Fix slogdet sign requiring grad when input requires grad (#16337)

Summary:
The real fix for https://github.com/pytorch/pytorch/issues/15605.

This is sort of BC breaking because now
```py
In [1]: import torch

In [2]: a = torch.randn(3, 3, requires_grad=True)

In [3]: a.slogdet()
Out[3]: (tensor(1.), tensor(0.1356, grad_fn=<SlogdetBackward>))

In [4]: a.slogdet()[0].requires_grad
Out[4]: False
```
while before this patch ` a.slogdet()[0]` requires grad with `grad_fn=<SlogdetBackward>`. But any use of backproping through this value will meet the error in #15605 so I don't think this is a problem.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16337

Differential Revision: D13832644

Pulled By: soumith

fbshipit-source-id: f96c477e99edcbdbd966888e5c5ea7fd058429a8

1 files changed, 20 insertions, 0 deletions

diff --git a/test/test_autograd.py b/test/test_autograd.py
index 6525870fd9..31c138a798 100644
--- a/test/test_autograd.py
+++ b/test/test_autograd.py
@@ -204,6 +204,26 @@ class TestAutograd(TestCase):
         x_grad, x_grad_clone = compute_grad(create_graph=True)
         self.assertEqual(x_grad, x_grad_clone)
 
+    def test_slogdet_sign(self):
+        a = torch.randn(3, 3, requires_grad=True)
+        s, logdet = a.slogdet()
+
+        # test that sign should not require grad
+        self.assertFalse(s.requires_grad)
+
+        # test that backward through computation involving sign works
+        def sign_mul_logdet(mat):
+            s, logdet = mat.slogdet()
+            return s * logdet
+
+        u, s, v = a.detach().svd()
+        s.abs_().clamp_(0.0001)
+        for sign in (-1, 1):
+            s[-1] = sign
+            mat = torch.chain_matmul(u, s.diag(), v.t()).requires_grad_()
+            gradcheck(sign_mul_logdet, mat)
+            gradgradcheck(sign_mul_logdet, mat)
+
     def test_sum_to_with_empty_dim_grad(self):
         a = torch.rand(4, 0, requires_grad=True)
         b = torch.rand(4, 1, requires_grad=True)