class_docstr: Separable convolution.
class_docstr_tok: ["Separable","convolution","."]
code: def __init__(self, in_ch, out_ch, stride=1, kernel=3, fm_size=7):
      super(SeparableConv, self).__init__()
      assert stride in [1, 2], "stride should be in [1, 2]"
      pad = kernel // 2
  
      self.conv = nn.Sequential(
          conv_bn(in_ch, in_ch, kernel, stride, pad=pad, groups=in_ch),
          conv_bn(in_ch, out_ch, 1, 1, pad=0),
      )
  
imports: from __future__ import absolute_import, division, print_function
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new SeparableConv object from inherited base classes: nn with example: obj = SeparableConv(in_ch, out_ch, stride, kernel, fm_size)