    def build_model(cls, args, task):
        """Build a new model instance."""
        # make sure that all args are properly defaulted (in case there are any new ones)
        base_architecture(args)

        encoder_embed_dict = None
        if args.encoder_embed_path:
            encoder_embed_dict = utils.parse_embedding(args.encoder_embed_path)
            utils.print_embed_overlap(encoder_embed_dict, task.source_dictionary)

        decoder_embed_dict = None
        if args.decoder_embed_path:
            decoder_embed_dict = utils.parse_embedding(args.decoder_embed_path)
            utils.print_embed_overlap(decoder_embed_dict, task.target_dictionary)

        encoder = FConvEncoder(
            dictionary=task.source_dictionary,
            embed_dim=args.encoder_embed_dim,
            embed_dict=encoder_embed_dict,
            convolutions=eval(args.encoder_layers),
            dropout=args.dropout,
            max_positions=args.max_source_positions,
        )
        decoder = FConvDecoder(
            dictionary=task.target_dictionary,
            embed_dim=args.decoder_embed_dim,
            embed_dict=decoder_embed_dict,
            convolutions=eval(args.decoder_layers),
            out_embed_dim=args.decoder_out_embed_dim,
            attention=eval(args.decoder_attention),
            dropout=args.dropout,
            max_positions=args.max_target_positions,
            share_embed=args.share_input_output_embed,
        )
        return FConvModel(encoder, decoder)
Build a new model instance.
fairseq/models/fconv.py