code: def test_length_regulator():
      # prepare inputs
      idim = 5
      ilens = [10, 5, 3]
      xs = pad_list([torch.randn((ilen, idim)) for ilen in ilens], 0.0)
      ds = pad_list([torch.arange(ilen) for ilen in ilens], 0)
  
      # test with non-zero durations
      length_regulator = LengthRegulator()
      xs_expand = length_regulator(xs, ds)
      assert int(xs_expand.shape[1]) == int(ds.sum(dim=-1).max())
  
      # test with duration including zero
      ds[:, 2] = 0
      xs_expand = length_regulator(xs, ds)
      assert int(xs_expand.shape[1]) == int(ds.sum(dim=-1).max())
  
imports: import json
  import os
  import shutil
  import tempfile
  from argparse import Namespace
  import numpy
  import pytest
  import torch
  from espnet.nets.pytorch_backend.e2e_tts_fastspeech import FeedForwardTransformer
  from espnet.nets.pytorch_backend.e2e_tts_tacotron2 import Tacotron2
  from espnet.nets.pytorch_backend.e2e_tts_transformer import Transformer
  from espnet.nets.pytorch_backend.fastspeech.duration_calculator import DurationCalculator
  from espnet.nets.pytorch_backend.fastspeech.length_regulator import LengthRegulator
  from espnet.nets.pytorch_backend.nets_utils import pad_list
label_desc: Use image node_id 9 for calling a global function with example usage: test_length_regulator() without return types