code: def test_duration_calculator():
      # define duration calculator
      idim, odim = 10, 25
      teacher_model_args = make_transformer_args()
      teacher = Transformer(idim, odim, Namespace(**teacher_model_args))
      duration_calculator = DurationCalculator(teacher)
  
      # setup batch
      ilens = [10, 5, 3]
      olens = [20, 15, 10]
      batch = prepare_inputs(idim, odim, ilens, olens)
  
      # calculate durations
      ds = duration_calculator(
          batch["xs"], batch["ilens"], batch["ys"], batch["olens"]
      )
      np.testing.assert_array_equal(
          ds.sum(dim=-1).cpu().numpy(), batch["olens"].cpu().numpy()
      )
  
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 10 for calling a global function with example usage: test_duration_calculator() without return types