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import pytest
from torch_geometric.explain.config import ExplainerConfig, ThresholdConfig
@pytest.mark.parametrize('threshold_pairs', [
('hard', 0.5, True),
('hard', 1.1, False),
('hard', -1, False),
('topk', 1, True),
('topk', 0, False),
('topk', -1, False),
('topk', 0.5, False),
('invalid', None, False),
('hard', None, False),
])
def test_threshold_config(threshold_pairs):
threshold_type, threshold_value, valid = threshold_pairs
if valid:
threshold = ThresholdConfig(threshold_type, threshold_value)
assert threshold.type.value == threshold_type
assert threshold.value == threshold_value
else:
with pytest.raises(ValueError):
ThresholdConfig(threshold_type, threshold_value)
@pytest.mark.parametrize('explanation_type', [
'model',
'phenomenon',
'invalid',
])
@pytest.mark.parametrize('mask_type', [
None,
'object',
'common_attributes',
'attributes',
'invalid',
])
def test_configuration_config(explanation_type, mask_type):
if (explanation_type != 'invalid' and mask_type is not None
and mask_type != 'invalid'):
config = ExplainerConfig(explanation_type, mask_type, None)
assert config.explanation_type.value == explanation_type
assert config.node_mask_type.value == mask_type
else:
with pytest.raises(ValueError):
ExplainerConfig(explanation_type, mask_type, mask_type)
|
