关于机器学习:MindSpore报错TypeError-parse-missing-1-required-positional

35次阅读

共计 2234 个字符,预计需要花费 6 分钟才能阅读完成。

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_target

def __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。

正文完
 0