def test_relu_api(self):
X = torch.arange(-5, 5, dtype=torch.float)
scale = 2.0
zero_point = 1
qX = torch.quantize_linear(X, scale=scale, zero_point=zero_point, dtype=torch.quint8)
qY = torch.ops.quantized.relu(qX)
qY_hat = qF.relu(qX)
self.assertEqual(qY, qY_hat)
def test_functional_api(self):
X = torch.arange(-5, 5, dtype=torch.float)
scale = 2.0
zero_point = 1
Y = X.numpy().copy()
Y[Y < 0] = 0
qY = _quantize(Y, scale, zero_point)
qX = X.quantize_linear(scale=scale,
zero_point=zero_point,
dtype=torch.qint8)
qY_hat = F.relu(qX)
np.testing.assert_equal(qY, qY_hat.int_repr())
