Added CUDA support for complex input for QR decomposition

[IvanYashchuk]

QR decomposition now works for complex inputs on GPU.

Ref. #33152

[dr-ci]

💊 CI failures summary and remediations

As of commit a180fef (more details on the Dr. CI page):

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• 1/1 failures possibly* introduced in this PR
  • 1/1 non-CircleCI failure(s)

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1 failure confirmed as flaky and can be ignored:

• pytorch_linux_bionic_py3_6_clang9_test

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ci.pytorch.org: 1 failed

• Failed: pr/caffe2-pytorch-linux-bionic-rocm3.7-py3.6-test

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This comment has been revised 3 times.

[codecov]

Codecov Report

Merging #45032 into master will increase coverage by 0.00%.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master   #45032   +/-   ##
=======================================
  Coverage   67.83%   67.84%           
=======================================
  Files         384      384           
  Lines       49962    49962           
=======================================
+ Hits        33892    33896    +4     
+ Misses      16070    16066    -4     

Impacted Files	Coverage Δ
torch/testing/_internal/expecttest.py	78.57% <0.00%> (+1.02%)	⬆️
torch/utils/_benchmark/utils/common.py	80.16% <0.00%> (+2.47%)	⬆️

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[vishwakftw]

Looks good to me, thanks!

[IvanYashchuk]

@anjali411 can we merge this?

[anjali411]

sorry for the late response, I was running behind on the reviews. LGTM. my only comment would be that we should enable autograd for qr in an follow up PR

[facebook-github-bot]

@anjali411 has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

[facebook-github-bot]

@anjali411 merged this pull request in f010df3.

[rlucas7]

sorry for the late response, I was running behind on the reviews. LGTM. my only comment would be that we should enable autograd for qr in an follow up PR

AFAICS the existing autograd for QR won't work for complex, it's missing a phase part on R matrix diagonals

[IvanYashchuk]

The derivative rule for QR was updated with #48489.