test_torch.py 文件源码

def test_pow(self):
        # [res] torch.pow([res,] x)

        # base - tensor, exponent - number
        # contiguous
        m1 = torch.randn(100,100)
        res1 = torch.pow(m1[4], 3)
        res2 = res1.clone().zero_()
        for i in range(res2.size(0)):
            res2[i] = math.pow(m1[4][i], 3)
        self.assertEqual(res1, res2)

        # non-contiguous
        m1 = torch.randn(100,100)
        res1 = torch.pow(m1[:,4], 3)
        res2 = res1.clone().zero_()
        for i in range(res2.size(0)):
            res2[i] = math.pow(m1[i,4], 3)
        self.assertEqual(res1, res2)

        # base - number, exponent - tensor
        # contiguous
        m1 = torch.randn(100,100)
        res1 = torch.pow(3, m1[4])
        res2 = res1.clone().zero_()
        for i in range(res2.size(0)):
            res2[i] = math.pow(3, m1[4,i])
        self.assertEqual(res1, res2)

        # non-contiguous
        m1 = torch.randn(100,100)
        res1 = torch.pow(3, m1[:,4])
        res2 = res1.clone().zero_()
        for i in range(res2.size(0)):
            res2[i] = math.pow(3, m1[i][4])
        self.assertEqual(res1, res2)