code: def test_normalize_audio(self, sample_len, gain):
      array_raw = np.random.randn(sample_len)
      array_input = torch.from_numpy(
          gain * array_raw / np.max(np.abs(array_raw))
      )
      norm_array = normalize_audio(array_input)
      assert torch.max(torch.abs(norm_array)) == 1.0
      assert torch.min(torch.abs(norm_array)) < 1.0
  
imports: import os
  import numpy
  import pytest
  import torch
  from omegaconf import DictConfig
  from nemo.collections.asr.parts.utils.data_simulation_utils import DataAnnotator, SpeechSampler, add_silence_to_alignments, binary_search_alignments, get_cleaned_base_path, get_split_points_in_alignments, normalize_audio, read_noise_manifest
  from nemo.collections.asr.parts.utils.manifest_utils import get_ctm_line
label_desc: Use image node_id 2 for calling the TestDataSimulatorUtils obj's underlying member method code with example usage: obj.test_normalize_audio(sample_len, gain) without return types