Method from_pretrained

bert/configuration_utils.py:145–201

r""" Instantiate a :class:`~transformers.PretrainedConfig` (or a derived class) from a pre-trained model configuration. Args: pretrained_model_name_or_path (:obj:`string`): either: - a string with the `shortcut name` of a pre-trained mo

(cls, pretrained_model_name_or_path, **kwargs)

    @classmethod
    def from_pretrained(cls, pretrained_model_name_or_path, **kwargs) -> "PretrainedConfig":
        r"""

        Instantiate a :class:`~transformers.PretrainedConfig` (or a derived class) from a pre-trained model configuration.

        Args:
            pretrained_model_name_or_path (:obj:`string`):
                either:
                  - a string with the `shortcut name` of a pre-trained model configuration to load from cache or
                    download, e.g.: ``bert-base-uncased``.
                  - a string with the `identifier name` of a pre-trained model configuration that was user-uploaded to
                    our S3, e.g.: ``dbmdz/bert-base-german-cased``.
                  - a path to a `directory` containing a configuration file saved using the
                    :func:`~transformers.PretrainedConfig.save_pretrained` method, e.g.: ``./my_model_directory/``.
                  - a path or url to a saved configuration JSON `file`, e.g.:
                    ``./my_model_directory/configuration.json``.
            cache_dir (:obj:`string`, `optional`):
                Path to a directory in which a downloaded pre-trained model
                configuration should be cached if the standard cache should not be used.
            kwargs (:obj:`Dict[str, any]`, `optional`):
                The values in kwargs of any keys which are configuration attributes will be used to override the loaded
                values. Behavior concerning key/value pairs whose keys are *not* configuration attributes is
                controlled by the `return_unused_kwargs` keyword parameter.
            force_download (:obj:`bool`, `optional`, defaults to :obj:`False`):
                Force to (re-)download the model weights and configuration files and override the cached versions if they exist.
            resume_download (:obj:`bool`, `optional`, defaults to :obj:`False`):
                Do not delete incompletely recieved file. Attempt to resume the download if such a file exists.
            proxies (:obj:`Dict`, `optional`):
                A dictionary of proxy servers to use by protocol or endpoint, e.g.:
                :obj:`{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}.`
                The proxies are used on each request.
            return_unused_kwargs: (`optional`) bool:
                If False, then this function returns just the final configuration object.
                If True, then this functions returns a :obj:`Tuple(config, unused_kwargs)` where `unused_kwargs` is a
                dictionary consisting of the key/value pairs whose keys are not configuration attributes: ie the part
                of kwargs which has not been used to update `config` and is otherwise ignored.

        Returns:
            :class:`PretrainedConfig`: An instance of a configuration object

        Examples::

            # We can't instantiate directly the base class `PretrainedConfig` so let's show the examples on a
            # derived class: BertConfig
            config = BertConfig.from_pretrained('bert-base-uncased')    # Download configuration from S3 and cache.
            config = BertConfig.from_pretrained('./test/saved_model/')  # E.g. config (or model) was saved using `save_pretrained('./test/saved_model/')`
            config = BertConfig.from_pretrained('./test/saved_model/my_configuration.json')
            config = BertConfig.from_pretrained('bert-base-uncased', output_attention=True, foo=False)
            assert config.output_attention == True
            config, unused_kwargs = BertConfig.from_pretrained('bert-base-uncased', output_attention=True,
                                                               foo=False, return_unused_kwargs=True)
            assert config.output_attention == True
            assert unused_kwargs == {'foo': False}

        """
        config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs)
        return cls.from_dict(config_dict, **kwargs)