Skip to content

Make svd / svdvals fully functorch compatible#72181

Closed
lezcano wants to merge 3 commits intomasterfrom
svdvals
Closed

Make svd / svdvals fully functorch compatible#72181
lezcano wants to merge 3 commits intomasterfrom
svdvals

Conversation

@lezcano
Copy link
Copy Markdown
Collaborator

@lezcano lezcano commented Feb 2, 2022

This should (hopefully) make all the CI from functorch go green (including jvp's!) after changing VARIADIC_BDIMS_BOXED(_svd_helper); with VARIADIC_BDIMS_BOXED(_linalg_svd); and removing all the skip and xfails associated to linalg.svdvals.

Locally, there's just one test that started failing because of this, and that is test_vmapjvpall_norm_nuc_cpu_float32. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within norm_nuc as this is a composite operation.

@pytorch-bot
Copy link
Copy Markdown

pytorch-bot Bot commented Feb 2, 2022

CI Flow Status

⚛️ CI Flow

Ruleset - Version: v1
Ruleset - File: https://github.com/pytorch/pytorch/blob/1e75d995252c0ee5de13bced38d1aa185e73bd5a/.github/generated-ciflow-ruleset.json
PR ciflow labels: ciflow/default
Add ciflow labels to this PR to trigger more builds:

