class_docstr: Applies `Layer Normalization <https://arxiv.org/abs/1607.06450>`_ over a input tensor with FP32 precision
code: def __init__(
      self,
      normalized_shape: Union[int, List[int], Size],
      eps: Optional[float] = 1e-5,
      elementwise_affine: Optional[bool] = True,
      *args,
      **kwargs,
  ):
      super().__init__(
          normalized_shape=normalized_shape,
          eps=eps,
          elementwise_affine=elementwise_affine,
          *args,
          **kwargs,
      )
  
file_path: ml-cvnets/cvnets/layers/normalization/layer_norm.py
imports: from typing import List, Optional, Union
  import torch
  from torch import Size, Tensor, nn
  from cvnets.layers.normalization import register_norm_fn
label_desc: Use image node_id 1 to create a new LayerNormFP32 object from inherited base classes: LayerNorm with example: obj = LayerNormFP32(normalized_shape, eps, elementwise_affine)