code: def make_seq_mask_like(
      lengths: torch.Tensor,
      like: torch.Tensor,
      time_dim: int = -1,
      valid_ones: bool = True,
  ) -> torch.Tensor:
      """
  
      Args:
          lengths: Tensor with shape [B] containing the sequence length of each batch element
          like: The mask will contain the same number of dimensions as this Tensor, and will have the same max
              length in the time dimension of this Tensor.
          time_dim: Time dimension of the `shape_tensor` and the resulting mask. Zero-based.
          valid_ones: If True, valid tokens will contain value `1` and padding will be `0`. Else, invert.
  
      Returns:
          A :class:`torch.Tensor` containing 1's and 0's for valid and invalid tokens, respectively, if `valid_ones`, else
          vice-versa. Mask will have the same number of dimensions as `like`. Batch and time dimensions will match
          the `like`. All other dimensions will be singletons. E.g., if `like.shape == [3, 4, 5]` and
          `time_dim == -1', mask will have shape `[3, 1, 5]`.
      """
      # Mask with shape [B, T]
      mask = (
          torch.arange(like.shape[time_dim], device=like.device)
          .repeat(lengths.shape[0], 1)
          .lt(lengths.view(-1, 1))
      )
      # [B, T] -> [B, *, T] where * is any number of singleton dimensions to expand to like tensor
      for _ in range(like.dim() - mask.dim()):
          mask = mask.unsqueeze(1)
      # If needed, transpose time dim
      if time_dim != -1 and time_dim != mask.dim() - 1:
          mask = mask.transpose(-1, time_dim)
      # Maybe invert the padded vs. valid token values
      if not valid_ones:
          mask = ~mask
      return mask
  
imports: import math
  import random
  from typing import Optional, Tuple, Union
  import librosa
  import numpy
  import torch
  import torch.nn
  from nemo.collections.asr.parts.preprocessing.perturb import AudioAugmentor
  from nemo.collections.asr.parts.preprocessing.segment import AudioSegment
  from nemo.utils import logging
label_desc: Use image node_id 4 for calling a global function with example usage: make_seq_mask_like(lengths, like, time_dim, valid_ones) and returns: mask