class_docstr: Implementation that supports fp16 inputs but fp32 gains/biases.
class_docstr_tok: ["Implementation","that","supports","fp16","inputs","but","fp32","gains\/biases","."]
code: def forward(self, x: th.Tensor):
      return super().forward(x.float()).to(x.dtype)
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from .nn import timestep_embedding
label_desc: Use image node_id 1 for calling the LayerNorm obj's underlying member method code with example usage: obj.forward(x) and returns: super