class_docstr: An abstract class to handle weights initialization and a simple interface for downloading and loading pretrained
  models.
code: def _init_weights(self, module):
      if isinstance(module, nn.Conv2d):
          module.weight.data.normal_(
              mean=0.0, std=self.config.initializer_range
          )
          if module.bias is not None:
              module.bias.data.zero_()
  
imports: from dataclasses import dataclass
  from typing import Optional, Tuple
  import torch
  from torch import nn
  from ...None import AutoBackbone
  from ...modeling_utils import PreTrainedModel
  from ...utils import ModelOutput, add_start_docstrings, add_start_docstrings_to_model_forward, replace_return_docstrings
  from .configuration_vitmatte import VitMatteConfig
label_desc: Use image node_id 1 for calling the VitMattePreTrainedModel obj's underlying member method code with example usage: obj._init_weights(module) without return types