class_docstr: (2+1)D convolutions for R2plus1D (1x3x3 kernel + 3x1x1 kernel)
code: def __init__(
      self, in_planes, out_planes, midplanes, stride=1, padding=1
  ):
      super(Conv2Plus1D, self).__init__(
          nn.Conv3d(
              in_planes,
              midplanes,
              kernel_size=(1, 3, 3),
              stride=(1, stride, stride),
              padding=(0, padding, padding),
              bias=False,
          ),
          nn.BatchNorm3d(midplanes),
          nn.ReLU(inplace=True),
          nn.Conv3d(
              midplanes,
              out_planes,
              kernel_size=(3, 1, 1),
              stride=(stride, 1, 1),
              padding=(padding, 0, 0),
              bias=False,
          ),
      )
  
imports: import torch.nn
  from torch.hub import load_state_dict_from_url
label_desc: Use image node_id 1 to create a new Conv2Plus1D object from inherited base classes: nn with example: obj = Conv2Plus1D(in_planes, out_planes, midplanes, stride, padding)