class_docstr: A kxk depthwise convolution + a 1x1 convolution.
  
  In :paper:`xception`, norm & activation are applied on the second conv.
  :paper:`mobilenet` uses norm & activation on both convs.
code: def forward(self, x):
      return self.pointwise(self.depthwise(x))
  
file_path: detectron2/detectron2/layers/blocks.py
imports: import fvcore.nn.weight_init
  from torch import nn
  from .batch_norm import FrozenBatchNorm2d, get_norm
  from .wrappers import Conv2d
label_desc: Use image node_id 2 for calling the DepthwiseSeparableConv2d obj's underlying member method code with example usage: obj.forward(x) and returns: self