code: def default_dataset_subset_sizes():
      n_train = 1000
      n_test = 100
      yield n_train, n_test
  
imports: import importlib
  import json
  import logging
  import os
  import shutil
  import tempfile
  from typing import Dict, List, TYPE_CHECKING, Union
  import warnings
  import numpy
  import pytest
  import requests
  from art.data_generators import KerasDataGenerator, MXDataGenerator, PyTorchDataGenerator, TensorFlowDataGenerator, TensorFlowV2DataGenerator
  from art.defences.preprocessor import FeatureSqueezing, JpegCompression, SpatialSmoothing
  from art.estimators.classification import KerasClassifier
  from tests.utils import ARTTestFixtureNotImplemented, get_attack_classifier_pt, get_image_classifier_kr, get_image_classifier_kr_functional, get_image_classifier_kr_tf, get_image_classifier_kr_tf_functional, get_image_classifier_kr_tf_with_wildcard, get_image_classifier_mxnet_custom_ini, get_image_classifier_pt, get_image_classifier_pt_functional, get_image_classifier_tf, get_image_classifier_hf, get_image_gan_tf_v2, get_image_generator_tf_v2, get_tabular_classifier_kr, get_tabular_classifier_pt, get_tabular_classifier_scikit_list, get_tabular_classifier_tf, load_dataset, master_seed
label_desc: Use image node_id 29 for calling a global function with example usage: default_dataset_subset_sizes() without return types