code: def test_criterion_behavior_noise_dereverb(
      encoder, decoder, extractor
  ):
      with pytest.raises(ValueError):
          ESPnetExtractionModel(
              encoder=encoder,
              extractor=extractor,
              decoder=decoder,
              loss_wrappers=[
                  PITSolver(criterion=SISNRLoss(is_noise_loss=True))
              ],
          )
      with pytest.raises(ValueError):
          ESPnetExtractionModel(
              encoder=encoder,
              extractor=extractor,
              decoder=decoder,
              loss_wrappers=[
                  PITSolver(criterion=SISNRLoss(is_dereverb_loss=True))
              ],
          )
  
file_path: espnet/test/espnet2/enh/test_espnet_model_tse.py
imports: import pytest
  import torch
  from packaging.version import parse
  from espnet2.enh.decoder.conv_decoder import ConvDecoder
  from espnet2.enh.decoder.stft_decoder import STFTDecoder
  from espnet2.enh.encoder.conv_encoder import ConvEncoder
  from espnet2.enh.encoder.stft_encoder import STFTEncoder
  from espnet2.enh.espnet_model_tse import ESPnetExtractionModel
  from espnet2.enh.extractor.td_speakerbeam_extractor import TDSpeakerBeamExtractor
  from espnet2.enh.loss.criterions.tf_domain import FrequencyDomainMSE
  from espnet2.enh.loss.criterions.time_domain import SISNRLoss
  from espnet2.enh.loss.wrappers.fixed_order import FixedOrderSolver
  from espnet2.enh.loss.wrappers.pit_solver import PITSolver
label_desc: Use image node_id 2 for calling a global function with example usage: test_criterion_behavior_noise_dereverb(encoder, decoder, extractor) without return types