code: def __init__(self, dim):
      super().__init__()
      self.scale = dim**0.5
      self.gamma = nn.Parameter(torch.ones(dim))
  
file_path: mixture-of-attention/mixture_of_attention/transformer.py
imports: import torch
  import torch.nn.functional
  from torch import nn, einsum
  from einops import rearrange
  from mixture_of_attention.mixture_of_attention import MixtureOfAutoregressiveAttention
  from mixture_of_attention.rotary_emb import RotaryEmbedding
label_desc: Use image node_id 1 to create a new RMSNorm object from inherited base classes: nn with example: obj = RMSNorm(dim)