fractional_max_pool2d_backward: port to structured kernel #68245

francescocastelli · 2021-11-12T11:33:06Z

Ported to structured kernel the fractional_max_pool2d_backward.

pytorch-probot · 2021-11-12T11:33:08Z

CI Flow Status

⚛️ CI Flow

Ruleset - Version: v1
Ruleset - File: https://github.com/francescocastelli/pytorch/blob/01617d3d15bb397c1c71f3cbeb30922c8a46b096/.github/generated-ciflow-ruleset.json
PR ciflow labels: ciflow/default

Workflows	Labels (bold enabled)	Status
Triggered Workflows
linux-bionic-py3.6-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-py3.6-clang9	`ciflow/all`, `ciflow/cpu`, `ciflow/default`, `ciflow/linux`, `ciflow/trunk`, `ciflow/vulkan`	✅ triggered
linux-xenial-cuda11.3-py3.6-gcc7	`ciflow/all`, `ciflow/cuda`, `ciflow/default`, `ciflow/linux`, `ciflow/trunk`	✅ triggered
linux-xenial-cuda11.3-py3.6-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-py3.6-clang7-asan	`ciflow/all`, `ciflow/cpu`, `ciflow/default`, `ciflow/linux`, `ciflow/sanitizers`, `ciflow/trunk`	✅ triggered
linux-xenial-py3.6-clang7-onnx	`ciflow/all`, `ciflow/cpu`, `ciflow/default`, `ciflow/linux`, `ciflow/onnx`, `ciflow/trunk`	✅ triggered
linux-xenial-py3.6-gcc5.4	`ciflow/all`, `ciflow/cpu`, `ciflow/default`, `ciflow/linux`, `ciflow/trunk`	✅ triggered
linux-xenial-py3.6-gcc7	`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
Skipped Workflows
caffe2-linux-xenial-py3.6-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-py3.6-gcc7	`ciflow/all`, `ciflow/cuda`, `ciflow/libtorch`, `ciflow/linux`, `ciflow/trunk`	🚫 skipped
libtorch-linux-xenial-cuda11.3-py3.6-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-docs-push	`ciflow/all`, `ciflow/cpu`, `ciflow/linux`, `ciflow/scheduled`	🚫 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-py3.6-gcc5.4	`ciflow/all`, `ciflow/cpu`, `ciflow/linux`, `ciflow/trunk`	🚫 skipped
periodic-libtorch-linux-bionic-cuda11.5-py3.6-gcc7	`ciflow/all`, `ciflow/cuda`, `ciflow/libtorch`, `ciflow/linux`, `ciflow/scheduled`	🚫 skipped
periodic-libtorch-linux-xenial-cuda11.1-py3.6-gcc7	`ciflow/all`, `ciflow/cuda`, `ciflow/libtorch`, `ciflow/linux`, `ciflow/scheduled`	🚫 skipped
periodic-linux-bionic-cuda11.5-py3.6-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-py3.6-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

You can add a comment to the PR and tag @pytorchbot with the following commands:

# ciflow rerun, "ciflow/default" will always be added automatically
@pytorchbot ciflow rerun

# ciflow rerun with additional labels "-l <ciflow/label_name>", which is equivalent to adding these labels manually and trigger the rerun
@pytorchbot ciflow rerun -l ciflow/scheduled -l ciflow/slow

For more information, please take a look at the CI Flow Wiki.

facebook-github-bot · 2021-11-12T11:33:11Z

🔗 Helpful links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/68245
📄 Preview docs built from this PR
📄 Preview C++ docs built from this PR
🔧 Opt-in to CIFlow to control what jobs run on your PRs

💊 CI failures summary and remediations

As of commit 01617d3 (more details on the Dr. CI page):

1/2 failures introduced in this PR
1/2 broken upstream at merge base 911d527 since Dec 22

🕵️ 1 new failure recognized by patterns

The following CI failures do not appear to be due to upstream breakages:

linux-xenial-cuda11.3-py3.6-gcc7-bazel-test / build-and-test (1/1)

Step: "Build" (full log | diagnosis details | 🔁 rerun)

2021-12-24T21:52:05.9388757Z �[36;1m echo "ERR...t available for the merge-base of your branch"�[0m

