code: def test_DPCLSolver_forward(num_spk):
      batch = 2
      o = {"tf_embedding": torch.rand(batch, 10 * 200, 40)}
      inf = [torch.rand(batch, 10, 200) for spk in range(num_spk)]
      ref = [
          inf[num_spk - spk - 1] for spk in range(num_spk)
      ]  # reverse inf as ref
      solver = DPCLSolver(FrequencyDomainDPCL())
  
      loss, stats, others = solver(ref, inf, o)
  
imports: import pytest
  import torch
  from espnet2.enh.loss.criterions.tf_domain import FrequencyDomainDPCL
  from espnet2.enh.loss.wrappers.dpcl_solver import DPCLSolver
label_desc: Use image node_id 1 for calling a global function with example usage: test_DPCLSolver_forward(num_spk) without return types