class_docstr: convolutional generator for UASR.
class_docstr_tok: ["convolutional","generator","for","UASR","."]
code: def bn_padded_data(
      self, feature: torch.Tensor, padding_mask: torch.Tensor
  ):
      normed_feature = feature.clone()
      normed_feature[~padding_mask] = self.bn(
          feature[~padding_mask].unsqueeze(-1)
      ).squeeze(-1)
      return normed_feature
  
imports: import argparse
  import logging
  from typing import Dict, Optional
  import torch
  from typeguard import check_argument_types
  from espnet2.uasr.generator.abs_generator import AbsGenerator
  from espnet2.utils.types import str2bool
label_desc: Use image node_id 4 for calling the ConvGenerator obj's underlying member method code with example usage: obj.bn_padded_data(feature, padding_mask) and returns: normed_feature