class_docstr: Asymmetric Pyramid Non-local Block.
  
  Args:
      in_channels (int): The input channels of APNB module.
      out_channels (int): Out channels of APNB module.
      key_channels (int): The key channels in self-attention block.
      value_channels (int): The value channels in self-attention block.
      dropout_prob (float): The dropout rate of output.
      repeat_sizes (tuple, optional): The number of AFNB modules. Default: ([1]).
      psp_size (tuple, optional): The out size of pooled feature maps. Default: (1, 3, 6, 8).
code: def forward(self, x):
      priors = [stage(x) for stage in self.stages]
      context = priors[0]
      for i in range(1, len(priors)):
          context += priors[i]
  
      output = self.conv_bn(paddle.concat([context, x], axis=1))
      output = self.dropout(output)
  
      return output
  
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 APNB obj's underlying member method code with example usage: obj.forward(x) and returns: output