import tensorflow as tf

                X = decoder_conf('u4', X, 256, F, 2, norm, reuse_decoder, is_train, self.args.dropout)              # 14  > 28
                X = decoder_conf('d4', X, 256, F, 1, norm, reuse_decoder, is_train, self.args.dropout)              # 28  > 30
                if self.args.skip_connections: X = tf.concat((X, X1), axis=-1)
                X = decoder_conf('u5', X, 128, F, 2, norm, reuse_decoder, is_train, self.args.dropout)              # 30  > 60
                X_LATE = X
                X = decoder_conf('d5', X, 128, F, 1, norm, reuse_decoder, is_train, self.args.dropout)              # 60  > 62
                if self.args.skip_connections: X = tf.concat((X, X0), axis=-1)
                X = decoder_conf('u6', X, 64, F, 2, norm, reuse_decoder, is_train, self.args.dropout)               # 62  > 124
                X = decoder_conf('d6', X, 64, 5, 1, norm, reuse_decoder, is_train, self.args.dropout)               # 124 > 128

                X = decoder_conf('out', X, self.args.num_classes, 1, 1, '', reuse_decoder, is_train, slope=1.0, stddev=0.02,
                                use_bias=False)
