code: def test_criterion_behavior_noise(encoder, decoder, separator):
      if not isinstance(encoder, STFTEncoder) and isinstance(
          separator, (DCCRNSeparator, DC_CRNSeparator)
      ):
          # skip because DCCRNSeparator and DC_CRNSeparator only work
          # for complex spectrum features
          return
      inputs = torch.randn(2, 300)
      ilens = torch.LongTensor([300, 200])
      speech_refs = [
          torch.randn(2, 300).float(),
          torch.randn(2, 300).float(),
      ]
      noise_ref = torch.randn(2, 300)
      enh_model = ESPnetEnhancementModel(
          encoder=encoder,
          separator=separator,
          decoder=decoder,
          mask_module=None,
          loss_wrappers=[
              PITSolver(criterion=SISNRLoss(is_noise_loss=True))
          ],
      )
  
      enh_model.train()
  
      kwargs = {
          "speech_mix": inputs,
          "speech_mix_lengths": ilens,
          **{
              "speech_ref{}".format(i + 1): speech_refs[i]
              for i in range(2)
          },
          "noise_ref1": noise_ref,
      }
      loss, stats, weight = enh_model(**kwargs)
  
imports: import pytest
  import torch
  from packaging.version import parse
  from espnet2.enh.decoder.conv_decoder import ConvDecoder
  from espnet2.enh.decoder.null_decoder import NullDecoder
  from espnet2.enh.decoder.stft_decoder import STFTDecoder
  from espnet2.enh.encoder.conv_encoder import ConvEncoder
  from espnet2.enh.encoder.null_encoder import NullEncoder
  from espnet2.enh.encoder.stft_encoder import STFTEncoder
  from espnet2.enh.espnet_model import ESPnetEnhancementModel
  from espnet2.enh.loss.criterions.tf_domain import FrequencyDomainL1, FrequencyDomainMSE
  from espnet2.enh.loss.criterions.time_domain import SISNRLoss
  from espnet2.enh.loss.wrappers.fixed_order import FixedOrderSolver
  from espnet2.enh.loss.wrappers.multilayer_pit_solver import MultiLayerPITSolver
  from espnet2.enh.loss.wrappers.pit_solver import PITSolver
  from espnet2.enh.separator.conformer_separator import ConformerSeparator
  from espnet2.enh.separator.dc_crn_separator import DC_CRNSeparator
  from espnet2.enh.separator.dccrn_separator import DCCRNSeparator
  from espnet2.enh.separator.dprnn_separator import DPRNNSeparator
  from espnet2.enh.separator.dptnet_separator import DPTNetSeparator
  from espnet2.enh.separator.ineube_separator import iNeuBe
  from espnet2.enh.separator.neural_beamformer import NeuralBeamformer
  from espnet2.enh.separator.rnn_separator import RNNSeparator
  from espnet2.enh.separator.svoice_separator import SVoiceSeparator
  from espnet2.enh.separator.tcn_separator import TCNSeparator
  from espnet2.enh.separator.tfgridnet_separator import TFGridNet
  from espnet2.enh.separator.tfgridnetv2_separator import TFGridNetV2
  from espnet2.enh.separator.transformer_separator import TransformerSeparator
  from espnet2.enh.separator.uses_separator import USESSeparator
label_desc: Use image node_id 2 for calling a global function with example usage: test_criterion_behavior_noise(encoder, decoder, separator) without return types