Created by: hubu-wangpei

版本： Name: paddlepaddle Version: 1.7.1 保存了模型后，运行下面的代码报错 ValueError: type to initialized an Operator can not be None.

place = fluid.CPUPlace()
exe = fluid.Executor(place)

path = "./saved_infer_model"

[inference_program, feed_target_names, fetch_targets] = (fluid.io.load_inference_model(dirname=path, executor=exe))

报错

---------------------------------------------------------------------------ValueError                                Traceback (most recent call last)<ipython-input-39-188e36eee31c> in <module>
      7 
      8 # 示例一: 不需要指定分布式查找表的模型加载示例，即训练时未用到distributed lookup table。
----> 9 [inference_program, feed_target_names, fetch_targets] = (fluid.io.load_inference_model(dirname=path, executor=exe))
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/io.py in load_inference_model(dirname, executor, model_filename, params_filename, pserver_endpoints)
   1369         params_filename = params_filename
   1370 
-> 1371     program = Program.parse_from_string(program_desc_str)
   1372     if not core._is_program_version_supported(program._version()):
   1373         raise ValueError("Unsupported program version: %d\n" %
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/framework.py in parse_from_string(binary_str)
   4230         p.desc = core.ProgramDesc(binary_str)
   4231         p.blocks = [Block(p, i) for i in six.moves.range(p.desc.num_blocks())]
-> 4232         p._sync_with_cpp()
   4233         return p
   4234 
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/framework.py in _sync_with_cpp(self)
   4424             self.blocks.append(Block(self, block_idx))
   4425         for block in self.blocks:
-> 4426             block._sync_with_cpp()
   4427 
   4428     def _copy_param_info_from(self, other):
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/framework.py in _sync_with_cpp(self)
   2643         for index in range((end_index + 1), len(ops_in_cpp)):
   2644             op_desc = ops_in_cpp[index]
-> 2645             op = Operator(self, op_desc)
   2646             self.ops.append(op)
   2647 
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/framework.py in __init__(self, block, desc, type, inputs, outputs, attrs)
   1757             if type is None:
   1758                 raise ValueError(
-> 1759                     "`type` to initialized an Operator can not be None.")
   1760             self._type = type
   1761             self.attrs = attrs if attrs else {}
ValueError: `type` to initialized an Operator can not be None.

运行load_inference_model这个示例也报同样的错误

import paddle.fluid as fluid
import numpy as np

# 构建模型
main_prog = fluid.Program()
startup_prog = fluid.Program()
with fluid.program_guard(main_prog, startup_prog):
    data = fluid.layers.data(name="img", shape=[64, 784], append_batch_size=False)
    w = fluid.layers.create_parameter(shape=[784, 200], dtype='float32')
    b = fluid.layers.create_parameter(shape=[200], dtype='float32')
    hidden_w = fluid.layers.matmul(x=data, y=w)
    hidden_b = fluid.layers.elementwise_add(hidden_w, b)
place = fluid.CPUPlace()
exe = fluid.Executor(place)
exe.run(startup_prog)

# 保存预测模型
path = "./infer_model"
fluid.io.save_inference_model(dirname=path, feeded_var_names=['img'],target_vars=[hidden_b], executor=exe, main_program=main_prog)

# 示例一: 不需要指定分布式查找表的模型加载示例，即训练时未用到distributed lookup table。
[inference_program, feed_target_names, fetch_targets] = (fluid.io.load_inference_model(dirname=path, executor=exe))
tensor_img = np.array(np.random.random((1, 64, 784)), dtype=np.float32)
results = exe.run(inference_program,
          feed={feed_target_names[0]: tensor_img},
          fetch_list=fetch_targets)