resolve conjugate bit in torch.testing.assert_close
#60522
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💊 CI failures summary and remediationsAs of commit a7e1b72 (more details on the Dr. CI page and at hud.pytorch.org/pr/60522):
🕵️ 3 new failures recognized by patternsThe following CI failures do not appear to be due to upstream breakages:
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| Job | Step | Action |
|---|---|---|
 pytorch_doc_test |
Doc test | 🔁 rerun |
🚧 1 fixed upstream failure:
These were probably caused by upstream breakages that were already fixed.
Please rebase on the viable/strict branch (expand for instructions)
If your commit is older than viable/strict, run these commands:
git fetch https://github.com/pytorch/pytorch viable/strict
git rebase FETCH_HEAD
- pytorch_xla_linux_bionic_py3_6_clang9_test from Jun 23 until Jun 24 (80f40b1 - b7298f4)
ci.pytorch.org: 1 failed
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pmeier
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module: complex
mruberry
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Jun 24, 2021
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Good catch, @pmeier
@anjali411 -- does this look OK to you, too?
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@mruberry has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
# Conflicts: # torch/testing/_asserts.py
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yup looks good! although this won't be needed after #56058 is merged! |
anjali411
approved these changes
Jun 24, 2021
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@mruberry has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
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anjali411
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Jul 8, 2021
User facing changes: 1. Adds a negative bit and corresponding new API (`is_neg()`,`resolve_neg()`) 2. `tensor.conj().imag` now returns a floating point tensor with neg bit set to 1 instead of a tensor with no notion of negative bit. Note that imag is still a view and all the view properties still hold for imag. Non user facing changes: 1. Added a new Negative dispatch key and a backend fallback to handle it 2. Updated copy kernel to handle negative bit 3. Merged conjugate and negative bit fallback kernel 4. fixed #60478 (caused due to #54987) Testing: 1. Added a new OpInfo based test `test_neg_view` (verifies that out-of-place and in-place operations work correctly for all operations when the input is a neg view tensor by checking the result against an actually negated tensor, verifies that autograd returns the same output for both neg view and actually negated tensors as well as it works fine when grad_out is a neg view). 2. Added a new test class containing `test_conj_view`, `test_neg_view`. TODO: follow up on #60522 (comment) Differential Revision: [](https://our.internmc.facebook.com/intern/diff/) [ghstack-poisoned]
anjali411
added a commit
that referenced
this pull request
Jul 8, 2021
User facing changes: 1. Adds a negative bit and corresponding new API (`is_neg()`,`resolve_neg()`) 2. `tensor.conj().imag` now returns a floating point tensor with neg bit set to 1 instead of a tensor with no notion of negative bit. Note that imag is still a view and all the view properties still hold for imag. Non user facing changes: 1. Added a new Negative dispatch key and a backend fallback to handle it 2. Updated copy kernel to handle negative bit 3. Merged conjugate and negative bit fallback kernel 4. fixed #60478 (caused due to #54987) Testing: 1. Added a new OpInfo based test `test_neg_view` (verifies that out-of-place and in-place operations work correctly for all operations when the input is a neg view tensor by checking the result against an actually negated tensor, verifies that autograd returns the same output for both neg view and actually negated tensors as well as it works fine when grad_out is a neg view). 2. Added a new test class containing `test_conj_view`, `test_neg_view`. TODO: follow up on #60522 (comment) Differential Revision: [](https://our.internmc.facebook.com/intern/diff/) [ghstack-poisoned]
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We need to resolve the conjugate bit for complex tensors, because otherwise we may not be able to access the imaginary component: