class_docstr: The GCNet implementation based on PaddlePaddle.
  
  The original article refers to
  Cao, Yue, et al. "GCnet: Non-local networks meet squeeze-excitation networks and beyond"
  (https://arxiv.org/pdf/1904.11492.pdf).
  
  Args:
      num_classes (int): The unique number of target classes.
      backbone (Paddle.nn.Layer): Backbone network, currently support Resnet50/101.
      backbone_indices (tuple, optional): Two values in the tuple indicate the indices of output of backbone.
      gc_channels (int, optional): The input channels to Global Context Block. Default: 512.
      ratio (float, optional): It indicates the ratio of attention channels and gc_channels. Default: 0.25.
      enable_auxiliary_loss (bool, optional): A bool value indicates whether adding auxiliary loss. Default: True.
      align_corners (bool, optional): An argument of F.interpolate. It should be set to False when the feature size is even,
          e.g. 1024x512, otherwise it is True, e.g. 769x769. Default: False.
      pretrained (str, optional): The path or url of pretrained model. Default: None.
class_docstr_tok: ["The","GCNet","implementation","based","on","PaddlePaddle",".","The","original","article","refers","to","Cao",",","Yue",",","et","al",".","``","GCnet",":","Non-local","networks","meet","squeeze-excitation","networks","and","beyond","''","(","https",":","\/\/arxiv.org\/pdf\/1904.11492.pdf",")",".","Args",":","num_classes","(","int",")",":","The","unique","number","of","target","classes",".","backbone","(","Paddle.nn.Layer",")",":","Backbone","network",",","currently","support","Resnet50\/101",".","backbone_indices","(","tuple",",","optional",")",":","Two","values","in","the","tuple","indicate","the","indices","of","output","of","backbone",".","gc_channels","(","int",",","optional",")",":","The","input","channels","to","Global","Context","Block",".","Default",":","512.","ratio","(","float",",","optional",")",":","It","indicates","the","ratio","of","attention","channels","and","gc_channels",".","Default",":","0.25.","enable_auxiliary_loss","(","bool",",","optional",")",":","A","bool","value","indicates","whether","adding","auxiliary","loss",".","Default",":","True",".","align_corners","(","bool",",","optional",")",":","An","argument","of","F.interpolate",".","It","should","be","set","to","False","when","the","feature","size","is","even",",","e.g",".","1024x512",",","otherwise","it","is","True",",","e.g",".","769x769",".","Default",":","False",".","pretrained","(","str",",","optional",")",":","The","path","or","url","of","pretrained","model",".","Default",":","None","."]
code: def forward(self, x):
      feat_list = self.backbone(x)
      logit_list = self.head(feat_list)
      return [
          F.interpolate(
              logit,
              paddle.shape(x)[2:],
              mode="bilinear",
              align_corners=self.align_corners,
          )
          for logit in logit_list
      ]
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
  from paddleseg.utils import utils
label_desc: Use image node_id 2 for calling the GCNet obj's underlying member method code with example usage: obj.forward(x) and returns: unknown