code: def mnasnet1_3(
      *,
      weights: Optional[MNASNet1_3_Weights] = None,
      progress: bool = True,
      **kwargs: Any,
  ) -> MNASNet:
      """MNASNet with depth multiplier of 1.3 from
      `MnasNet: Platform-Aware Neural Architecture Search for Mobile
      <https://arxiv.org/abs/1807.11626>`_ paper.
  
      Args:
          weights (:class:`~torchvision.models.MNASNet1_3_Weights`, optional): The
              pretrained weights to use. See
              :class:`~torchvision.models.MNASNet1_3_Weights` below for
              more details, and possible values. By default, no pre-trained
              weights are used.
          progress (bool, optional): If True, displays a progress bar of the
              download to stderr. Default is True.
          **kwargs: parameters passed to the ``torchvision.models.mnasnet.MNASNet``
              base class. Please refer to the `source code
              <https://github.com/pytorch/vision/blob/main/torchvision/models/mnasnet.py>`_
              for more details about this class.
  
      .. autoclass:: torchvision.models.MNASNet1_3_Weights
          :members:
      """
      weights = MNASNet1_3_Weights.verify(weights)
  
      return _mnasnet(1.3, weights, progress, **kwargs)
  
imports: import warnings
  from functools import partial
  from typing import Any, Dict, List, Optional
  import torch
  import torch.nn
  from torch import Tensor
  from ..transforms._presets import ImageClassification
  from ..utils import _log_api_usage_once
  from ._api import register_model, Weights, WeightsEnum
  from ._meta import _IMAGENET_CATEGORIES
  from ._utils import _ovewrite_named_param, handle_legacy_interface
label_desc: Use image node_id 8 for calling a global function with example usage: mnasnet1_3() and returns: _mnasnet