Workflows Labels (bold enabled) Status
Triggered Workflows
linux-binary-conda ciflow/binaries, ciflow/binaries_conda, ciflow/default ✅ triggered
linux-binary-libtorch-cxx11-abi ciflow/binaries, ciflow/binaries_libtorch, ciflow/default ✅ triggered
linux-binary-libtorch-pre-cxx11 ciflow/binaries, ciflow/binaries_libtorch, ciflow/default ✅ triggered
linux-binary-manywheel ciflow/binaries, ciflow/binaries_wheel, ciflow/default ✅ triggered
linux-bionic-py3.7-clang9 ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/noarch, ciflow/trunk, ciflow/xla ✅ triggered
linux-docs ciflow/all, ciflow/cpu, ciflow/default, ciflow/docs, ciflow/linux, ciflow/trunk ✅ triggered
linux-vulkan-bionic-py3.7-clang9 ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/trunk, ciflow/vulkan ✅ triggered
linux-xenial-cuda11.3-py3.7-gcc7 ciflow/all, ciflow/cuda, ciflow/default, ciflow/linux, ciflow/trunk ✅ triggered
linux-xenial-cuda11.3-py3.7-gcc7-bazel-test ciflow/all, ciflow/bazel, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/trunk ✅ triggered
linux-xenial-py3-clang5-mobile-build ciflow/all, ciflow/default, ciflow/linux, ciflow/mobile, ciflow/trunk ✅ triggered
linux-xenial-py3-clang5-mobile-custom-build-static ciflow/all, ciflow/default, ciflow/linux, ciflow/mobile, ciflow/trunk ✅ triggered
linux-xenial-py3.7-clang7-asan ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/sanitizers, ciflow/trunk ✅ triggered
linux-xenial-py3.7-clang7-onnx ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/onnx, ciflow/trunk ✅ triggered
linux-xenial-py3.7-gcc5.4 ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/trunk ✅ triggered
linux-xenial-py3.7-gcc7 ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/trunk ✅ triggered
linux-xenial-py3.7-gcc7-no-ops ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/trunk ✅ triggered
pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-custom-build-single ciflow/all, ciflow/android, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/trunk ✅ triggered
pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-custom-build-single-full-jit ciflow/all, ciflow/android, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/trunk ✅ triggered
win-vs2019-cpu-py3 ciflow/all, ciflow/cpu, ciflow/default, ciflow/trunk, ciflow/win ✅ triggered
win-vs2019-cuda11.3-py3 ciflow/all, ciflow/cuda, ciflow/default, ciflow/trunk, ciflow/win ✅ triggered
windows-binary-libtorch-cxx11-abi ciflow/binaries, ciflow/binaries_libtorch, ciflow/default ✅ triggered
windows-binary-libtorch-pre-cxx11 ciflow/binaries, ciflow/binaries_libtorch, ciflow/default ✅ triggered
windows-binary-wheel ciflow/binaries, ciflow/binaries_wheel, ciflow/default ✅ triggered
Skipped Workflows
caffe2-linux-xenial-py3.7-gcc5.4 ciflow/all, ciflow/cpu, ciflow/linux, ciflow/trunk 🚫 skipped
docker-builds ciflow/all, ciflow/trunk 🚫 skipped
ios-12-5-1-arm64 ciflow/all, ciflow/ios, ciflow/macos, ciflow/trunk 🚫 skipped
ios-12-5-1-arm64-coreml ciflow/all, ciflow/ios, ciflow/macos, ciflow/trunk 🚫 skipped
ios-12-5-1-arm64-custom-ops ciflow/all, ciflow/ios, ciflow/macos, ciflow/trunk 🚫 skipped
ios-12-5-1-arm64-full-jit ciflow/all, ciflow/ios, ciflow/macos, ciflow/trunk 🚫 skipped
ios-12-5-1-arm64-metal ciflow/all, ciflow/ios, ciflow/macos, ciflow/trunk 🚫 skipped
ios-12-5-1-x86-64 ciflow/all, ciflow/ios, ciflow/macos, ciflow/trunk 🚫 skipped
ios-12-5-1-x86-64-coreml ciflow/all, ciflow/ios, ciflow/macos, ciflow/trunk 🚫 skipped
ios-12-5-1-x86-64-full-jit ciflow/all, ciflow/ios, ciflow/macos, ciflow/trunk 🚫 skipped
libtorch-linux-xenial-cuda10.2-py3.7-gcc7 ciflow/all, ciflow/cuda, ciflow/libtorch, ciflow/linux, ciflow/trunk 🚫 skipped
libtorch-linux-xenial-cuda11.3-py3.7-gcc7 ciflow/all, ciflow/cuda, ciflow/libtorch, ciflow/linux, ciflow/trunk 🚫 skipped
linux-bionic-cuda10.2-py3.9-gcc7 ciflow/all, ciflow/cuda, ciflow/linux, ciflow/slow, ciflow/trunk 🚫 skipped
linux-bionic-rocm4.5-py3.7 ciflow/linux, ciflow/rocm 🚫 skipped
linux-docs-push ciflow/all, ciflow/cpu, ciflow/linux, ciflow/scheduled 🚫 skipped
linux-xenial-cuda11.3-py3.7-gcc7-no-ops ciflow/all, ciflow/cuda, ciflow/linux, ciflow/trunk 🚫 skipped
macos-10-15-py3-arm64 ciflow/all, ciflow/macos, ciflow/trunk 🚫 skipped
macos-10-15-py3-lite-interpreter-x86-64 ciflow/all, ciflow/macos, ciflow/trunk 🚫 skipped
macos-11-py3-x86-64 ciflow/all, ciflow/macos, ciflow/trunk 🚫 skipped
parallelnative-linux-xenial-py3.7-gcc5.4 ciflow/all, ciflow/cpu, ciflow/linux, ciflow/trunk 🚫 skipped
periodic-libtorch-linux-bionic-cuda11.5-py3.7-gcc7 ciflow/all, ciflow/cuda, ciflow/libtorch, ciflow/linux, ciflow/scheduled 🚫 skipped
periodic-libtorch-linux-xenial-cuda11.1-py3.7-gcc7 ciflow/all, ciflow/cuda, ciflow/libtorch, ciflow/linux, ciflow/scheduled 🚫 skipped
periodic-linux-bionic-cuda11.5-py3.7-gcc7 ciflow/all, ciflow/cuda, ciflow/linux, ciflow/scheduled 🚫 skipped
periodic-linux-xenial-cuda10.2-py3-gcc7-slow-gradcheck ciflow/all, ciflow/cuda, ciflow/linux, ciflow/scheduled, ciflow/slow, ciflow/slow-gradcheck 🚫 skipped
periodic-linux-xenial-cuda11.1-py3.7-gcc7-debug ciflow/all, ciflow/cuda, ciflow/linux, ciflow/scheduled 🚫 skipped
periodic-win-vs2019-cuda11.1-py3 ciflow/all, ciflow/cuda, ciflow/scheduled, ciflow/win 🚫 skipped
periodic-win-vs2019-cuda11.5-py3 ciflow/all, ciflow/cuda, ciflow/scheduled, ciflow/win 🚫 skipped
pytorch-linux-xenial-py3-clang5-android-ndk-r19c-build ciflow/all, ciflow/android, ciflow/cpu, ciflow/linux, ciflow/trunk 🚫 skipped

@facebook-github-bot
Copy link
Copy Markdown
Contributor

facebook-github-bot commented Feb 2, 2022

🔗 Helpful links

💊 CI failures summary and remediations

As of commit a914e99 (more details on the Dr. CI page):


💚 💚 Looks good so far! There are no failures yet. 💚 💚


This comment was automatically generated by Dr. CI (expand for details).

Please report bugs/suggestions to the (internal) Dr. CI Users group.

Click here to manually regenerate this comment.

Comment thread aten/src/ATen/native/BatchLinearAlgebra.cpp
Copy link
Copy Markdown
Contributor

@zou3519 zou3519 left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM. I ran the functorch tests locally to confirm and saw the same thing as you did, @lezcano. Since that test (test_vmapjvpall_norm_nuc_cpu_float32) is not a regression, we don't need to worry about fixing it soon.