2021-12-24T21:52:05.9383148Z �[36;1mfi�[0m
2021-12-24T21:52:05.9383585Z �[36;1m# Covers the case where a previous tag doesn't exist for the tree�[0m
2021-12-24T21:52:05.9384251Z �[36;1m# this is only really applicable on trees that don't have `.circleci/docker` at its merge base, i.e. nightly�[0m
2021-12-24T21:52:05.9384896Z �[36;1mif ! git rev-parse "$MERGE_BASE:.circleci/docker"; then�[0m
2021-12-24T21:52:05.9385584Z �[36;1m  echo "Directory '.circleci/docker' not found in commit $MERGE_BASE, you should probably rebase onto a more recent commit"�[0m
2021-12-24T21:52:05.9386123Z �[36;1m  exit 1�[0m
2021-12-24T21:52:05.9386392Z �[36;1mfi�[0m
2021-12-24T21:52:05.9386810Z �[36;1mPREVIOUS_DOCKER_TAG=$(git rev-parse "$MERGE_BASE:.circleci/docker")�[0m
2021-12-24T21:52:05.9387536Z �[36;1m# If no image exists but the hash is the same as the previous hash then we should error out here�[0m
2021-12-24T21:52:05.9388120Z �[36;1mif [[ "${PREVIOUS_DOCKER_TAG}" = "${DOCKER_TAG}" ]]; then�[0m
2021-12-24T21:52:05.9388757Z �[36;1m  echo "ERROR: Something has gone wrong and the previous image isn't available for the merge-base of your branch"�[0m
2021-12-24T21:52:05.9389464Z �[36;1m  echo "       contact the PyTorch team to restore the original images"�[0m
2021-12-24T21:52:05.9389898Z �[36;1m  exit 1�[0m
2021-12-24T21:52:05.9390155Z �[36;1mfi�[0m
2021-12-24T21:52:05.9390509Z �[36;1mecho ::set-output name=rebuild::yes�[0m
2021-12-24T21:52:05.9400436Z shell: /usr/bin/bash -e {0}
2021-12-24T21:52:05.9400743Z env:
2021-12-24T21:52:05.9401357Z   BUILD_ENVIRONMENT: linux-xenial-cuda11.3-py3.6-gcc7-bazel-test
2021-12-24T21:52:05.9402602Z   DOCKER_IMAGE_BASE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7
2021-12-24T21:52:05.9403733Z   SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2
2021-12-24T21:52:05.9404588Z   XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla

🚧 1 ongoing upstream failure:

These were probably caused by upstream breakages that are not fixed yet.

linux-bionic-py3.6-clang9 / test (xla, 1, 1, linux.2xlarge) since Dec 22 (b15212c)
- 🔁 rerun

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.

francescocastelli · 2021-12-26T11:00:54Z

@bdhirsh Hi, could you take a look at this, please?

bdhirsh

Looks good to me. Thanks for contributing!

facebook-github-bot · 2022-01-04T15:59:08Z

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

Summary: Ported to structured kernel the fractional_max_pool2d_backward. Ref #55070 Pull Request resolved: #68245 Reviewed By: jbschlosser Differential Revision: D33405521 Pulled By: bdhirsh fbshipit-source-id: 4930e870d4025485317208df751bc3721ecdb7eb

francescocastelli requested a review from ezyang as a code owner November 12, 2021 11:33

pytorch-probot bot added the ciflow/default label Nov 12, 2021

facebook-github-bot added the cla signed label Nov 12, 2021

pytorchbot added the open source label Nov 12, 2021

saketh-are added the triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module label Nov 12, 2021

francescocastelli marked this pull request as draft December 9, 2021 14:22

francescocastelli force-pushed the fractional_maxpool2d_backward branch from 4566c19 to 5c12924 Compare December 9, 2021 14:49

francescocastelli force-pushed the fractional_maxpool2d_backward branch from 9cc8f49 to 7ac9c61 Compare December 21, 2021 16:45

francescocastelli added 10 commits December 24, 2021 18:59

ported fractional max pool 2d backward to structured kernel

0777927

fixed cuda kernel

acd6827

re-introduced resize in cuda kernel

465c530

check gradoutput numel instead of gradInput

fab8de1

fixed cuda kernel reshape

3b04a15

check gradInput

b3e82ac

fixed cuda kernel reshape

a09c154

fixed cuda kernel reshape

eaa5bf8

go back to previous cuda implementation

d2c4a49

change set ouput to handle ndim=3

e4ceac1

francescocastelli force-pushed the fractional_maxpool2d_backward branch from 22c6926 to e4ceac1 Compare December 24, 2021 17:59

francescocastelli added 2 commits December 24, 2021 20:02

fixed shapes

c23842e

fixed cuda parameters order

01617d3

francescocastelli marked this pull request as ready for review December 25, 2021 00:57

bdhirsh approved these changes Jan 4, 2022

View reviewed changes

facebook-github-bot closed this in a60adc7 Jan 4, 2022

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

fractional_max_pool2d_backward: port to structured kernel #68245

fractional_max_pool2d_backward: port to structured kernel #68245

francescocastelli commented Nov 12, 2021

pytorch-probot bot commented Nov 12, 2021 •

edited

Loading

⚛️ CI Flow

facebook-github-bot commented Nov 12, 2021 •

edited

Loading

francescocastelli commented Dec 26, 2021

bdhirsh left a comment

facebook-github-bot commented Jan 4, 2022

fractional_max_pool2d_backward: port to structured kernel #68245

fractional_max_pool2d_backward: port to structured kernel #68245

Conversation

francescocastelli commented Nov 12, 2021

pytorch-probot bot commented Nov 12, 2021 • edited Loading

⚛️ CI Flow

facebook-github-bot commented Nov 12, 2021 • edited Loading

🔗 Helpful links

💊 CI failures summary and remediations

🕵️ 1 new failure recognized by patterns

linux-xenial-cuda11.3-py3.6-gcc7-bazel-test / build-and-test (1/1)

🚧 1 ongoing upstream failure:

francescocastelli commented Dec 26, 2021

bdhirsh left a comment

Choose a reason for hiding this comment

facebook-github-bot commented Jan 4, 2022

pytorch-probot bot commented Nov 12, 2021 •

edited

Loading

facebook-github-bot commented Nov 12, 2021 •

edited

Loading