小编Raj*_*gah的帖子

在 fastai v2 中我试图添加图像增强

所以

tfms = aug_transforms(do_flip = True,
                                 flip_vert=True, 
                                 max_lighting=0.1, 
                                 )
data = ImageDataLoaders.from_df(df,bs=5,item_tfms=tfms,folder=path_to_data)

这给出了输出

Could not do one pass in your dataloader, there is something wrong in it

当我这样做时

data.show_batch()

它给

RuntimeError: "check_uniform_bounds" not implemented for 'Byte'

如何解决

我将 databunch 定义为

data = (TabularList.from_df(train_df, path='./', cont_names=cont_names, procs=procs)
                           .split_by_idx(list(range(500,3000)))
                           .label_from_df(cols=dep_var)
                           .add_test(test, label=0)
                           .databunch())

训练后我是

p = learn3.get_preds()
len(p[1])

o/p 是 2500，正确的是

                       .split_by_idx(list(range(500,3000)))

这是 2500 个号码

for index in range(len(test_df)):
    predictions = learn3.predict(test_df.iloc[index])
    predictions = predictions[1].tolist()
    print(index)

这将花费大量的时间。我想通过 test_df 并获得预测

p = learn3.get_preds()

我怎样才能做到这一点 ？

                       .split_by_idx(list(range(500,3000)))

我们有办法替换它并从其他文件传递数据吗？

当我通过 ssh 运行此命令到 aws 实例时

docker run hello-world
aws ecr get-login --no-include-email --region ap-south-1 > ./login
source ./login

它输出

WARNING! Using --password via the CLI is insecure. Use --password-stdin.
WARNING! Your password will be stored unencrypted in /home/ubuntu/.docker/config.json.
Configure a credential helper to remove this warning. See
https://docs.docker.com/engine/reference/commandline/login/#credentials-store

Login Succeeded

Run Code Online (Sandbox Code Playgroud)

这就是成功。但是当在詹金斯中输入相同的命令时 输出是

1. 我通过添加用户

   sudo usermod -a -G docker jenkins
   sudo usermod -a -G docker user
   

   Run Code Online (Sandbox Code Playgroud)

出了什么问题？