class_docstr: An abstract class to handle weights initialization and a simple interface for downloading and loading pretrained
  models.
docstr: Initialize the weights
docstr_tok: ["Initialize","the","weights"]
code: def init_weights(self):
      """Initialize the weights"""
      self.backbone.init_weights()
      self.decode_head.init_weights()
      if self.auxiliary_head is not None:
          self.auxiliary_head.init_weights()
  
imports: from typing import List, Optional, Tuple, Union
  import torch
  from torch import nn
  from torch.nn import CrossEntropyLoss
  from ...None import AutoBackbone
  from ...modeling_outputs import SemanticSegmenterOutput
  from ...modeling_utils import PreTrainedModel
  from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, replace_return_docstrings
  from .configuration_upernet import UperNetConfig
label_desc: Use image node_id 2 for calling the UperNetPreTrainedModel obj's underlying member method code with example usage: obj.init_weights() without return types