code: def relative_time_to_absolute(batch, relative_lens, rate):
      """Converts SpeechBrain style relative length to the absolute duration.
  
      Operates on batch level.
  
      Arguments
      ---------
      batch : torch.tensor
          Sequences to determine the duration for.
      relative_lens : torch.tensor
          The relative length of each sequence in batch. The longest sequence in
          the batch needs to have relative length 1.0.
      rate : float
          The rate at which sequence elements occur in real-world time. Sample
          rate, if batch is raw wavs (recommended) or 1/frame_shift if batch is
          features. This has to have 1/s as the unit.
  
      Returns
      ------:
      torch.tensor
          Duration of each sequence in seconds.
  
      Example
      -------
      >>> batch = torch.ones(2, 16000)
      >>> relative_lens = torch.tensor([3./4., 1.0])
      >>> rate = 16000
      >>> print(relative_time_to_absolute(batch, relative_lens, rate))
      tensor([0.7500, 1.0000])
      """
      max_len = batch.shape[1]
      durations = torch.round(relative_lens * max_len) / rate
      return durations
  
imports: import os
  import torch
  import logging
  import numpy
  import pickle
  import hashlib
  import csv
  import time
  import torchaudio
  import json
  import re
  from speechbrain.utils.torch_audio_backend import check_torchaudio_backend
label_desc: Use image node_id 13 for calling a global function with example usage: relative_time_to_absolute(batch, relative_lens, rate) and returns: durations