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Thank you for contributing to PaddlePaddle. Before submitting the issue, you could search issue in the github in case that th If there is no solution,please make sure that this is an inference issue including the following details : System information -PaddlePaddle version （eg.1.1）or CommitID -CPU: including CPUMKL/OpenBlas/MKLDNN version -GPU: including CUDA/CUDNN version -OS Platform (eg.Mac OS 10.14) -Python version -Cmake orders -C++version.txt -API information To Reproduce Steps to reproduce the behavior Describe your current behavior Code to reproduce the issue Other info / logs

预测报错： Traceback (most recent call last): File "dcn_infer.py", line 117, in <module> infer() File "dcn_infer.py", line 107, in infer fetch_list=[v.name for v in fetch_list]) File "/home/work/tools/paddle/paddle_release_home/python/lib/python2.7/site-packages/paddle/fluid/executor.py", line 565, in run use_program_cache=use_program_cache) File "/home/work/tools/paddle/paddle_release_home/python/lib/python2.7/site-packages/paddle/fluid/executor.py", line 642, in _run exe.run(program.desc, scope, 0, True, True, fetch_var_name) paddle.fluid.core.EnforceNotMet: Invoke operator mul error. Python Callstacks: File "/home/work/tools/paddle/paddle_release_home/python/lib/python2.7/site-packages/paddle/fluid/framework.py", line 1654, in append_op attrs=kwargs.get("attrs", None)) File "/home/work/tools/paddle/paddle_release_home/python/lib/python2.7/site-packages/paddle/fluid/layer_helper.py", line 43, in append_op return self.main_program.current_block().append_op(*args, **kwargs) File "/home/work/tools/paddle/paddle_release_home/python/lib/python2.7/site-packages/paddle/fluid/layers/nn.py", line 326, in fc "y_num_col_dims": 1}) File "/home/work/shulei/msd_dcn_v1/fluid_dcn.py", line 112, in DCN ctr_predict = fluid.layers.fc(input=ctr_fc,size=2, act="softmax", param_attr=fluid.ParamAttr(initializer=fluid.initializer.Normal(scale=1 / math.sqrt(ctr_fc.shape[1])))) File "dcn_infer.py", line 96, in infer ctr_predict, dura_predict ,words = DCN(args, feat_list.features) File "dcn_infer.py", line 117, in <module> infer() C++ Callstacks: Input Y(0)is not initialized at [/paddle/paddle/fluid/framework/operator.cc:1142]

预测部分代码： `args = parse_args()

place = fluid.CPUPlace()
inference_scope = fluid.core.Scope()

feat_list = dcn_reader.Msd_Feat_Builder(args.feat_list_path, args.bucket_statistic)
dataset = dcn_reader.MsdDataset(feat_list.features, args.data_path, args.mapping_path, args.seccate_map_path)
dataset.prepare_read()
test_reader = paddle.batch(dataset.infer(), batch_size=args.batch_size)

exe = fluid.Executor(place)
ctr_predict, dura_predict ,words = DCN(args, feat_list.features)
#[inference_program, feed_target_names, fetch_targets] = fluid.io.load_inference_model(executor=exe, dirname=args.model_path)
def if_exist(var):
    return os.path.exists(os.path.join(args.model_path, var.name))
#[inference_program, feed_target_names, fetch_targets] = fluid.io.load_vars(executor=exe, dirname=args.model_path, predicate=if_exist)
fluid.io.load_vars(executor=exe, dirname=args.model_path, predicate=if_exist)
feeder = fluid.DataFeeder(feed_list=words, place=place)
fetch_list = [ctr_predict]
for batch_id, data in enumerate(test_reader()):
    print data
    predict = exe.run(feed=feeder.feed(data),
                    fetch_list=[v.name for v in fetch_list])
    for i in range(len(data)):
        print predict[0][i][1]
exe.close()`

模型部分代码：

`sparse_embed_seq = list(starmap(embedding_layer, zip(words[1 : 1 + sparse_input_length], sparse_attr_names, sparse_attr_size)))

concated = fluid.layers.concat(sparse_embed_seq  + words[0:1] , axis=1)

last_deep_layer = deepnet(concated, args)
last_cross_layer = crossnet(concated, args)

top_fc_input = fluid.layers.concat([last_deep_layer, last_cross_layer], axis=1)

top_fc = fc_block(top_fc_input, np.fromstring(args.top_fc_block,dtype=int, sep="-").tolist())

ctr_fc = fluid.layers.fc(input=top_fc,size=128,act='relu',param_attr=fluid.ParamAttr(initializer=fluid.initializer.Normal(scale=1 / math.sqrt(top_fc.shape[1]))))

#duration_fc = fluid.layers.fc(input=top_fc,size=128,act='relu',param_attr=fluid.ParamAttr(initializer=fluid.initializer.Normal(scale=1 / math.sqrt(top_fc.shape[1]))))

ctr_predict = fluid.layers.fc(input=ctr_fc,size=2, act="softmax", param_attr=fluid.ParamAttr(initializer=fluid.initializer.Normal(scale=1 / math.sqrt(ctr_fc.shape[1]))))

dura_predict = fluid.layers.fc(input=ctr_fc,size=1, act=None, param_attr=fluid.ParamAttr(initializer=fluid.initializer.Normal(scale=1 / math.sqrt(ctr_fc.shape[1]))))`