Once we have actual Composite Compliance testing for backward passes, we'll be able to add a lot of in-place operations back into the backward pass and have confidence that it won't break functorch :)

@facebook-github-bot
Copy link
Copy Markdown
Contributor

@zou3519 has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

facebook-github-bot pushed a commit that referenced this pull request Feb 3, 2022
Summary:
This should (hopefully) make all the CI from `functorch` go green (including jvp's!) after changing `VARIADIC_BDIMS_BOXED(_svd_helper);` with `VARIADIC_BDIMS_BOXED(_linalg_svd);` and removing all the skip and xfails associated to `linalg.svdvals`.

Locally, there's just one test that started failing because of this, and that is `test_vmapjvpall_norm_nuc_cpu_float32`. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within `norm_nuc` as this is a composite operation.

Pull Request resolved: #72181

Reviewed By: ngimel

Differential Revision: D33952744

Pulled By: zou3519

fbshipit-source-id: 2a2510d97eed4a0bfc25615264ddd36e38856efe
pytorchmergebot pushed a commit that referenced this pull request Feb 3, 2022
Summary:
This should (hopefully) make all the CI from `functorch` go green (including jvp's!) after changing `VARIADIC_BDIMS_BOXED(_svd_helper);` with `VARIADIC_BDIMS_BOXED(_linalg_svd);` and removing all the skip and xfails associated to `linalg.svdvals`.

Locally, there's just one test that started failing because of this, and that is `test_vmapjvpall_norm_nuc_cpu_float32`. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within `norm_nuc` as this is a composite operation.

Pull Request resolved: #72181

Reviewed By: ngimel

Differential Revision: D33952744

Pulled By: zou3519

fbshipit-source-id: 2a2510d97eed4a0bfc25615264ddd36e38856efe
(cherry picked from commit 5805fa1)
@github-actions
Copy link
Copy Markdown
Contributor

github-actions Bot commented Feb 3, 2022

Hey Lezcano.
You've committed this PR, but it does not have both a 'release notes: ...' and 'topics: ...' label. Please add one of each to the PR. The 'release notes: ...' label should represent the part of PyTorch that this PR changes (fx, autograd, distributed, etc) and the 'topics: ...' label should represent the kind of PR it is (not user facing, new feature, bug fix, perf improvement, etc). The list of valid labels can be found here for the 'release notes: ...' and here for the 'topics: ...'.
For changes that are 'topic: not user facing' there is no need for a release notes label.

cyyever pushed a commit to cyyever/pytorch_private that referenced this pull request Feb 3, 2022
Summary:
This should (hopefully) make all the CI from `functorch` go green (including jvp's!) after changing `VARIADIC_BDIMS_BOXED(_svd_helper);` with `VARIADIC_BDIMS_BOXED(_linalg_svd);` and removing all the skip and xfails associated to `linalg.svdvals`.

Locally, there's just one test that started failing because of this, and that is `test_vmapjvpall_norm_nuc_cpu_float32`. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within `norm_nuc` as this is a composite operation.

Pull Request resolved: pytorch/pytorch#72181

Reviewed By: ngimel

Differential Revision: D33952744

Pulled By: zou3519

fbshipit-source-id: 2a2510d97eed4a0bfc25615264ddd36e38856efe
(cherry picked from commit 5805fa107c3a91c58f8ecc9778cfc87aa7f64233)
cyyever pushed a commit to cyyever/pytorch_private that referenced this pull request Feb 3, 2022
Summary:
This should (hopefully) make all the CI from `functorch` go green (including jvp's!) after changing `VARIADIC_BDIMS_BOXED(_svd_helper);` with `VARIADIC_BDIMS_BOXED(_linalg_svd);` and removing all the skip and xfails associated to `linalg.svdvals`.

Locally, there's just one test that started failing because of this, and that is `test_vmapjvpall_norm_nuc_cpu_float32`. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within `norm_nuc` as this is a composite operation.

Pull Request resolved: pytorch/pytorch#72181

Reviewed By: ngimel

Differential Revision: D33952744

Pulled By: zou3519

fbshipit-source-id: 2a2510d97eed4a0bfc25615264ddd36e38856efe
(cherry picked from commit 5805fa107c3a91c58f8ecc9778cfc87aa7f64233)
@lezcano lezcano added module: autograd Related to torch.autograd, and the autograd engine in general module: linear algebra Issues related to specialized linear algebra operations in PyTorch; includes matrix multiply matmul labels Feb 3, 2022
zou3519 pushed a commit that referenced this pull request Feb 3, 2022
Summary:
This should (hopefully) make all the CI from `functorch` go green (including jvp's!) after changing `VARIADIC_BDIMS_BOXED(_svd_helper);` with `VARIADIC_BDIMS_BOXED(_linalg_svd);` and removing all the skip and xfails associated to `linalg.svdvals`.

