code: def convnext_base(
      *,
      weights: Optional[ConvNeXt_Base_Weights] = None,
      progress: bool = True,
      **kwargs: Any,
  ) -> ConvNeXt:
      """ConvNeXt Base model architecture from the
      `A ConvNet for the 2020s <https://arxiv.org/abs/2201.03545>`_ paper.
  
      Args:
          weights (:class:`~torchvision.models.convnext.ConvNeXt_Base_Weights`, optional): The pretrained
              weights to use. See :class:`~torchvision.models.convnext.ConvNeXt_Base_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.convnext.ConvNext``
              base class. Please refer to the `source code
              <https://github.com/pytorch/vision/blob/main/torchvision/models/convnext.py>`_
              for more details about this class.
  
      .. autoclass:: torchvision.models.ConvNeXt_Base_Weights
          :members:
      """
      weights = ConvNeXt_Base_Weights.verify(weights)
  
      block_setting = [
          CNBlockConfig(128, 256, 3),
          CNBlockConfig(256, 512, 3),
          CNBlockConfig(512, 1024, 27),
          CNBlockConfig(1024, None, 3),
      ]
      stochastic_depth_prob = kwargs.pop("stochastic_depth_prob", 0.5)
      return _convnext(
          block_setting,
          stochastic_depth_prob,
          weights,
          progress,
          **kwargs,
      )
  
imports: from functools import partial
  from typing import Any, Callable, List, Optional, Sequence
  import torch
  from torch import nn, Tensor
  from torch.nn import functional
  from ..ops.misc import Conv2dNormActivation, Permute
  from ..ops.stochastic_depth import StochasticDepth
  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 4 for calling a global function with example usage: convnext_base() and returns: _convnext