1. 模块列表
  2. 函数列表
  3. torch.inverse()

Python torch 模块，inverse() 实例源码

我们从Python开源项目中，提取了以下12个代码示例，用于说明如何使用torch.inverse()。

项目：pytorch-dist    作者：apaszke    | 项目源码 | 文件源码 
def test_inverse(self):
        M = torch.randn(5,5)
        MI = torch.inverse(M)
        E = torch.eye(5)
        self.assertFalse(MI.is_contiguous(), 'MI is contiguous')
        self.assertEqual(E, torch.mm(M, MI), 1e-8, 'inverse value')
        self.assertEqual(E, torch.mm(MI, M), 1e-8, 'inverse value')

        MII = torch.Tensor(5, 5)
        torch.inverse(MII, M)
        self.assertFalse(MII.is_contiguous(), 'MII is contiguous')
        self.assertEqual(MII, MI, 0, 'inverse value in-place')
        # second call, now that MII is transposed
        torch.inverse(MII, M)
        self.assertFalse(MII.is_contiguous(), 'MII is contiguous')
        self.assertEqual(MII, MI, 0, 'inverse value in-place')
项目：pytorch    作者：tylergenter    | 项目源码 | 文件源码 
def test_inverse(self):
        M = torch.randn(5, 5)
        MI = torch.inverse(M)
        E = torch.eye(5)
        self.assertFalse(MI.is_contiguous(), 'MI is contiguous')
        self.assertEqual(E, torch.mm(M, MI), 1e-8, 'inverse value')
        self.assertEqual(E, torch.mm(MI, M), 1e-8, 'inverse value')

        MII = torch.Tensor(5, 5)
        torch.inverse(M, out=MII)
        self.assertFalse(MII.is_contiguous(), 'MII is contiguous')
        self.assertEqual(MII, MI, 0, 'inverse value in-place')
        # second call, now that MII is transposed
        torch.inverse(M, out=MII)
        self.assertFalse(MII.is_contiguous(), 'MII is contiguous')
        self.assertEqual(MII, MI, 0, 'inverse value in-place')
项目：pytorch-coriander    作者：hughperkins    | 项目源码 | 文件源码 
def test_inverse(self):
        M = torch.randn(5, 5)
        MI = torch.inverse(M)
        E = torch.eye(5)
        self.assertFalse(MI.is_contiguous(), 'MI is contiguous')
        self.assertEqual(E, torch.mm(M, MI), 1e-8, 'inverse value')
        self.assertEqual(E, torch.mm(MI, M), 1e-8, 'inverse value')

        MII = torch.Tensor(5, 5)
        torch.inverse(M, out=MII)
        self.assertFalse(MII.is_contiguous(), 'MII is contiguous')
        self.assertEqual(MII, MI, 0, 'inverse value in-place')
        # second call, now that MII is transposed
        torch.inverse(M, out=MII)
        self.assertFalse(MII.is_contiguous(), 'MII is contiguous')
        self.assertEqual(MII, MI, 0, 'inverse value in-place')
项目：pytorch    作者：ezyang    | 项目源码 | 文件源码 
def test_inverse(self):
        M = torch.randn(5, 5)
        MI = torch.inverse(M)
        E = torch.eye(5)
        self.assertFalse(MI.is_contiguous(), 'MI is contiguous')
        self.assertEqual(E, torch.mm(M, MI), 1e-8, 'inverse value')
        self.assertEqual(E, torch.mm(MI, M), 1e-8, 'inverse value')

        MII = torch.Tensor(5, 5)
        torch.inverse(M, out=MII)
        self.assertFalse(MII.is_contiguous(), 'MII is contiguous')
        self.assertEqual(MII, MI, 0, 'inverse value in-place')
        # second call, now that MII is transposed
        torch.inverse(M, out=MII)
        self.assertFalse(MII.is_contiguous(), 'MII is contiguous')
        self.assertEqual(MII, MI, 0, 'inverse value in-place')
项目：pytorch    作者：pytorch    | 项目源码 | 文件源码 
def test_inverse(self):
        M = torch.randn(5, 5)
        MI = torch.inverse(M)
        E = torch.eye(5)
        self.assertFalse(MI.is_contiguous(), 'MI is contiguous')
        self.assertEqual(E, torch.mm(M, MI), 1e-8, 'inverse value')
        self.assertEqual(E, torch.mm(MI, M), 1e-8, 'inverse value')

        MII = torch.Tensor(5, 5)
        torch.inverse(M, out=MII)
        self.assertFalse(MII.is_contiguous(), 'MII is contiguous')
        self.assertEqual(MII, MI, 0, 'inverse value in-place')
        # second call, now that MII is transposed
        torch.inverse(M, out=MII)
        self.assertFalse(MII.is_contiguous(), 'MII is contiguous')
        self.assertEqual(MII, MI, 0, 'inverse value in-place')
项目：pytorch-dist    作者：apaszke    | 项目源码 | 文件源码 
def tset_potri(self):
        a=torch.Tensor(((6.80, -2.11,  5.66,  5.97,  8.23),
                        (-6.05, -3.30,  5.36, -4.44,  1.08),
                        (-0.45,  2.58, -2.70,  0.27,  9.04),
                        (8.32,  2.71,  4.35, -7.17,  2.14),
                        (-9.67, -5.14, -7.26,  6.08, -6.87))).t()

        # make sure 'a' is symmetric PSD
        a = a * a.t()

        # compute inverse directly
        inv0 = torch.inverse(a)

        # default case
        chol = torch.potrf(a)
        inv1 = torch.potri(chol)
        self.assertLessEqual(inv0.dist(inv1), 1e-12)

