code: def __init__(
      self,
      in_planes: int,
      out_planes: int,
      midplanes: int,
      stride: int = 1,
      padding: int = 1,
  ) -> None:
      super().__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: from functools import partial
  from typing import Any, Callable, List, Optional, Sequence, Tuple, Type, Union
  import torch.nn
  from torch import Tensor
  from ...transforms._presets import VideoClassification
  from ...utils import _log_api_usage_once
  from .._api import register_model, Weights, WeightsEnum
  from .._meta import _KINETICS400_CATEGORIES
  from .._utils import _ovewrite_named_param, handle_legacy_interface
  from .._utils import _ModelURLs
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)