code: def load_model(pretrained: bool = True) -> nn.Module:
      """Load the lraspp_mobilenet_v3_large model and return it."""
      model = lraspp_mobilenet_v3_large(
          pretrained=pretrained, progress=False
      )
      _ = model.eval()
      return model
  
imports: import contextlib
  import os
  import pathlib
  import typing
  from pathlib import Path
  import albumentations
  import numpy
  import torch
  import torchvision.transforms.functional
  from albumentations.pytorch.transforms import ToTensorV2
  from PIL import Image, ImageDraw
  from torch import nn
  from torch.utils.data import DataLoader
  from typing_extensions import Literal
  from deepchecks.vision.utils.test_utils import get_data_loader_sequential
  from deepchecks.vision.vision_data import BatchOutputFormat, VisionData
  from deepchecks.vision.vision_data.utils import object_to_numpy
label_desc: Use image node_id 1 for calling a global function with example usage: load_model(pretrained) and returns: model