def test_get_test_epochs() -> None:
"""
Test if the creation of the list of epochs for model testing will always contain at least the last training epoch.
"""
c = DeepLearningConfig(num_epochs=2,
test_start_epoch=100,
test_diff_epochs=2,
test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [2]
c = DeepLearningConfig(num_epochs=100,
test_start_epoch=100,
test_diff_epochs=2,
test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [100]
c = DeepLearningConfig(num_epochs=150,
test_start_epoch=100,
test_diff_epochs=2,
test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [100, 110, 150]
c = DeepLearningConfig(num_epochs=100,
test_start_epoch=100,
test_diff_epochs=0,
test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [100]
c = DeepLearningConfig(num_epochs=100,
test_start_epoch=200,
test_diff_epochs=None,
test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [100]
def test_get_test_epochs() -> None:
"""
Test if the creation of the list of epochs for model testing will always contain at least the last training epoch.
"""
c = DeepLearningConfig(num_epochs=2, test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [2]
c = DeepLearningConfig(num_epochs=100, test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [100]
c = DeepLearningConfig(num_epochs=150, test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [100, 110, 150]
c = DeepLearningConfig(num_epochs=100, test_start_epoch=100, test_diff_epochs=0, test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [100]
c = DeepLearningConfig(num_epochs=100, test_start_epoch=200, test_diff_epochs=None, test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [100]
c = DeepLearningConfig(num_epochs=100, epochs_to_test=[1, 3, 5],
should_validate=False)
assert c.get_test_epochs() == [1, 3, 5, 100]
# epochs_to_test should have precedence over (test_start_epoch, test_diff_epochs and test_step_epochs)
c = DeepLearningConfig(num_epochs=150, epochs_to_test=[1, 3, 5],
test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10,
should_validate=False)
assert c.get_test_epochs() == [1, 3, 5, 150]