Locally, there's just one test that started failing because of this, and that is `test_vmapjvpall_norm_nuc_cpu_float32`. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within `norm_nuc` as this is a composite operation.

Pull Request resolved: #72181

Reviewed By: ngimel

Differential Revision: D33952744

Pulled By: zou3519

fbshipit-source-id: 2a2510d97eed4a0bfc25615264ddd36e38856efe
(cherry picked from commit 5805fa1)
atalman added a commit that referenced this pull request Feb 4, 2022
* release 1.11 Install torch from test channel, Pin builder and xla repo (#72217)

* Make svd / svdvals fully functorch compatible (#72181)

Summary:
This should (hopefully) make all the CI from `functorch` go green (including jvp's!) after changing `VARIADIC_BDIMS_BOXED(_svd_helper);` with `VARIADIC_BDIMS_BOXED(_linalg_svd);` and removing all the skip and xfails associated to `linalg.svdvals`.

Locally, there's just one test that started failing because of this, and that is `test_vmapjvpall_norm_nuc_cpu_float32`. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within `norm_nuc` as this is a composite operation.

Pull Request resolved: #72181

Reviewed By: ngimel

Differential Revision: D33952744

Pulled By: zou3519

fbshipit-source-id: 2a2510d97eed4a0bfc25615264ddd36e38856efe
(cherry picked from commit 5805fa1)

Co-authored-by: Andrey Talman <atalman@fb.com>
Co-authored-by: lezcano <lezcano-93@hotmail.com>
cyyever pushed a commit to cyyever/pytorch_private that referenced this pull request Feb 9, 2022
Summary:
This should (hopefully) make all the CI from `functorch` go green (including jvp's!) after changing `VARIADIC_BDIMS_BOXED(_svd_helper);` with `VARIADIC_BDIMS_BOXED(_linalg_svd);` and removing all the skip and xfails associated to `linalg.svdvals`.

Locally, there's just one test that started failing because of this, and that is `test_vmapjvpall_norm_nuc_cpu_float32`. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within `norm_nuc` as this is a composite operation.

Pull Request resolved: pytorch/pytorch#72181

Reviewed By: ngimel

Differential Revision: D33952744

Pulled By: zou3519

fbshipit-source-id: 2a2510d97eed4a0bfc25615264ddd36e38856efe
(cherry picked from commit 5805fa107c3a91c58f8ecc9778cfc87aa7f64233)
cyyever pushed a commit to cyyever/pytorch_private that referenced this pull request Feb 9, 2022
Summary:
This should (hopefully) make all the CI from `functorch` go green (including jvp's!) after changing `VARIADIC_BDIMS_BOXED(_svd_helper);` with `VARIADIC_BDIMS_BOXED(_linalg_svd);` and removing all the skip and xfails associated to `linalg.svdvals`.

Locally, there's just one test that started failing because of this, and that is `test_vmapjvpall_norm_nuc_cpu_float32`. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within `norm_nuc` as this is a composite operation.

Pull Request resolved: pytorch/pytorch#72181

Reviewed By: ngimel

Differential Revision: D33952744

Pulled By: zou3519

fbshipit-source-id: 2a2510d97eed4a0bfc25615264ddd36e38856efe
(cherry picked from commit 5805fa107c3a91c58f8ecc9778cfc87aa7f64233)
@github-actions github-actions Bot deleted the svdvals branch February 14, 2024 02:14
laurentdupin pushed a commit to laurentdupin/pytorch that referenced this pull request Apr 25, 2026
Summary:
This should (hopefully) make all the CI from `functorch` go green (including jvp's!) after changing `VARIADIC_BDIMS_BOXED(_svd_helper);` with `VARIADIC_BDIMS_BOXED(_linalg_svd);` and removing all the skip and xfails associated to `linalg.svdvals`.

Locally, there's just one test that started failing because of this, and that is `test_vmapjvpall_norm_nuc_cpu_float32`. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within `norm_nuc` as this is a composite operation.

Pull Request resolved: pytorch#72181

Reviewed By: ngimel

Differential Revision: D33952744

Pulled By: zou3519

fbshipit-source-id: 2a2510d97eed4a0bfc25615264ddd36e38856efe
(cherry picked from commit 5805fa1)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

cla signed module: autograd Related to torch.autograd, and the autograd engine in general module: linear algebra Issues related to specialized linear algebra operations in PyTorch; includes matrix multiply matmul open source

Projects

None yet

Development

Successfully merging this pull request may close these issues.

5 participants