class_docstr: Separable Convolution.
class_docstr_tok: ["Separable","Convolution","."]
code: def __init__(self, in_planes, out_planes, kernel_size, stride):
      super(SepConv, self).__init__()
      self.conv1 = nn.Conv2d(
          in_planes,
          out_planes,
          kernel_size,
          stride,
          padding=(kernel_size - 1) // 2,
          bias=False,
          groups=in_planes,
      )
      self.bn1 = nn.BatchNorm2d(out_planes)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new SepConv object from inherited base classes: nn with example: obj = SepConv(in_planes, out_planes, kernel_size, stride)