class_docstr: Channel attention module
  from the paper `"Dual Attention Network for Scene Segmentation"
  <https://arxiv.org/abs/1809.02983>`
  CAM_Module explicitly models interdependencies between channels.
class_docstr_tok: ["Channel","attention","module","from","the","paper","`","``","Dual","Attention","Network","for","Scene","Segmentation","''","<","https",":","\/\/arxiv.org\/abs\/1809.02983",">","`","CAM_Module","explicitly","models","interdependencies","between","channels","."]
code: def __init__(self, in_dim):
      super(CAM_Module, self).__init__()
      self.chanel_in = in_dim
  
      self.gamma = self.params.get(
          "gamma", shape=(1,), init=mx.init.Zero()
      )
  
file_path: gluon-cv/gluoncv/model_zoo/attention.py
imports: import mxnet
  from mxnet.gluon import nn
  from mxnet.gluon.nn import HybridBlock
label_desc: Use image node_id 1 to create a new CAM_Module object from inherited base classes: HybridBlock with example: obj = CAM_Module(in_dim)