= image_feature

