class_docstr: This class tests the deep partition ensemble classifier.
class_docstr_tok: ["This","class","tests","the","deep","partition","ensemble","classifier","."]
code: def setUpClass(cls):
      # Get MNIST
      (x_train, y_train), (x_test, y_test), _, _ = load_dataset("mnist")
      x_train, y_train = x_train[:NB_TRAIN], y_train[:NB_TRAIN]
      x_test, y_test = x_test[:NB_TEST], y_test[:NB_TEST]
      cls.mnist = (x_train, y_train), (x_test, y_test)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import os
  import unittest
  import numpy
  import tensorflow
  from tensorflow.keras.models import Sequential
  from tensorflow.keras.layers import Dense, Flatten, Conv2D, MaxPooling2D
  from tensorflow.keras.losses import categorical_crossentropy
  from tensorflow.keras.optimizers.legacy import Adam
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from art.utils import load_dataset
  from art.estimators.classification.deep_partition_ensemble import DeepPartitionEnsemble
  from art.estimators.classification import TensorFlowV2Classifier, PyTorchClassifier, KerasClassifier
  from tests.utils import master_seed
label_desc: Use image node_id 1 for calling the TestDeepPartitionEnsemble obj's underlying member method code with example usage: obj.setUpClass(cls) without return types