code: def transmute_Conv3d3x3x3DwBnAct(input_module: nn.Module):
      """
      Given an input_module, transmutes it into a equivalent Conv3d3x3x3DwBnAct. Returns
      None if no equivalent Conv3d3x3x3DwBnAct is found, else returns an instance of
      equivalent Conv3d3x3x3DwBnAct.
      Args:
          input_module (nn.Module): input module to find an equivalent Conv3d3x3x3DwBnAct
      """
      if not isinstance(input_module, nn.Conv3d):
          return None
      if (
          input_module.kernel_size == (3, 3, 3)
          and input_module.in_channels == input_module.out_channels
          and input_module.groups == input_module.out_channels
          and input_module.stride[0] == 1
          and input_module.stride[1] == input_module.stride[2]
          and input_module.padding == (1, 1, 1)
          and input_module.padding_mode == "zeros"
          and input_module.dilation == (1, 1, 1)
      ):
          spatial_stride = input_module.stride[1]
          module = Conv3d3x3x3DwBnAct(
              in_channels=input_module.in_channels,
              spatial_stride=spatial_stride,
              bias=False if input_module.bias is None else True,
              activation="identity",
              use_bn=False,
          )
          module.kernel.conv.load_state_dict(input_module.state_dict())
          return module
      else:
          return None
  
imports: import torch.nn
  from pytorchvideo.layers.accelerator.mobile_cpu.convolutions import Conv3d3x1x1BnAct, Conv3d3x3x3DwBnAct, Conv3d5x1x1BnAct, Conv3dPwBnAct, Conv3dTemporalKernel1BnAct
label_desc: Use image node_id 2 for calling a global function with example usage: transmute_Conv3d3x3x3DwBnAct(input_module) and returns: None, module, None