code: def forward_padding_mask(
      self,
      features: torch.Tensor,
      padding_mask: torch.Tensor,
  ) -> torch.Tensor:
      extra = padding_mask.size(1) % features.size(1)
      if extra > 0:
          padding_mask = padding_mask[:, :-extra]
      padding_mask = padding_mask.view(
          padding_mask.size(0), features.size(1), -1
      )
      # padding_mask = padding_mask.all(-1)
      padding_mask = padding_mask.any(-1)
      return padding_mask
  
imports: import logging
  import math
  from typing import List, Optional, Tuple
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import LayerNorm
  from TTS.vc.modules.freevc.wavlm.modules import Fp32GroupNorm, Fp32LayerNorm, GLU_Linear, GradMultiply, MultiheadAttention, SamePad, TransposeLast, get_activation_fn, init_bert_params
label_desc: Use image node_id 3 for calling the WavLM obj's underlying member method code with example usage: obj.forward_padding_mask(features, padding_mask) and returns: padding_mask