[ST][MS][2.3]GPU环境,pynative模式下,动态shape场景使用ms_function,报错ValueError: For primitive[Reshape], the accumulate of x_shape must be equal to out_shape

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Bug Report	Use this template for reporting a bug	kind/bug

Describe the current behavior / 问题描述 (Mandatory / 必填)

ValueError: For primitive[Reshape], the accumulate of x_shape must be equal to out_shape, but got x_shape: [const vector]{32, 3}, and out_shape: [const vector]{[0]:{32}, [1]:{3}, [2]:{1}, [3]:{1}, [4]:{32}, [5]:{3}, [6]:{1}, [7]:{1}, [8]:{32}, [9]:{3}, [10]:{1}, [11]:{1}, [12]:{32}, [13]:{3}, [14]:{1}, [15]:{1}} 。
在只跑graph模式，或者去掉顶层的ms_function后，就没有问题

Environment / 环境信息 (Mandatory / 必填)

Hardware Environment(Ascend/GPU/CPU) / 硬件环境:

Please delete the backend not involved / 请删除不涉及的后端:
/device GPU

Software Environment / 软件环境 (Mandatory / 必填):
-- MindSpore version (e.g., 1.7.0.Bxxx) :Mindspore 2.3 B210
-- Python version (e.g., Python 3.7.5) :python 3.9
-- OS platform and distribution (e.g., Linux Ubuntu 16.04):
-- GCC/Compiler version (if compiled from source):
Excute Mode / 执行模式 (Mandatory / 必填)(PyNative/Graph):

Please delete the mode not involved / 请删除不涉及的模式:
/mode pynative

Related testcase / 关联用例 (Mandatory / 必填)

test_ms_dynamic_shape_msfunc_multiplecell_0001.py

Steps to reproduce the issue / 重现步骤 (Mandatory / 必填)

获取solution test仓
export TRAIN_MODE=PYNATIVE_MODE
source ~/workspace/TDT_deployment/solution_test/env_set.source -e CUDA11.6
cd solution_test/cases/03subject_test/02usability/model_develop/dynamic_shape/
pytest -s test_ms_dynamic_shape_msfunc_multiplecell_0001.py

Describe the expected behavior / 预期结果 (Mandatory / 必填)

Related log / screenshot / 日志 / 截图 (Mandatory / 必填)

Traceback (most recent call last):
  File "train_dynamic_net.py", line 394, in <module>
    train_net_with_model()
  File "train_dynamic_net.py", line 233, in train_net_with_model
    sink_size=config.sink_size)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/train/model.py", line 1094, in train
    initial_epoch=initial_epoch)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/train/model.py", line 115, in wrapper
    func(self, *args, **kwargs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/train/model.py", line 644, in _train
    cb_params, sink_size, initial_epoch, valid_infos)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/train/model.py", line 728, in _train_dataset_sink_process
    outputs = train_network(*inputs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/nn/cell.py", line 698, in __call__
    raise err
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/nn/cell.py", line 694, in __call__
    output = self._run_construct(args, kwargs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/nn/cell.py", line 482, in _run_construct
    output = self.construct(*cast_inputs, **kwargs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/train/dataset_helper.py", line 109, in construct
    return self.network(*outputs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/nn/cell.py", line 698, in __call__
    raise err
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/nn/cell.py", line 694, in __call__
    output = self._run_construct(args, kwargs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/nn/cell.py", line 482, in _run_construct
    output = self.construct(*cast_inputs, **kwargs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py", line 418, in construct
    return self._no_sens_impl(*inputs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py", line 434, in _no_sens_impl
    grads = self.grad_no_sens(self.network, self.weights)(*inputs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/ops/composite/base.py", line 389, in after_grad
    return grad_(fn, weights)(*args, **kwargs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/common/api.py", line 131, in wrapper
    results = fn(*arg, **kwargs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/ops/composite/base.py", line 378, in after_grad
    out = _pynative_executor.grad(fn, grad_, weights, self.grad_position, *args, **kwargs)
  File "/home/miniconda3/envs/tt2/lib/python3.7/site-packages/mindspore/common/api.py", line 1298, in grad
    return self._executor.grad(grad, obj, weights, grad_position, *args, *(kwargs.values()))
ValueError: For primitive[Reshape], the accumulate of x_shape must be equal to out_shape, but got x_shape: [const vector]{32, 3}, and out_shape: [const vector]{[0]:{32}, [1]:{3}, [2]:{1}, [3]:{1}, [4]:{32}, [5]:{3}, [6]:{1}, [7]:{1}, [8]:{32}, [9]:{3}, [10]:{1}, [11]:{1}, [12]:{32}, [13]:{3}, [14]:{1}, [15]:{1}}

----------------------------------------------------
- C++ Call Stack: (For framework developers)
----------------------------------------------------
mindspore/core/ops/ops_func_impl/reshape.cc:78 InferShape

Special notes for this issue/备注 (Optional / 选填)

Please assign maintainer to check this issue.
请为此issue分配处理人。
@田桐

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