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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def serialize(self, file_path, compress=True):
 """Serializes the TokenEmbedding to a file specified by file_path. TokenEmbedding is serialized by converting the list of tokens, the array of word embeddings and other metadata to numpy arrays, saving all in a single (optionally compressed) Zipfile. See https://docs.scipy.org/doc/numpy-1.14.2/neps/npy-format.html for more information on the format. Parameters file_path : str or file The path at which to create the file holding the serialized TokenEmbedding. If file is a string or a Path, the .npz extension will be appended to the file name if it is not already there. compress : bool, default True Compress the Zipfile or leave it uncompressed. """

        if self.unknown_lookup is not None:
            warnings.warn(
                'Serialization of `unknown_lookup` is not supported. '
                'Save it manually and pass the loaded lookup object '
                'during deserialization.')

        unknown_token = np.array(self.unknown_token)
        idx_to_token = np.array(self.idx_to_token, dtype='O')
        idx_to_vec = self.idx_to_vec.asnumpy()

        if not unknown_token:  # Store empty string instead of None
            unknown_token = ''
        else:
            assert unknown_token == idx_to_token[C.UNK_IDX]

        if not compress:
            np.savez(file=file_path, unknown_token=unknown_token,
                     idx_to_token=idx_to_token, idx_to_vec=idx_to_vec)
        else:
            np.savez_compressed(file=file_path, unknown_token=unknown_token,
                                idx_to_token=idx_to_token,
                                idx_to_vec=idx_to_vec)