code: def test_DiarizeSpeech(
      diar_config_file,
      batch_size,
      input_size,
      segment_size,
      normalize_segment_scale,
      num_spk,
  ):
      diarize_speech = DiarizeSpeech(
          train_config=diar_config_file,
          segment_size=segment_size,
          normalize_segment_scale=normalize_segment_scale,
          num_spk=num_spk,
      )
      wav = torch.rand(batch_size, input_size)
      diarize_speech(wav, fs=8000)
  
file_path: espnet/test/espnet2/bin/test_diar_inference.py
imports: from argparse import ArgumentParser
  from pathlib import Path
  import pytest
  import torch
  from espnet2.bin.diar_inference import DiarizeSpeech, get_parser, main
  from espnet2.tasks.diar import DiarizationTask
  from espnet2.tasks.enh_s2t import EnhS2TTask
label_desc: Use image node_id 4 for calling a global function with example usage: test_DiarizeSpeech(diar_config_file, batch_size, input_size, segment_size, normalize_segment_scale, num_spk) without return types