def test_backward1(self): x = np.array([[-1, 0, 1, 2], [2, 0, 1, -1]]) f = lambda x: F.log_softmax(x) self.assertTrue(gradient_check(f, x))
def test_backward2(self): x = np.random.randn(10, 10) f = lambda x: F.log_softmax(x) self.assertTrue(gradient_check(f, x))
def test_forward1(self): x = np.array([[-1, 0, 1, 2], [2, 0, 1, -1]], np.float32) y = F.log_softmax(x) y2 = CF.log_softmax(x) res = np.allclose(y.data, y2.data) self.assertTrue(res)