def test_stack_histories_fail_wrong_type(self):
""" Should raise an error, as other is no ExperimentHistory but a list. """
histories0 = ExperimentHistories()
histories0.setup(1, 1, 1, 1, 1)
with self.assertRaises(AssertionError):
histories0.stack_histories([])
def test_stack_histories_fail_unequal_sparsity(self):
""" Should raise an error, as the sparsity-histories do not match. """
histories0, histories1 = ExperimentHistories(), ExperimentHistories()
histories0.setup(1, 1, 2, 3, 2)
histories1.setup(1, 1, 2, 3, 2)
histories0.sparsity, histories1.sparsity = np.array(
[1., 0.5]), np.array([1., 0.7])
with self.assertRaises(AssertionError):
histories0.stack_histories(histories1)
def test_stack_histories(self):
""" Should stack two histories, i.e. append their arrays at the net-dimension.
The sparsity histories should not be appended, as they need to be equal. """
histories0 = ExperimentHistories()
histories1 = ExperimentHistories()
histories0.setup(
2, 1, 2, 3, 2
) # arrays for accuracies and losses have shape (2, 2, 3), all filled with zeroes
histories1.setup(2, 1, 2, 3, 2)
# fill arrays for accuracies and losses with ones
histories1.train_loss = np.ones_like(histories1.train_loss)
histories1.val_loss = np.ones_like(histories1.val_loss)
histories1.val_acc = np.ones_like(histories1.val_acc)
histories1.test_acc = np.ones_like(histories1.test_acc)
# expected history for accuracies and losses
expected_history = np.array(
[[[0., 0., 0.], [0., 0., 0.]], [[0., 0., 0.], [0., 0., 0.]],
[[1., 1., 1.], [1., 1., 1.]], [[1., 1., 1.], [1., 1., 1.]]],
dtype=float)
result_history = histories0.stack_histories(histories1)
np.testing.assert_array_equal(expected_history,
result_history.train_loss)
np.testing.assert_array_equal(expected_history,
result_history.val_loss)
np.testing.assert_array_equal(expected_history, result_history.val_acc)
np.testing.assert_array_equal(expected_history,
result_history.test_acc)
np.testing.assert_array_equal(histories0.sparsity,
result_history.sparsity)
def test_get_all_random_experiment_histories_from_files(self):
""" Should load two fake random_histories from npz files. """
histories = ExperimentHistories()
histories.setup(1, 1, 1, 1, 1)
with TemporaryDirectory() as tmp_dir_name:
result_saver.save_experiment_histories_random_retrain(
tmp_dir_name, 'prefix', 0, histories)
result_saver.save_experiment_histories_random_retrain(
tmp_dir_name, 'prefix', 1, histories)
# load and validate histories from file
experiment_path_prefix = f"{tmp_dir_name}/prefix"
loaded_histories = result_loader.get_all_random_experiment_histories_from_files(
experiment_path_prefix, 2)
self.assertEqual(histories.stack_histories(histories),
loaded_histories)