Method to

surya/common/predictor.py:38–46

(self, device_dtype: torch.device | str | None = None)

        self._disable_tqdm = settings.DISABLE_TQDM

    def to(self, device_dtype: torch.device | str | None = None):
        if hasattr(self, "model") and self.model:
            self.model.to(device_dtype)
            return
        # Predictors that don't own a torch model (e.g. VLM-backed predictors that
        # rely on an external server) treat .to() as a no-op.
        if hasattr(self, "manager") and self.manager is not None:
            return
        raise ValueError("Model not loaded")

    def get_batch_size(self):
        batch_size = self.batch_size