code: def structure_discrete_hmsvm_bmrm(m_data_dict=data_dict):
      import shogun as sg
  
      try:
          _ = sg.create_machine("DualLibQPBMSOSVM")
      except:
          print("DualLibQPBMSOSVM not available")
          return
  
      labels_array = m_data_dict["label"][0]
  
      idxs = numpy.nonzero(labels_array == -1)
      labels_array[idxs] = 0
  
      labels = sg.SequenceLabels(labels_array, 250, 500, 2)
      features = sg.RealMatrixFeatures(
          m_data_dict["signal"].astype(float), 250, 500
      )
  
      num_obs = 4  # given by the data file used
      model = sg.create_structured_model(
          "HMSVMModel",
          features=features,
          labels=labels,
          state_model_type="SMT_TWO_STATE",
          num_obs=num_obs,
      )
  
      sosvm = sg.create_machine(
          "DualLibQPBMSOSVM",
          model=model,
          labels=labels,
          m_lambda=5000.0,
      )
      sosvm.train()
      # print sosvm.get_w()
  
      predicted = sosvm.apply(features)
      evaluator = sg.create_evaluation("StructuredAccuracy")
      acc = evaluator.evaluate(predicted, labels)
  
label_desc: Use image node_id 1 for calling a global function with example usage: structure_discrete_hmsvm_bmrm(m_data_dict) without return types