1 报错形容1.1 零碎环境ardware Environment(Ascend/GPU/CPU): CPUSoftware Environment:– MindSpore version (source or binary): 1.6.0– Python version (e.g., Python 3.7.5): 3.7.6– OS platform and distribution (e.g., Linux Ubuntu 16.04): Ubuntu 4.15.0-74-generic– GCC/Compiler version (if compiled from source):1.2 根本信息1.2.1脚本此案例应用mindspore.dataset自定义数据集：import os
import numpy as np
from PIL import Image
import mindspore.common.dtype as mstype
import mindspore.dataset as ds
import mindspore.dataset.transforms.c_transforms as C
import mindspore.dataset.vision.c_transforms as vc

class _dcp_Dataset:

def __init__(self,img_root_dir,device_target="CPU"):    if not os.path.exists(img_root_dir):        raise RuntimeError(f"the input image dir {img_root_dir} is invalid")    self.img_root_dir=img_root_dir    self.img_names=[i for i in os.listdir(img_root_dir) if i.endswith(".jpg")]    self.target=device_targetdef __len__(self):    return len(self.img_names)def __getitem__(self, index):    img_name=self.img_names[index]    im=Image.open(os.path.join(self.img_root_dir,img_name))    image=np.array(im)    label_str=img_name.split("_")[-1]    label_str=label_str.split(".")[0]    label=np.array(label_str)    return image,label

def creat_dataset(dataset_path,batch_size=2,num_shards=1,shard_id=0,device_target="CPU"):

dataset=_dcp_Dataset(dataset_path,device_target)data_set=ds.GeneratorDataset(dataset,["image","label"],shuffle=True,num_shards=1,shard_id=0)image_trans=[    vc.Resize((224,224)),    vc.RandomHorizontalFlip(),    vc.Rescale(1/255,shift=0),    vc.Normalize((0.4465, 0.4822, 0.4914), (0.2010, 0.1994, 0.2023)),    vc.HWC2CHW]label_trans=[C.TypeCast(mstype.int32)]data_set=data_set.map(operations=image_trans,input_columns=["image"])data_set=data_set.map(operations=label_trans,input_columns=["label"])# data_set=data_set.shuffle(buffer_size=batch_size)data_set=data_set.batch(batch_size=batch_size,drop_remainder=True)# data_set=data_set.repeat(1)return data_set

if name == '__main__':
data=creat_dataset("./image_DCP")
print(data)
data_loader = data.create_dict_iterator()
for i, data in enumerate(data_loader):

    print(i)    print(data)

1.2.2报错报错信息：

2 起因剖析以及解决办法

此处短少(),将此处代码改为 vc.HWC2CHW() 可失常执行。3 总结定位问题的步骤例如：有 xxDataset -> map -> map -> batch 这样的数据处理流程。能够按如下形式调试脚本：只保留 xxDataset，而后运行下脚本，查看是否报错；保留 xxDataset -> map，而后运行下脚本，查看是否报错；保留 xxDataset -> map -> map，而后运行下脚本，查看是否报错；保留 xxDataset -> map -> map -> batch，而后运行下脚本，查看是否报错；依照上述的办法，可定位到是哪个map/batch出错了。