def forward(self, src_tokens, src_lengths):
        """
        Args:
            src_tokens (LongTensor): tokens in the source language of shape
                `(batch, src_len)`
            src_lengths (LongTensor): lengths of each source sentence of shape
                `(batch)`

        Returns:
            dict:
                the outputs from each Encoder
        """
        encoder_out = {}
        for key in self.encoders:
            encoder_out[key] = self.encoders[key](src_tokens, src_lengths)
        return encoder_out

        Args:
            src_tokens (LongTensor): tokens in the source language of shape
                `(batch, src_len)`
            src_lengths (LongTensor): lengths of each source sentence of shape
                `(batch)`

        Returns:
            dict:
                the outputs from each Encoder
        
structured_prompting/fairseq-version/fairseq/fairseq/models/composite_encoder.py