align/models.py [27:44]:
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        self.device = device
        args = torch.load(args_path)
        task = tasks.setup_task(args)
        models, _model_args = checkpoint_utils.load_model_ensemble(
            path.split(':'),
            arg_overrides=eval('{}'),
            task=task
        )
        for model in models:
            model.make_generation_fast_(
                beamable_mm_beam_size=None if args.no_beamable_mm else args.beam,
                need_attn=args.print_alignment,
            )
            if args.fp16:
                model.half()
            model = model.to(self.device)
        self.model = EnsembleModel(models).to(self.device)
        self.tokenizer = AutoTokenizer.from_pretrained(tokenizer)
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src/models.py [15:32]:
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        self.device = device
        args = torch.load(args_path)
        task = tasks.setup_task(args)
        models, _model_args = checkpoint_utils.load_model_ensemble(
            path.split(':'),
            arg_overrides=eval('{}'),
            task=task
        )
        for model in models:
            model.make_generation_fast_(
                beamable_mm_beam_size=None if args.no_beamable_mm else args.beam,
                need_attn=args.print_alignment,
            )
            if args.fp16:
                model.half()
            model = model.to(self.device)
        self.model = EnsembleModel(models).to(self.device)
        self.tokenizer = AutoTokenizer.from_pretrained(tokenizer)
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