class_docstr: Compact Spatial Attention Module
class_docstr_tok: ["Compact","Spatial","Attention","Module"]
code: def __init__(self, channels):
      super(CSAM, self).__init__()
  
      mid_channels = 4
      self.relu1 = nn.ReLU()
      self.conv1 = nn.Conv2d(
          channels, mid_channels, kernel_size=1, padding=0
      )
      self.conv2 = nn.Conv2d(
          mid_channels, 1, kernel_size=3, padding=1, bias=False
      )
      self.sigmoid = nn.Sigmoid()
      nn.init.constant_(self.conv1.bias, 0)
  
imports: import os
  import math
  import torch
  import numpy
  import torch.nn
  import torch.nn.functional
  from typing import Optional
  from cftool.cv import to_uint8
  from ....parameters import OPT
label_desc: Use image node_id 1 to create a new CSAM object from inherited base classes: nn with example: obj = CSAM(channels)