[composite compliance] fix linalg.eigvals (#84137)
linalg.eigvals fails in some cases with functorch and the root of the
problem is that it is not composite compliant.
In particular, checks that branch on whether or not a Tensor requires
grad do not work with functorch. In order to support functorch with
them, we have to include an additional "if the tensor is a Tensor
Subclass, then assume that it MAY require grad, so we must always go
through the differentiable path".
This PR also changes the batching rule for linalg.eigvals to be a
decomposition instead of what it was previously. What it was previously
was masking the error in functorch's test suite.
Unfortunately we don't comprehensive tests for this on the functorch
side which is why this was not caught before. I'll look into why
that is in the future; it's a bit complicated.
Test Plan:
- wait for tests
Pull Request resolved: https://github.com/pytorch/pytorch/pull/84137
Approved by: https://github.com/Lezcano, https://github.com/IvanYashchuk, https://github.com/samdow
