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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 encode(self, data: mx.sym.Symbol, data_length: mx.sym.Symbol, seq_len: int) -> Tuple[mx.sym.Symbol, mx.sym.Symbol, int]: """ Encodes data with a stack of Convolution+GLU blocks given sequence lengths of individual examples and maximum sequence length. :param data: Input data. Shape: (batch_size, seq_len, input_num_hidden). :param data_length: Vector with sequence lengths. :param seq_len: Maximum sequence length. :return: Encoded version of the data. """

        # data: (batch_size, seq_len, num_hidden)
        data = mx.sym.FullyConnected(data=data,
                                     num_hidden=self.config.cnn_config.num_hidden,
                                     no_bias=True,
                                     flatten=False,
                                     weight=self.i2h_weight)

        # Multiple layers with residual connections:
        for layer in self.layers:
            data = data + layer(data, data_length, seq_len)
        return data, data_length, seq_len