code: def i3d_nl10_resnet101_v1_kinetics400(
      nclass=400,
      pretrained=False,
      pretrained_base=True,
      ctx=cpu(),
      root="~/.mxnet/models",
      use_tsn=False,
      num_segments=1,
      num_crop=1,
      partial_bn=False,
      feat_ext=False,
      **kwargs,
  ):
      r"""Inflated 3D model (I3D) with ResNet101 backbone and 10 non-local blocks
      trained on Kinetics400 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.
      bn_frozen : bool.
          Whether to freeze weight and bias of BN layers.
      feat_ext : bool.
          Whether to extract features before dense classification layer or
          do a complete forward pass.
      """
  
      model = I3D_ResNetV1(
          nclass=nclass,
          depth=101,
          pretrained=pretrained,
          pretrained_base=pretrained_base,
          feat_ext=feat_ext,
          num_segments=num_segments,
          num_crop=num_crop,
          out_indices=[3],
          inflate_freq=(
              (1, 1, 1),
              (1, 0, 1, 0),
              (
                  1,
                  0,
                  1,
                  0,
                  1,
                  0,
                  1,
                  0,
                  1,
                  0,
                  1,
                  0,
                  1,
                  0,
                  1,
                  0,
                  1,
                  0,
                  1,
                  0,
                  1,
                  0,
                  1,
              ),
              (0, 1, 0),
          ),
          nonlocal_stages=(1, 2),
          nonlocal_cfg=dict(nonlocal_type="gaussian"),
          nonlocal_freq=(
              (0, 0, 0),
              (1, 1, 1, 1),
              (
                  0,
                  0,
                  1,
                  0,
                  0,
                  0,
                  1,
                  0,
                  0,
                  0,
                  1,
                  0,
                  0,
                  0,
                  1,
                  0,
                  0,
                  0,
                  1,
                  0,
                  0,
                  0,
                  1,
              ),
              (0, 0, 0),
          ),
          bn_eval=False,
          partial_bn=partial_bn,
          ctx=ctx,
          **kwargs,
      )
  
      if pretrained:
          from ..model_store import get_model_file
  
          model.load_parameters(
              get_model_file(
                  "i3d_nl10_resnet101_v1_kinetics400",
                  tag=pretrained,
                  root=root,
              ),
              ctx=ctx,
          )
          from ...data import Kinetics400Attr
  
          attrib = Kinetics400Attr()
          model.classes = attrib.classes
      model.collect_params().reset_ctx(ctx)
  
      return model
  
imports: from mxnet import nd
  from mxnet import init
  from mxnet.context import cpu
  from mxnet.gluon.block import HybridBlock
  from mxnet.gluon import nn
  from mxnet.gluon.nn import BatchNorm
  from ..resnetv1b import resnet50_v1b, resnet101_v1b
  from .non_local import build_nonlocal_block
label_desc: Use image node_id 9 for calling a global function with example usage: i3d_nl10_resnet101_v1_kinetics400(nclass, pretrained, pretrained_base, ctx, root, use_tsn, num_segments, num_crop, partial_bn, feat_ext) and returns: model