class_docstr: Fused BatchNorm to use in Conformer to improve accuracy in finetuning with TTS scenario
  Drop-in replacement for BatchNorm1d with simple affine projection
class_docstr_tok: ["Fused","BatchNorm","to","use","in","Conformer","to","improve","accuracy","in","finetuning","with","TTS","scenario","Drop-in","replacement","for","BatchNorm1d","with","simple","affine","projection"]
code: def forward(self, x: torch.Tensor):
      if x.dim() == 3:
          return x * self.weight.unsqueeze(-1) + self.bias.unsqueeze(-1)
      assert x.dim() == 2
      return x * self.weight + self.bias
  
file_path: NeMo/nemo/collections/asr/parts/submodules/batchnorm.py
imports: from __future__ import annotations
  from functools import reduce
  from typing import List
  import torch
  import torch.nn
label_desc: Use image node_id 3 for calling the FusedBatchNorm1d obj's underlying member method code with example usage: obj.forward(x) and returns: unknown, unknown