code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size=1,
      stride=1,
      padding=0,
      dilation=1,
  ):
      super(SeparableConv2d, self).__init__()
  
      self.conv1 = nn.Conv2d(
          in_channels,
          in_channels,
          kernel_size,
          stride,
          padding,
          dilation,
          groups=in_channels,
          bias=False,
      )
      self.pointwise = nn.Conv2d(
          in_channels, out_channels, 1, 1, 0, 1, 1, bias=False
      )
  
imports: import torch.jit
  import torch.nn
  import torch.nn.functional
  from timm.layers import create_classifier
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs, register_model_deprecations
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)