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

percnn网络单卡训练报错

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 Ascend910B

• Software Environment / 软件环境 (Mandatory / 必填):
  -- MindSpore version (e.g., 1.7.0.Bxxx) :2.3.0rc1
  -- Python version (e.g., Python 3.7.5) :3.8.0
  -- OS platform and distribution (e.g., Linux Ubuntu 16.04):Linux 10-90-66-192 4.15.0-45-generic #48-Ubuntu
  -- GCC/Compiler version (if compiled from source): 7.5.0

• 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 graph

Related testcase / 关联用例 (Mandatory / 必填)

暂无

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

1.git clone https://gitee.com/mindspore/mindscience.git
2.cd MindFlow/applications/data_mechanism_fusion/percnn
3.python {percnn_path}train.py --config_file_path {yaml} --device_target Ascend --device_id 0 --mode GRAPH

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

percnn网络训练正常

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

epoch: 6000 train loss: 0.000110330286 epoch time: 2.637ms step time: 2.644ms
Traceback (most recent call last):
File "/home/ma-user/modelarts/outputs/train_url_0/MindSporeLab_Test/source_code/mindscience/MindFlow/applications/data_mechanism_fusion/percnn/burgers_2d/train.py", line 191, in
train(args)
File "/home/ma-user/modelarts/outputs/train_url_0/MindSporeLab_Test/source_code/mindscience/MindFlow/mindflow/utils/time_utils.py", line 11, in wrapper
func(*args, **kwargs)
File "/home/ma-user/modelarts/outputs/train_url_0/MindSporeLab_Test/source_code/mindscience/MindFlow/applications/data_mechanism_fusion/percnn/burgers_2d/train.py", line 178, in train
train_stage(percnn_trainer, 'finetune', pattern, optimizer_config['finetune'], ckpt_dir, use_ascend)
File "/home/ma-user/modelarts/outputs/train_url_0/MindSporeLab_Test/source_code/mindscience/MindFlow/applications/data_mechanism_fusion/percnn/burgers_2d/train.py", line 94, in train_stage
step_train_loss, loss_data, loss_ic, loss_phy, loss_valid = train_step()
File "/home/ma-user/anaconda3/envs/Python380/lib/python3.8/site-packages/mindspore/common/api.py", line 742, in staging_specialize
out = _MindsporeFunctionExecutor(func, hash_obj, input_signature, process_obj, jit_config)(*args, **kwargs)
File "/home/ma-user/anaconda3/envs/Python380/lib/python3.8/site-packages/mindspore/common/api.py", line 131, in wrapper
results = fn(*arg, **kwargs)
File "/home/ma-user/anaconda3/envs/Python380/lib/python3.8/site-packages/mindspore/common/api.py", line 361, in call
raise err
File "/home/ma-user/anaconda3/envs/Python380/lib/python3.8/site-packages/mindspore/common/api.py", line 358, in call
phase = self.compile(self.fn.name, *args_list, **kwargs)
File "/home/ma-user/anaconda3/envs/Python380/lib/python3.8/site-packages/mindspore/common/api.py", line 450, in compile
is_compile = self._graph_executor.compile(self.fn, compile_args, kwargs, phase, True)
TypeError: For primitive[Conv2D], the input type must be same.
name:[w]:Tensor[Float16].
name:[x]:Tensor[Float32].

• C++ Call Stack: (For framework developers)

mindspore/core/utils/check_convert_utils.cc:1128 CheckTypeSame

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