code: def __init__(self, in_features, out_features, std_init=0.4):
      super().__init__()
  
      self.in_features = in_features
      self.out_features = out_features
      self.std_init = std_init
  
      self.weight_mu = torch.nn.Parameter(
          torch.empty(out_features, in_features)
      )
      self.weight_sigma = torch.nn.Parameter(
          torch.empty(out_features, in_features)
      )
  
      self.register_buffer(
          "weight_epsilon", torch.empty(out_features, in_features)
      )
  
      self.bias_mu = torch.nn.Parameter(torch.empty(out_features))
      self.bias_sigma = torch.nn.Parameter(torch.empty(out_features))
  
      self.register_buffer("bias_epsilon", torch.empty(out_features))
  
      self.reset_parameters()
      self.reset_noise()
  
file_path: SerpentAI/serpent/machine_learning/reinforcement_learning/rainbow_dqn/noisy_linear.py
imports: import math
  import torch
label_desc: Use image node_id 1 to create a new NoisyLinear object from inherited base classes: torch.nn with example: obj = NoisyLinear(in_features, out_features, std_init)