code: def inceptionv1_sthsthv2(
      nclass=174,
      pretrained=False,
      pretrained_base=True,
      tsn=False,
      num_segments=1,
      num_crop=1,
      partial_bn=True,
      ctx=mx.cpu(),
      root="~/.mxnet/models",
      **kwargs,
  ):
      r"""InceptionV1 model trained on Something-Something-V2 dataset.
  
      Parameters
      ----------
      nclass : int.
          Number of categories in the dataset.
      pretrained : bool or str.
          Boolean value controls whether to load the default pretrained weights for model.
          String value represents the hashtag for a certain version of pretrained weights.
      pretrained_base : bool or str, optional, default is True.
          Load pretrained base network, the extra layers are randomized. Note that
          if pretrained is `True`, this has no effect.
      ctx : Context, default CPU.
          The context in which to load the pretrained weights.
      root : str, default $MXNET_HOME/models
          Location for keeping the model parameters.
      num_segments : int, default is 1.
          Number of segments used to evenly divide a video.
      num_crop : int, default is 1.
          Number of crops used during evaluation, choices are 1, 3 or 10.
      partial_bn : bool, default False.
          Freeze all batch normalization layers during training except the first layer.
      """
      model = ActionRecInceptionV1(
          nclass=nclass,
          partial_bn=partial_bn,
          pretrained_base=pretrained_base,
          num_segments=num_segments,
          num_crop=num_crop,
          dropout_ratio=0.5,
          init_std=0.01,
      )
  
      if pretrained:
          from ..model_store import get_model_file
  
          model.load_parameters(
              get_model_file(
                  "inceptionv1_sthsthv2", tag=pretrained, root=root
              )
          )
          from ...data import SomethingSomethingV2Attr
  
          attrib = SomethingSomethingV2Attr()
          model.classes = attrib.classes
      model.collect_params().reset_ctx(ctx)
      return model
  
file_path: gluon-cv/gluoncv/model_zoo/action_recognition/actionrec_inceptionv1.py
imports: import mxnet
  from mxnet import init
  from mxnet.gluon import nn
  from mxnet.gluon.nn import HybridBlock
  from gluoncv.model_zoo.googlenet import googlenet
label_desc: Use image node_id 4 for calling a global function with example usage: inceptionv1_sthsthv2(nclass, pretrained, pretrained_base, tsn, num_segments, num_crop, partial_bn, ctx, root) and returns: model