avalanche_extension/avalanche/tests/test_fmnist_benckmarks.py

import unittest

from avalanche.benchmarks import Experience, SplitFMNIST
from tests.unit_tests_utils import load_experience_train_eval

MNIST_DOWNLOADS = 0
MNIST_DOWNLOAD_METHOD = None


class FMNISTBenchmarksTests(unittest.TestCase):
    def setUp(self):
        import avalanche.benchmarks.classic.cfashion_mnist as cfashion_mnist
        global MNIST_DOWNLOAD_METHOD
        MNIST_DOWNLOAD_METHOD = cfashion_mnist._get_fmnist_dataset

        def count_downloads(*args, **kwargs):
            global MNIST_DOWNLOADS
            MNIST_DOWNLOADS += 1
            return MNIST_DOWNLOAD_METHOD(*args, **kwargs)

        cfashion_mnist._get_fmnist_dataset = count_downloads

    def tearDown(self):
        global MNIST_DOWNLOAD_METHOD
        if MNIST_DOWNLOAD_METHOD is not None:
            import avalanche.benchmarks.classic.cfashion_mnist as cfashion_mnist
            cfashion_mnist._get_fmnist_dataset = MNIST_DOWNLOAD_METHOD
            MNIST_DOWNLOAD_METHOD = None

    def test_SplitFMNIST_benchmark(self):
        benchmark = SplitFMNIST(5)
        self.assertEqual(5, len(benchmark.train_stream))
        self.assertEqual(5, len(benchmark.test_stream))

        train_sz = 0
        for experience in benchmark.train_stream:
            self.assertIsInstance(experience, Experience)
            train_sz += len(experience.dataset)

            load_experience_train_eval(experience)

        self.assertEqual(60000, train_sz)

        test_sz = 0
        for experience in benchmark.test_stream:
            self.assertIsInstance(experience, Experience)
            test_sz += len(experience.dataset)

            load_experience_train_eval(experience)

        self.assertEqual(10000, test_sz)


if __name__ == '__main__':
    unittest.main()