docstr: Make masking for padding.
code: def make_pad_mask(self, seq_lens, max_audio_length, device=None):
      """Make masking for padding."""
      if device and self.seq_range.device != device:
          self.seq_range = self.seq_range.to(device)
      if self.seq_range.device != seq_lens.device:
          seq_lens = seq_lens.to(self.seq_range.device)
  
      mask = self.seq_range[:max_audio_length].expand(
          seq_lens.size(0), -1
      ) < seq_lens.unsqueeze(
          -1
      )  # [B, T]; bool
      mask = mask.unsqueeze(1)  # [B, 1, T]
  
      return mask
  
imports: import math
  from typing import Callable, Iterable, List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from torch.nn.init import _calculate_correct_fan
  from torch.nn.modules.utils import _single
  from nemo.collections.common.parts.utils import activation_registry
  from nemo.core.classes.mixins import AccessMixin
  from nemo.core.classes.mixins.adapter_mixins import AdapterModuleMixin
  from nemo.utils import logging
label_desc: Use image node_id 6 for calling the SqueezeExcite obj's underlying member method code with example usage: obj.make_pad_mask(seq_lens, max_audio_length, device) and returns: mask