code: def forward(self, x):
      normed = F.normalize(x, dim=-1)
      return normed * self.scale * self.gamma
  
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 2 for calling the RMSNorm obj's underlying member method code with example usage: obj.forward(x) and returns: unknown