class_docstr: This class is adapted from the compacter implementation at https://github.com/rabeehk/compacter
code: def reset_parameters(self):
      if not self.shared_W_phm:
          self._init_W()
  
      if self.bias_flag:
          self.b.data = torch.zeros_like(self.b.data)
  
      if not self.shared_phm_rule:
          if self.factorized_phm_rule:
              if self.c_init == "uniform":
                  self.phm_rule_left.data.uniform_(-0.01, 0.01)
                  self.phm_rule_right.data.uniform_(-0.01, 0.01)
              elif self.c_init == "normal":
                  self.phm_rule_left.data.normal_(std=0.01)
                  self.phm_rule_right.data.normal_(std=0.01)
              else:
                  raise NotImplementedError
          else:
              if self.c_init == "uniform":
                  self.phm_rule.data.uniform_(-0.01, 0.01)
              elif self.c_init == "normal":
                  self.phm_rule.data.normal_(mean=0, std=0.01)
              else:
                  raise NotImplementedError
  
imports: import math
  import torch
  from torch import nn
  from transformers.activations import get_activation
  from ..configuration import AdapterFusionConfig, BnConfig
  from ..context import ForwardContext
label_desc: Use image node_id 3 for calling the PHMLayer obj's underlying member method code with example usage: obj.reset_parameters() without return types