code: def rms_layernorm(
      hidden: torch.Tensor, weight: torch.Tensor, eps: float
  ):
      old_dtype = hidden.dtype
      variance = (
          hidden.to(torch.float32).pow(2).mean(dim=-1, keepdim=True)
      )
      hidden = (hidden * torch.rsqrt(variance + eps)).to(old_dtype)
      return hidden * weight
  
imports: import torch
  import bmtrain
label_desc: Use image node_id 1 for calling a global function with example usage: rms_layernorm(hidden, weight, eps) and returns: unknown