class_docstr: Applies a `Batch Normalization <https://arxiv.org/abs/1502.03167>`_ over a 4D input tensor in FP32
class_docstr_tok: ["Applies","a","`","Batch","Normalization","<","https",":","\/\/arxiv.org\/abs\/1502.03167",">","`","_","over","a","4D","input","tensor","in","FP32"]
code: def forward(self, input: Tensor) -> Tensor:
      inp_dtype = input.dtype
      return super().forward(input.to(torch.float32)).to(inp_dtype)
  
file_path: ml-cvnets/cvnets/layers/normalization/batch_norm.py
imports: from typing import Optional
  import torch
  from torch import Tensor, nn
  from cvnets.layers.normalization import register_norm_fn
label_desc: Use image node_id 2 for calling the BatchNorm2dFP32 obj's underlying member method code with example usage: obj.forward(input) and returns: super