code: def mobilenet_v3_large(
      pretrained: bool = False, **kwargs: Any
  ) -> mobilenetv3.MobileNetV3:
      """MobileNetV3-Large architecture as described in
      `"Searching for MobileNetV3",
      <https://arxiv.org/pdf/1905.02244.pdf>`_.
  
      >>> import torch
      >>> from doctr.models import mobilenet_v3_large
      >>> model = mobilenet_v3_large(pretrained=False)
      >>> input_tensor = torch.rand((1, 3, 512, 512), dtype=torch.float32)
      >>> out = model(input_tensor)
  
      Args:
      ----
          pretrained: boolean, True if model is pretrained
          **kwargs: keyword arguments of the MobileNetV3 architecture
  
      Returns:
      -------
          a torch.nn.Module
      """
      return _mobilenet_v3(
          "mobilenet_v3_large",
          pretrained,
          ignore_keys=["classifier.3.weight", "classifier.3.bias"],
          **kwargs,
      )
  
file_path: doctr/doctr/models/classification/mobilenet/pytorch.py
imports: from copy import deepcopy
  from typing import Any, Dict, List, Optional
  from torchvision.models import mobilenetv3
  from doctr.datasets import VOCABS
  from ...utils import load_pretrained_params
label_desc: Use image node_id 4 for calling a global function with example usage: mobilenet_v3_large(pretrained) and returns: _mobilenet_v3