code: def __init__(self, in_dim, out_dim, bias=True, bias_init=0, lr_mul=1):
      super().__init__()
      self.weight = nn.Parameter(
          torch.randn(out_dim, in_dim).div_(lr_mul)
      )
      if bias:
          self.bias = nn.Parameter(
              torch.zeros(out_dim).fill_(bias_init)
          )
      else:
          self.bias = None
      self.scale = (1 / math.sqrt(in_dim)) * lr_mul
      self.lr_mul = lr_mul
  
file_path: TTS/TTS/tts/layers/tortoise/random_latent_generator.py
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new EqualLinear object from inherited base classes: nn with example: obj = EqualLinear(in_dim, out_dim, bias, bias_init, lr_mul)