class_docstr: Context Module for Mobile Model.
  
  Args:
      in_channels (int): The number of input channels to pyramid pooling module.
      inter_channels (int): The number of inter channels to pyramid pooling module.
      out_channels (int): The number of output channels after pyramid pooling module.
      bin_sizes (tuple, optional): The out size of pooled feature maps. Default: (1, 3).
      align_corners (bool): An argument of F.interpolate. It should be set to False
          when the output size of feature is even, e.g. 1024x512, otherwise it is True, e.g. 769x769.
class_docstr_tok: ["Context","Module","for","Mobile","Model",".","Args",":","in_channels","(","int",")",":","The","number","of","input","channels","to","pyramid","pooling","module",".","inter_channels","(","int",")",":","The","number","of","inter","channels","to","pyramid","pooling","module",".","out_channels","(","int",")",":","The","number","of","output","channels","after","pyramid","pooling","module",".","bin_sizes","(","tuple",",","optional",")",":","The","out","size","of","pooled","feature","maps",".","Default",":","(","1",",","3",")",".","align_corners","(","bool",")",":","An","argument","of","F.interpolate",".","It","should","be","set","to","False","when","the","output","size","of","feature","is","even",",","e.g",".","1024x512",",","otherwise","it","is","True",",","e.g",".","769x769","."]
code: def __init__(
      self,
      in_channels,
      inter_channels,
      out_channels,
      bin_sizes,
      align_corners=False,
  ):
      super().__init__()
  
      self.stages = nn.LayerList(
          [
              self._make_stage(in_channels, inter_channels, size)
              for size in bin_sizes
          ]
      )
  
      self.conv_out = layers.SeparableConvBNReLU(
          in_channels=inter_channels,
          out_channels=out_channels,
          kernel_size=3,
          bias_attr=False,
      )
  
      self.align_corners = align_corners
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg import utils
  from paddleseg.models import layers
  from paddleseg.cvlibs import manager
label_desc: Use image node_id 1 to create a new MobileContextModule object from inherited base classes: nn with example: obj = MobileContextModule(in_channels, inter_channels, out_channels, bin_sizes, align_corners)