code: def fix_init_weight(self):
      def rescale(param, layer_id):
          param.div_(math.sqrt(2.0 * layer_id))
  
      for layer_id, layer in enumerate(self.blocks):
          rescale(layer.attn.proj.weight.data, layer_id + 1)
          rescale(layer.mlp.fc2.weight.data, layer_id + 1)
      for trans in self.pred_head.transforms:
          for layer_id, layer in enumerate(trans):
              if hasattr(layer, "attn"):
                  rescale(
                      layer.attn.proj.weight.data,
                      layer_id + 1 + len(self.blocks),
                  )  # or + len(self.blocks)
                  rescale(layer.mlp.fc2.weight.data, layer_id + 1)
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.init import trunc_normal_
  import slowfast.utils.logging
  import slowfast.utils.misc
  from slowfast.models import head_helper
  from slowfast.models.attention import attention_pool
  from slowfast.models.utils import calc_mvit_feature_geometry
  from slowfast.models.video_model_builder import MViT
  from .None import head_helper, operators, resnet_helper, stem_helper
  from .build import MODEL_REGISTRY
label_desc: Use image node_id 3 for calling the MaskMViT obj's underlying member method code with example usage: obj.fix_init_weight() without return types