def test_confusion_matrix():
"""test_confusion_matrix"""
x = Tensor(np.array([1, 0, 1, 0]))
y = Tensor(np.array([1, 0, 0, 1]))
metric = ConfusionMatrix(num_classes=2)
metric.clear()
metric.update(x, y)
output = metric.eval()
assert np.allclose(output, np.array([[1, 1], [1, 1]]))
def test_confusion_matrix_update_len():
x = Tensor(np.array([[0.2, 0.5, 0.7], [0.3, 0.1, 0.2], [0.9, 0.6, 0.5]]))
metric = ConfusionMatrix(num_classes=2)
metric.clear()
with pytest.raises(ValueError):
metric.update(x)
def test_confusion_matrix_runtime():
metric = ConfusionMatrix(num_classes=2)
metric.clear()
with pytest.raises(RuntimeError):
metric.eval()
def test_confusion_matrix_init_threshold():
with pytest.raises(TypeError):
ConfusionMatrix(num_classes=2, normalize='no_norm', threshold=1)
def test_confusion_matrix_init_normalize_value():
with pytest.raises(ValueError):
ConfusionMatrix(num_classes=2, normalize="wwe")
def test_confusion_matrix_init_num_classes():
with pytest.raises(TypeError):
ConfusionMatrix(num_classes='1')