docstr: Creates a backend mock
docstr_tok: ["Creates","a","backend","mock"]
code: def setUp(self):
      """
      Creates a backend mock
      """
      self.ev_path = os.path.join(this_directory, ".tmp_evaluations")
      if not os.path.exists(self.ev_path):
          os.mkdir(self.ev_path)
      dummy_model_files = [
          os.path.join(self.ev_path, str(n)) for n in range(100)
      ]
      dummy_pred_files = [
          os.path.join(self.ev_path, str(n)) for n in range(100, 200)
      ]
  
      backend_mock = unittest.mock.Mock()
      backend_mock.get_model_dir.return_value = self.ev_path
      backend_mock.get_model_path.side_effect = dummy_model_files
      backend_mock.get_prediction_output_path.side_effect = (
          dummy_pred_files
      )
      D = get_multiclass_classification_datamanager()
      backend_mock.load_datamanager.return_value = D
      backend_mock.temporary_directory = tempfile.gettempdir()
      self.backend_mock = backend_mock
  
      self.port = logging.handlers.DEFAULT_TCP_LOGGING_PORT
  
      self.working_directory = os.path.join(
          this_directory, ".tmp_%s" % self.id()
      )
  
imports: import logging.handlers
  import os
  import shutil
  import sys
  import tempfile
  import numpy
  import sklearn.dummy
  from smac.tae import StatusType
  from autosklearn.automl_common.common.utils.backend import Backend, BackendContext
  from autosklearn.evaluation.abstract_evaluator import AbstractEvaluator
  from autosklearn.metrics import accuracy
  from autosklearn.pipeline.components.base import _addons
  import unittest
  import unittest.mock
  from evaluation_util import get_multiclass_classification_datamanager
label_desc: Use image node_id 1 for calling the AbstractEvaluatorTest obj's underlying member method code with example usage: obj.setUp() without return types