revice model acquisition logic

from vagen.env.svg.env_config import SvgEnvConfig

from vagen.server.serial import serialize_observation, serialize_step_result

from vagen.env.svg.score import calculate_total_score, calculate_total_score_batch

from vagen.env.svg.dino import get_dino_model

from vagen.env.svg.svg_utils import process_and_rasterize_svg, is_valid_svg

from vagen.env.utils.context_utils import parse_llm_raw_response, convert_numpy_to_PIL

from .service_config import SVGServiceConfig

        self.device = "cuda" if torch.cuda.is_available() else "cpu"

        print(f"SVGService initialized with {self.max_workers} workers, model_size={self.model_size}, device={self.device}")

    def _get_dino_model(self):

        """

        Get or initialize the DINO model.

        Uses lazy loading to avoid loading the model until needed.

        """

        if self.dino_model is None:

            self.dino_model = get_dino_model(self.model_size, self.device)

        return self.dino_model

    def _get_dreamsim_model(self):

        """

        Get or initialize the DreamSim model.

        Uses lazy loading to avoid loading the model until needed.

        """

        if self.dreamsim_model is None:

            from vagen.env.svg.dreamsim import get_dreamsim_model

            self.dreamsim_model = get_dreamsim_model(self.device)

        return self.dreamsim_model

    def create_environments_batch(self, ids2configs: Dict[Any, Any]) -> None:

        """

        Create multiple SVG environments in parallel.

        # Step 3: Batch process scores if there are valid images

        if valid_env_ids:

            # Get DINO model

            dino_model = self._get_dino_model()

            dreamsim_model = self._get_dreamsim_model()

            # Calculate all scores at once

            batch_results = calculate_total_score_batch(

                gt_images, gen_images, gt_codes, gen_codes, score_configs, dino_model, dreamsim_model

                gt_images, gen_images, gt_codes, gen_codes, score_configs

            )

            # Process results directly using the index mapping