docstr: Reset the parameters and buffers of the module.
docstr_tok: ["Reset","the","parameters","and","buffers","of","the","module","."]
code: def reset_lora_parameters(self) -> None:
      """Reset the parameters and buffers of the module."""
      if not self.skip_init:
          nn.init.kaiming_uniform_(self.lora_A, a=math.sqrt(5))
          nn.init.zeros_(self.lora_B)
  
imports: import math
  import re
  from abc import ABC, abstractmethod
  from dataclasses import dataclass
  from typing import Any, Dict, List, Literal, Optional, final
  import torch
  import torch.nn
  from torch import Tensor
  from torch.nn import Dropout
  from torch.nn.functional import embedding, linear
  from torch.nn.parameter import Parameter
  from fairseq2.nn import Embedding, Projection
  from fairseq2.typing import DataType, Device
label_desc: Use image node_id 3 for calling the LoRALinear obj's underlying member method code with example usage: obj.reset_lora_parameters() without return types