C:\Users\Jinu Augustine\Documents\Solidaridad FAQ Bot>docker run 4145b1589e68
2020-08-21 15:46:25 INFO     rasa_sdk.endpoint  - Starting action endpoint server...
2020-08-21 15:46:25 INFO     transformers.file_utils  - PyTorch version 1.6.0 available.
2020-08-21 15:46:26 INFO     root  - Load pretrained SentenceTransformer: bert-base-nli-mean-tokens
2020-08-21 15:46:26 INFO     root  - Did not find a '/' or '\' in the name. Assume to download model from server.
Traceback (most recent call last):
  File "/usr/local/lib/python3.7/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/local/lib/python3.7/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/app/rasa_sdk/__main__.py", line 34, in <module>
    main()
  File "/app/rasa_sdk/__main__.py", line 30, in main
    main_from_args(cmdline_args)
  File "/app/rasa_sdk/__main__.py", line 21, in main_from_args
    args.auto_reload,
  File "/app/rasa_sdk/endpoint.py", line 137, in run
    action_package_name, cors_origins=cors_origins, auto_reload=auto_reload
  File "/app/rasa_sdk/endpoint.py", line 80, in create_app
    executor.register_package(action_package_name)
  File "/app/rasa_sdk/executor.py", line 249, in register_package
    self._import_submodules(package)
  File "/app/rasa_sdk/executor.py", line 205, in _import_submodules
    package = self._import_module(package)
  File "/app/rasa_sdk/executor.py", line 226, in _import_module
    module = importlib.import_module(name)
  File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
  File "<frozen importlib._bootstrap>", line 983, in _find_and_load
  File "<frozen importlib._bootstrap>", line 967, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 677, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 728, in exec_module
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "/app/actions.py", line 151, in <module>
    encode_standard_question(sentence_transformer_select,pretrained_model)
  File "/app/actions.py", line 135, in encode_standard_question
    bc = SentenceTransformer(pretrained_model)
  File "/opt/venv/lib/python3.7/site-packages/sentence_transformers/SentenceTransformer.py", line 48, in __init__
    os.makedirs(model_path, exist_ok=True)
  File "/usr/local/lib/python3.7/os.py", line 213, in makedirs
    makedirs(head, exist_ok=exist_ok)
  File "/usr/local/lib/python3.7/os.py", line 213, in makedirs
    makedirs(head, exist_ok=exist_ok)
  File "/usr/local/lib/python3.7/os.py", line 213, in makedirs
    makedirs(head, exist_ok=exist_ok)
  File "/usr/local/lib/python3.7/os.py", line 223, in makedirs
    mkdir(name, mode)
PermissionError: [Errno 13] Permission denied: '/.cache'

我在尝试为 rasa 聊天机器人构建 docker 镜像时遇到以下错误。 我能够构建 docker 镜像，但是当我尝试运行该镜像时，出现以下错误。我在 NLP 中使用句子转换器，并使用 bert-base-nli-mean-tokens 作为 nli 模型。不知道怎么回事。

最佳答案

问题是有一个可写的目录路径来下载预训练模型。

SentenceTransformers Lib 使用两种方式读取此缓存目录路径(下载预训练模型的目录):-

1. 在文件中 SentenceTransformer.py#L55 , 它检查环境变量 SENTENCE_TRANSFORMERS_HOME设置正确。所以你可以设置这个环境。 var 到您具有写入权限的目录。

2. 如果环境。变种。 SENTENCE_TRANSFORMERS_HOME没有设置，它使用pytorch来获取它的缓存目录。 Pytorch 默认给出 <HOME>./cache (参见 here )作为缓存目录，但您可以通过设置环境变量 TORCH_HOME 来覆盖此选择.

现在，在您的情况下，它正在写入 /.cache目录，可能是因为 docker 的用户 set/notset。当你ssh到docker容器时，如果没有/home/username目录，pytorch 给出 /.cache默认目录(See here)。您可以使用以上 2 种方式覆盖此路径。

例如，您可以将 env 值传递为:SENTENCE_TRANSFORMERS_HOME=./.config python train.py

关于docker - 权限错误 : [Errno 13] Permission denied: '/.cache' - Error occurred while building a docker image，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/63526148/