code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size=1,
      stride=1,
      padding=0,
      dilation=1,
      bias=False,
  ):
      super(SeparableConv2d, self).__init__()
  
      self.conv1 = nn.Conv2d(
          in_channels,
          in_channels,
          kernel_size,
          stride,
          padding,
          dilation,
          groups=in_channels,
          bias=bias,
      )
      self.pointwise = nn.Conv2d(
          in_channels, out_channels, 1, 1, 0, 1, 1, bias=bias
      )
  
imports: from __future__ import print_function, division, absolute_import
  import math
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.model_zoo
  from torch.nn import init
label_desc: Use image node_id 1 to create a new SeparableConv2d object from inherited base classes: nn with example: obj = SeparableConv2d(in_channels, out_channels, kernel_size, stride, padding, dilation, bias)