code: def reset_adapter_parameters_random(self, adapter_name: str):
      # Original implementation performs initialization with normal distribution
      # https://github.com/KohakuBlueleaf/LyCORIS/blob/3549fdef8f564761d68b695a08ef88b1122fdedc/lycoris/modules/loha.py#L158
  
      # FedPara paper proposes to perform He initialization, let's stick with it
      # It is enough to initialize only single matrix with zeros to make adapter do nothing after initialization
      if adapter_name in self.hada_w1_a.keys():
          nn.init.kaiming_uniform_(
              self.hada_w1_a[adapter_name], a=math.sqrt(5)
          )
          nn.init.kaiming_uniform_(
              self.hada_w1_b[adapter_name], a=math.sqrt(5)
          )
          nn.init.kaiming_uniform_(
              self.hada_w2_a[adapter_name], a=math.sqrt(5)
          )
          nn.init.kaiming_uniform_(
              self.hada_w2_b[adapter_name], a=math.sqrt(5)
          )
      if adapter_name in self.hada_t1.keys():
          nn.init.kaiming_uniform_(
              self.hada_t1[adapter_name], a=math.sqrt(5)
          )
          nn.init.kaiming_uniform_(
              self.hada_t2[adapter_name], a=math.sqrt(5)
          )
  
imports: import math
  from typing import Any, Set, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from peft.tuners.lycoris_utils import LycorisLayer
label_desc: Use image node_id 5 for calling the LoHaLayer obj's underlying member method code with example usage: obj.reset_adapter_parameters_random(adapter_name) without return types