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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 _get_encoder_module(self) -> Tuple[mx.mod.BucketingModule, int]: """ Returns a BucketingModule for the encoder. Given a source sequence, it returns the initial decoder states of the model. The bucket key for this module is the length of the source sequence. :return: Tuple of encoder module and default bucket key. """


        def sym_gen(source_seq_len: int):
            source = mx.sym.Variable(C.SOURCE_NAME)
            source_words = source.split(num_outputs=self.num_source_factors, axis=2, squeeze_axis=True)[0]
            source_length = utils.compute_lengths(source_words)

            # source embedding
            (source_embed,
             source_embed_length,
             source_embed_seq_len) = self.embedding_source.encode(source, source_length, source_seq_len)

            # encoder
            # source_encoded: (source_encoded_length, batch_size, encoder_depth)
            (source_encoded,
             source_encoded_length,
             source_encoded_seq_len) = self.encoder.encode(source_embed,
                                                           source_embed_length,
                                                           source_embed_seq_len)

            # initial decoder states
            decoder_init_states = self.decoder.init_states(source_encoded,
                                                           source_encoded_length,
                                                           source_encoded_seq_len)

            data_names = [C.SOURCE_NAME]
            label_names = []  # type: List[str]

            # predict length ratios
            predicted_length_ratios = []  # type: List[mx.nd.NDArray]
            if self.length_ratio is not None:
                # predicted_length_ratios: List[(n, 1)]
                predicted_length_ratios = [self.length_ratio(source_encoded, source_encoded_length)]

            return mx.sym.Group(decoder_init_states + predicted_length_ratios), data_names, label_names

        default_bucket_key = self.max_input_length
        module = mx.mod.BucketingModule(sym_gen=sym_gen,
                                        default_bucket_key=default_bucket_key,
                                        context=self.context)
        return module, default_bucket_key