fact.mindspore_semi_parallel_impl(parallel_net, dataset=parallel_dataset, epoch=1,
>                                         device_num=8)

../test_parallel_shard_layout.py:2695:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../pipeline_split/test_pipeline.py:297: in mindspore_semi_parallel_impl
    dataset_strategy=dataset_strategy, **kwargs)
../../pipeline_split/test_pipeline.py:278: in __mindspore_impl
    eval_network=eval_network)
../../pipeline_split/test_pipeline.py:238: in _model_train_and_save_ckpt
    dataset_sink_mode=self.dataset_sink_mode)
/root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/train/model.py:1074: in train
    initial_epoch=initial_epoch)
/root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/train/model.py:114: in wrapper
    func(self, *args, **kwargs)
/root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/train/model.py:617: in _train
    self._train_process(epoch, train_dataset, list_callback, cb_params, initial_epoch, valid_infos)
/root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/train/model.py:919: in _train_process
    outputs = self._train_network(*next_element)
/root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/nn/cell.py:662: in __call__
    out = self.compile_and_run(*args, **kwargs)
/root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/nn/cell.py:980: in compile_and_run
    self.compile(*args, **kwargs)
/root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/nn/cell.py:964: in compile
    jit_config_dict=self._jit_config_dict, **kwargs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <mindspore.common.api._CellGraphExecutor object at 0xfffea3397610>
obj = TrainOneStepCell<
  (network): WithLossCell<
    (_backbone): TrainNet<
      (block): CellList<
        (0): MatMulNe...    (_loss_fn): SoftmaxCrossEntropyWithLogits<>
    >
  (optimizer): CustomOptimizer<>
  (grad_reducer): Identity<>
  >
phase = 'train.1710836617257453824.281467729116912.0', do_convert = True
jit_config_dict = {'exc_mode': 'auto', 'jit_level': 'O1', 'jit_syntax_level': ''}
args = (Tensor(shape=[128, 96], dtype=Float32, value=
[[ 1.76405239e+00,  4.00157213e-01,  9.78738010e-01 ...  9.76639032e-01...000e+00],
 [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00 ...  0.00000000e+00,  0.00000000e+00,  0.00000000e+00]]))
kwargs = {}, key_id = '2814677291169121710836617257453824', key = 0

    def compile(self, obj, *args, phase='predict', do_convert=True, jit_config_dict=None, **kwargs):
        """
        Compiles graph.

        Args:
            obj (Function/Cell): The function or cell instance need compile.
            phase (str): The name of compile phase. Default: 'predict'.
            do_convert (bool): When set to True, convert ME graph to GE graph after compiling graph.
            jit_config_dict (dict): Jit config for compile. Default: ``None``.
            args (tuple): Args of the Cell object.
            kwargs (dict): Kwargs of the Cell object.

        Return:
            Str, the full phase of the cell.
            Bool, if the graph has been compiled before, return False, else return True.
        """
        obj.__parse_method__ = 'construct'
        if not hasattr(obj, obj.__parse_method__):
            raise AttributeError(
                'The class {} dose not have method {}'.format(obj.__class__.__name__, obj.__parse_method__))
        key_id = str(id(obj)) + str(obj.create_time)
        args = get_auto_dynamic_shape_args(args, key_id)

        self.enable_tuple_broaden = False
        if hasattr(obj, "enable_tuple_broaden"):
            self.enable_tuple_broaden = obj.enable_tuple_broaden
        logger.debug(f"Convert the network: {do_convert}.")
        self._graph_executor.set_enable_tuple_broaden(self.enable_tuple_broaden)
        key = self._graph_executor.generate_arguments_key(obj, args, kwargs, self.enable_tuple_broaden)
        obj.arguments_key = str(key)
        phase = phase + '.' + str(obj.create_time) + '.' + str(id(obj)) + '.' + obj.arguments_key
        update_auto_dynamic_shape_phase(args, key_id, phase)

        if phase in obj.compile_cache and self.has_compiled(phase):
            logger.debug("%r graph has existed.", phase)
            # Release resource should be released when CompileInner won't be executed, such as cur_convert_input_
            # generated in generate_arguments_key.
            self._graph_executor.clear_compile_arguments_resource()
            return phase, False

        obj.check_names()
        _check_full_batch()
        self._set_dataset_mode(obj)
        self._set_compile_cache_dep_files(phase)

        self._graph_executor.set_weights_values(obj.parameters_dict())
        if jit_config_dict:
            self._graph_executor.set_jit_config(jit_config_dict)
        else:
            jit_config_dict = JitConfig().jit_config_dict
            self._graph_executor.set_jit_config(jit_config_dict)
>       result = self._graph_executor.compile(obj, args, kwargs, phase, self._use_vm_mode())
E       RuntimeError: The pointer[node_stra.second] is null.
E
E       ----------------------------------------------------
E       - Framework Unexpected Exception Raised:
E       ----------------------------------------------------
E       This exception is caused by framework's unexpected error. Please create an issue at https://gitee.com/mindspore/mindspore/issues to get help.
E
E       ----------------------------------------------------
E       - C++ Call Stack: (For framework developers)
E       ----------------------------------------------------
E       mindspore/ccsrc/frontend/parallel/strategy_checkpoint/strategy_checkpoint_info.cc:135 to_protobuf
E
E       ----------------------------------------------------
E       - The Traceback of Net Construct Code:
E       ----------------------------------------------------
E
E       # In file /root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py:416
E           def construct(self, *inputs):
E           ^
E
E       # In file /root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py:418
E                   return self._no_sens_impl(*inputs)
E                          ^
E
E       # In file /root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py:431
E           def _no_sens_impl(self, *inputs):
E           ^
E
E       # In file /root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py:433
E               loss = self.network(*inputs)
E                      ^
E
E       # In file /root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py:120
E           def construct(self, data, label):
E
E       # In file /root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py:121
E               out = self._backbone(data)
E                     ^
E
E       # In file /root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py:121
E               out = self._backbone(data)
E                     ^
E
E       # In file /home/zhanglin/MindSporeTest/parallel/pipeline_split/test_pipeline.py:87
E               for i in range(self.micro_size):
E
E       # In file /home/zhanglin/MindSporeTest/parallel/pipeline_split/test_pipeline.py:88
E                   x = self.block[i](x)
E                       ^
E
E       # In file /home/zhanglin/MindSporeTest/parallel/pipeline_split/test_pipeline.py:64
E               x = self.matmul1(inputs, self.matmul1_weight)
E                   ^

/root/archiconda3/envs/zhanglin3.7/lib/python3.7/site-packages/mindspore/common/api.py:1584: RuntimeError