code: def setUp(self):
      study_configuration_json = {
          "goal": "MAXIMIZE",
          "maxTrials": 5,
          "maxParallelTrials": 1,
          "randomInitTrials": 1,
          "params": [
              {
                  "parameterName": "l1_normalization",
                  "type": "DOUBLE",
                  "minValue": 0.01,
                  "maxValue": 0.99,
                  "scalingType": "LINEAR",
              },
              {
                  "parameterName": "learning_rate",
                  "type": "DOUBLE",
                  "minValue": 0.01,
                  "maxValue": 0.5,
                  "scalingType": "LINEAR",
              },
              {
                  "parameterName": "hidden2",
                  "type": "DISCRETE",
                  "feasiblePoints": "8, 16, 32, 64",
                  "scalingType": "LINEAR",
              },
              {
                  "parameterName": "optimizer",
                  "type": "CATEGORICAL",
                  "feasiblePoints": "sgd, adagrad, adam, ftrl",
                  "scalingType": "LINEAR",
              },
          ],
      }
      study_configuration = json.dumps(study_configuration_json)
      self.study = Study.create("CmaesStudy", study_configuration)
  
file_path: advisor/advisor_server/suggestion/algorithm/mocmaes_test.py
imports: import json
  from django.test import TestCase
  from suggestion.models import Study
  from suggestion.algorithm.abstract_algorithm import AbstractSuggestionAlgorithm
  from suggestion.algorithm.mocmaes import MocmaesAlgorithm
label_desc: Use image node_id 1 for calling the MocmaesAlgorithmTest obj's underlying member method code with example usage: obj.setUp() without return types