class_docstr: The DeepLabV3Head implementation based on PaddlePaddle.
  
  Args:
      Please Refer to DeepLabV3PHead above.
class_docstr_tok: ["The","DeepLabV3Head","implementation","based","on","PaddlePaddle",".","Args",":","Please","Refer","to","DeepLabV3PHead","above","."]
code: def __init__(
      self,
      num_classes,
      backbone_indices,
      backbone_channels,
      aspp_ratios,
      aspp_out_channels,
      align_corners,
  ):
      super().__init__()
  
      self.aspp = layers.ASPPModule(
          aspp_ratios,
          backbone_channels[0],
          aspp_out_channels,
          align_corners,
          use_sep_conv=False,
          image_pooling=True,
      )
  
      self.cls = nn.Conv2D(
          in_channels=aspp_out_channels,
          out_channels=num_classes,
          kernel_size=1,
      )
  
      self.backbone_indices = backbone_indices
  
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 1 to create a new DeepLabV3Head object from inherited base classes: nn with example: obj = DeepLabV3Head(num_classes, backbone_indices, backbone_channels, aspp_ratios, aspp_out_channels, align_corners)