docstr: The setup class method for the basic test case with all default values.
docstr_tok: ["The","setup","class","method","for","the","basic","test","case","with","all","default","values","."]
code: def setUpClass(self):
      """
      The setup class method for the basic test case with all default values.
      """
      _load_data(self)
  
      # Create the model
      self.model = tc.activity_classifier.create(
          self.data,
          features=self.features,
          target=self.target,
          session_id=self.session_id,
          prediction_window=self.prediction_window,
          validation_set=None,
      )
  
      self.def_opts = {
          "verbose": True,
          "prediction_window": 100,
          "max_iterations": 10,
          "batch_size": 32,
      }
  
      # Answers
      self.opts = self.def_opts.copy()
      self.opts["prediction_window"] = self.prediction_window
  
      self.get_ans = {
          "features": lambda x: x == self.features,
          "training_time": lambda x: x > 0,
          "target": lambda x: x == self.target,
          "verbose": lambda x: x == True,
          "session_id": lambda x: x == self.session_id,
          "prediction_window": lambda x: x == self.prediction_window,
          "training_accuracy": lambda x: x >= 0 and x <= 1,
          "training_log_loss": lambda x: isinstance(x, Number),
          "max_iterations": lambda x: x
          == self.def_opts["max_iterations"],
          "num_sessions": lambda x: x == self.num_sessions,
          "num_features": lambda x: x == self.num_features,
          "num_examples": lambda x: x == self.num_examples,
          "num_classes": lambda x: x == self.num_labels,
          "batch_size": lambda x: x == self.def_opts["batch_size"],
          "classes": lambda x: sorted(x)
          == sorted(self.data[self.target].unique()),
      }
      self.exposed_fields_ans = list(self.get_ans.keys())
      self.fields_ans = self.exposed_fields_ans + [
          "training_report_by_class",
          "training_iterations",
          "random_seed",
          "training_precision",
          "training_confusion_matrix",
          "use_data_augmentation",
          "training_f1_score",
          "training_auc",
          "training_roc_curve",
          "training_recall",
      ]
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import unittest
  import turicreate
  import random
  import tempfile
  import math
  import numpy
  from numbers import Number
  from .None import util
  import pytest
  from turicreate.toolkits._internal_utils import _mac_ver
  from turicreate.toolkits._main import ToolkitError
  import uuid
label_desc: Use image node_id 1 for calling the ActivityClassifierTest obj's underlying member method code with example usage: obj.setUpClass() without return types