        # upper Triangular Test
        chol = torch.potrf(a, 'U')
        inv1 = torch.potri(chol, 'U')
        self.assertLessEqual(inv0.dist(inv1), 1e-12)

        # lower Triangular Test
        chol = torch.potrf(a, 'L')
        inv1 = torch.potri(chol, 'L')
        self.assertLessEqual(inv0.dist(inv1), 1e-12)
项目：pytorch    作者：tylergenter    | 项目源码 | 文件源码 
def tset_potri(self):
        a = torch.Tensor(((6.80, -2.11, 5.66, 5.97, 8.23),
                          (-6.05, -3.30, 5.36, -4.44, 1.08),
                          (-0.45, 2.58, -2.70, 0.27, 9.04),
                          (8.32, 2.71, 4.35, -7.17, 2.14),
                          (-9.67, -5.14, -7.26, 6.08, -6.87))).t()

        # make sure 'a' is symmetric PSD
        a = a * a.t()

        # compute inverse directly
        inv0 = torch.inverse(a)

        # default case
        chol = torch.potrf(a)
        inv1 = torch.potri(chol)
        self.assertLessEqual(inv0.dist(inv1), 1e-12)

        # upper Triangular Test
        chol = torch.potrf(a, 'U')
        inv1 = torch.potri(chol, 'U')
        self.assertLessEqual(inv0.dist(inv1), 1e-12)

        # lower Triangular Test
        chol = torch.potrf(a, 'L')
        inv1 = torch.potri(chol, 'L')
        self.assertLessEqual(inv0.dist(inv1), 1e-12)
项目：pytorch-coriander    作者：hughperkins    | 项目源码 | 文件源码 
def tset_potri(self):
        a = torch.Tensor(((6.80, -2.11, 5.66, 5.97, 8.23),
                          (-6.05, -3.30, 5.36, -4.44, 1.08),
                          (-0.45, 2.58, -2.70, 0.27, 9.04),
                          (8.32, 2.71, 4.35, -7.17, 2.14),
                          (-9.67, -5.14, -7.26, 6.08, -6.87))).t()

        # make sure 'a' is symmetric PSD
        a = a * a.t()

        # compute inverse directly
        inv0 = torch.inverse(a)

        # default case
        chol = torch.potrf(a)
        inv1 = torch.potri(chol)
        self.assertLessEqual(inv0.dist(inv1), 1e-12)

        # upper Triangular Test
        chol = torch.potrf(a, 'U')
        inv1 = torch.potri(chol, 'U')
        self.assertLessEqual(inv0.dist(inv1), 1e-12)

        # lower Triangular Test
        chol = torch.potrf(a, 'L')
        inv1 = torch.potri(chol, 'L')
        self.assertLessEqual(inv0.dist(inv1), 1e-12)
项目：pytorch    作者：ezyang    | 项目源码 | 文件源码 
def forward(ctx, input):
        inverse = torch.inverse(input)
        ctx.save_for_backward(inverse)
        return inverse
项目：pytorch    作者：ezyang    | 项目源码 | 文件源码 
def backward(ctx, grad_output):
        inverse, = ctx.saved_variables
        return -torch.mm(inverse.t(), torch.mm(grad_output, inverse.t()))
项目：pytorch    作者：ezyang    | 项目源码 | 文件源码 
def tset_potri(self):
        a = torch.Tensor(((6.80, -2.11, 5.66, 5.97, 8.23),
                          (-6.05, -3.30, 5.36, -4.44, 1.08),
                          (-0.45, 2.58, -2.70, 0.27, 9.04),
                          (8.32, 2.71, 4.35, -7.17, 2.14),
                          (-9.67, -5.14, -7.26, 6.08, -6.87))).t()

        # make sure 'a' is symmetric PSD
        a = a * a.t()

        # compute inverse directly
        inv0 = torch.inverse(a)

        # default case
        chol = torch.potrf(a)
        inv1 = torch.potri(chol)
        self.assertLessEqual(inv0.dist(inv1), 1e-12)

        # upper Triangular Test
        chol = torch.potrf(a, 'U')
        inv1 = torch.potri(chol, 'U')
        self.assertLessEqual(inv0.dist(inv1), 1e-12)

        # lower Triangular Test
        chol = torch.potrf(a, 'L')
        inv1 = torch.potri(chol, 'L')
        self.assertLessEqual(inv0.dist(inv1), 1e-12)
项目：pytorch    作者：pytorch    | 项目源码 | 文件源码 
def tset_potri(self):
        a = torch.Tensor(((6.80, -2.11, 5.66, 5.97, 8.23),
                          (-6.05, -3.30, 5.36, -4.44, 1.08),
                          (-0.45, 2.58, -2.70, 0.27, 9.04),
                          (8.32, 2.71, 4.35, -7.17, 2.14),
                          (-9.67, -5.14, -7.26, 6.08, -6.87))).t()

        # make sure 'a' is symmetric PSD
        a = a * a.t()

        # compute inverse directly
        inv0 = torch.inverse(a)

        # default case
        chol = torch.potrf(a)
        inv1 = torch.potri(chol)
        self.assertLessEqual(inv0.dist(inv1), 1e-12)

        # upper Triangular Test
        chol = torch.potrf(a, 'U')
        inv1 = torch.potri(chol, 'U')
        self.assertLessEqual(inv0.dist(inv1), 1e-12)

        # lower Triangular Test
        chol = torch.potrf(a, 'L')
        inv1 = torch.potri(chol, 'L')
        self.assertLessEqual(inv0.dist(inv1), 1e-12)