def from_file(file_path, elem_delim=' ', encoding='utf8', **kwargs):
        """Creates a user-defined token embedding from a pre-trained embedding file.


        This is to load embedding vectors from a user-defined pre-trained token embedding file.
        For example, if `elem_delim` = ' ', the expected format of a custom pre-trained token
        embedding file may look like:

        'hello 0.1 0.2 0.3 0.4 0.5\\\\nworld 1.1 1.2 1.3 1.4 1.5\\\\n'

        where embedding vectors of words `hello` and `world` are [0.1, 0.2, 0.3, 0.4, 0.5] and
        [1.1, 1.2, 1.3, 1.4, 1.5] respectively.


        Parameters
        ----------
        file_path : str
            The path to the user-defined pre-trained token embedding file.
        elem_delim : str, default ' '
            The delimiter for splitting a token and every embedding vector element value on the same
            line of the custom pre-trained token embedding file.
        encoding : str, default 'utf8'
            The encoding scheme for reading the custom pre-trained token embedding file.
        kwargs : dict
            All other keyword arguments are passed to the TokenEmbedding initializer.


        Returns
        -------
        instance of :class:`gluonnlp.embedding.TokenEmbedding`
            The user-defined token embedding instance.
        """
        embedding = TokenEmbedding(**kwargs)
        embedding._load_embedding(file_path, elem_delim=elem_delim, encoding=encoding)
        return embedding
Creates a user-defined token embedding from a pre-trained embedding file.


        This is to load embedding vectors from a user-defined pre-trained token embedding file.
        For example, if `elem_delim` = ' ', the expected format of a custom pre-trained token
        embedding file may look like:

        'hello 0.1 0.2 0.3 0.4 0.5\\\\nworld 1.1 1.2 1.3 1.4 1.5\\\\n'

        where embedding vectors of words `hello` and `world` are [0.1, 0.2, 0.3, 0.4, 0.5] and
        [1.1, 1.2, 1.3, 1.4, 1.5] respectively.


        Parameters
        ----------
        file_path : str
            The path to the user-defined pre-trained token embedding file.
        elem_delim : str, default ' '
            The delimiter for splitting a token and every embedding vector element value on the same
            line of the custom pre-trained token embedding file.
        encoding : str, default 'utf8'
            The encoding scheme for reading the custom pre-trained token embedding file.
        kwargs : dict
            All other keyword arguments are passed to the TokenEmbedding initializer.


        Returns
        -------
        instance of :class:`gluonnlp.embedding.TokenEmbedding`
            The user-defined token embedding instance.