code: def forward(self, input):
      if self.training:
          return torch.nn.functional.linear(
              input,
              self.weight_mu + self.weight_sigma * self.weight_epsilon,
              self.bias_mu + self.bias_sigma * self.bias_epsilon,
          )
      else:
          return torch.nn.functional.linear(
              input, self.weight_mu, self.bias_mu
          )
  
file_path: SerpentAI/serpent/machine_learning/reinforcement_learning/rainbow_dqn/noisy_linear.py
imports: import math
  import torch
label_desc: Use image node_id 4 for calling the NoisyLinear obj's underlying member method code with example usage: obj.forward(input) and returns: torch, torch