score = fused deconv_final = self.deconv2d(inputdata=score, out_channel=64, kernel_size=16, stride=8, use_bias=False, name='deconv_final') score_final = self.conv2d(inputdata=deconv_final, out_channel=2, kernel_size=1, use_bias=False, name='score_final') ret['logits'] = score_final ret['deconv'] = deconv_final return ret if __name__ == '__main__': vgg_encoder = vgg_encoder.VGG16Encoder(phase=tf.constant('train', tf.string)) dense_encoder = dense_encoder.DenseEncoder(l=40, growthrate=12, with_bc=True, phase='train', n=5) decoder = FCNDecoder(phase='train') in_tensor = tf.placeholder(dtype=tf.float32, shape=[None, 256, 512, 3], name='input') vgg_encode_ret = vgg_encoder.encode(in_tensor, name='vgg_encoder') dense_encode_ret = dense_encoder.encode(in_tensor, name='dense_encoder') decode_ret = decoder.decode(vgg_encode_ret, name='decoder', decode_layer_list=['pool5', 'pool4', 'pool3'])