python - AutoTokenizer.from_pretrained 无法加载本地保存的预训练标记器 (PyTorch)

Question

我是 PyTorch 的新手，最近，我一直在尝试使用 Transformers。我正在使用 HuggingFace 提供的预训练标记器。
我成功下载并运行它们。但是如果我尝试保存它们并再次加载，则会发生一些错误。如果我使用 AutoTokenizer.from_pretrained下载一个标记器，然后它就可以工作了。

[1]:    tokenizer = AutoTokenizer.from_pretrained('distilroberta-base')
        text = "Hello there"
        enc = tokenizer.encode_plus(text)
        enc.keys()

Out[1]: dict_keys(['input_ids', 'attention_mask'])

但是如果我使用 tokenizer.save_pretrained("distilroberta-tokenizer") 保存它并尝试在本地加载它，然后它失败了。

[2]:    tmp = AutoTokenizer.from_pretrained('distilroberta-tokenizer')


---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
/opt/conda/lib/python3.7/site-packages/transformers/configuration_utils.py in get_config_dict(cls, pretrained_model_name_or_path, **kwargs)
    238                 resume_download=resume_download,
--> 239                 local_files_only=local_files_only,
    240             )

/opt/conda/lib/python3.7/site-packages/transformers/file_utils.py in cached_path(url_or_filename, cache_dir, force_download, proxies, resume_download, user_agent, extract_compressed_file, force_extract, local_files_only)
    266         # File, but it doesn't exist.
--> 267         raise EnvironmentError("file {} not found".format(url_or_filename))
    268     else:

OSError: file distilroberta-tokenizer/config.json not found

During handling of the above exception, another exception occurred:

OSError                                   Traceback (most recent call last)
<ipython-input-25-3bd2f7a79271> in <module>
----> 1 tmp = AutoTokenizer.from_pretrained("distilroberta-tokenizer")

/opt/conda/lib/python3.7/site-packages/transformers/tokenization_auto.py in from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs)
    193         config = kwargs.pop("config", None)
    194         if not isinstance(config, PretrainedConfig):
--> 195             config = AutoConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
    196 
    197         if "bert-base-japanese" in pretrained_model_name_or_path:

/opt/conda/lib/python3.7/site-packages/transformers/configuration_auto.py in from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
    194 
    195         """
--> 196         config_dict, _ = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
    197 
    198         if "model_type" in config_dict:

/opt/conda/lib/python3.7/site-packages/transformers/configuration_utils.py in get_config_dict(cls, pretrained_model_name_or_path, **kwargs)
    250                 f"- or '{pretrained_model_name_or_path}' is the correct path to a directory containing a {CONFIG_NAME} file\n\n"
    251             )
--> 252             raise EnvironmentError(msg)
    253 
    254         except json.JSONDecodeError:

OSError: Can't load config for 'distilroberta-tokenizer'. Make sure that:

- 'distilroberta-tokenizer' is a correct model identifier listed on 'https://huggingface.co/models'

- or 'distilroberta-tokenizer' is the correct path to a directory containing a config.json file

它说“config.josn”从目录中丢失。在检查目录时，我得到了这些文件的列表:

[3]:    !ls distilroberta-tokenizer

Out[3]: merges.txt  special_tokens_map.json  tokenizer_config.json  vocab.json

我知道这个问题之前已经发布过，但它们似乎都不起作用。我也试过关注 docs但仍然无法使其工作。
任何帮助，将不胜感激。

Answer 1

当前有一个 issue正在调查中，它只影响 AutoTokenizer，而不影响像 (RobertaTokenizer) 这样的底层标记器。例如，以下应该工作:

from transformers import RobertaTokenizer

tokenizer = RobertaTokenizer.from_pretrained('YOURPATH')

要使用 AutoTokenizer，您还需要保存配置以离线加载:

from transformers import AutoTokenizer, AutoConfig

tokenizer = AutoTokenizer.from_pretrained('distilroberta-base')
config = AutoConfig.from_pretrained('distilroberta-base')

tokenizer.save_pretrained('YOURPATH')
config.save_pretrained('YOURPATH')

tokenizer = AutoTokenizer.from_pretrained('YOURPATH')

我推荐给 要么 对标记器和模型使用不同的路径 或 保留模型的 config.json，因为您对模型应用的一些修改将存储在 model.save_pretrained() 期间创建的 config.json 中。并且当您在模型之后保存如上所述的分词器时将被覆盖(即您将无法使用分词器 config.json 加载修改后的模型)。