[PyTorch Vulkan] fix bug of aten::cat for concatenation of 3D tensors at channel dim with channels as multiple of 4
#103718
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/103718
Note: Links to docs will display an error until the docs builds have been completed. ✅ 4 Unrelated FailuresAs of commit ee6d0b0: BROKEN TRUNK - The following job failed but were present on the merge base 15eed5b:👉 Rebase onto the `viable/strict` branch to avoid these failures
UNSTABLE - The following jobs failed but were likely due to flakiness present on trunk and has been marked as unstable:
This comment was automatically generated by Dr. CI and updates every 15 minutes. |
pytorch-bot
bot
added
ciflow/periodic
|
This pull request was exported from Phabricator. Differential Revision: D46755034 |
SS-JIA
approved these changes
Jun 16, 2023
copyrightly
force-pushed
the
export-D46755034
branch
from
91e5c5f
to
e1bf5bf
Compare
copyrightly
added a commit
to copyrightly/pytorch
that referenced
this pull request
Jun 16, 2023
…rs at channel dim with channels as multiple of 4 (pytorch#103718) Summary: Pull Request resolved: pytorch#103718 The original `cat_feature_mult4ch` assumes input tensors are of 4d and use `tensor.sizes()[1]` to obtain the channel info of the tensor. This will cause bugs when the input tensors are of 3D. We generalize `cat_feature_mult4ch` to make it cover both 3D and 4D. Test Plan: Test for 3D tensors with channels as multiple of 4 is show below. Full test result is in P771032677. ``` (base) luwei@luwei-mbp fbsource % buck run --target-platforms ovr_config//platform/macos:arm64-fbsource //xplat/caffe2:pt_vulkan_api_test_binAppleMac\#macosx-arm64 -c pt.vulkan_full_precision=1 -- --gtest_filter="*cat_3d_dim0_mult4ch_success*" Building: finished in 0.1 sec (100%) 263/2812 jobs, 0/2812 updated Total time: 0.1 sec BUILD SUCCEEDED Running main() from xplat/third-party/gmock/googletest-1.12.1/googletest/src/gtest_main.cc Note: Google Test filter = *cat_3d_dim0_mult4ch_success* [==========] Running 1 test from 1 test suite. [----------] Global test environment set-up. [----------] 1 test from VulkanAPITest [ RUN ] VulkanAPITest.cat_3d_dim0_mult4ch_success [ OK ] VulkanAPITest.cat_3d_dim0_mult4ch_success (129 ms) [----------] 1 test from VulkanAPITest (129 ms total) [----------] Global test environment tear-down [==========] 1 test from 1 test suite ran. (129 ms total) [ PASSED ] 1 test. ``` Reviewed By: SS-JIA Differential Revision: D46755034 fbshipit-source-id: c6db3f9da452343bb9582e0712982063580a67a5
|
This pull request was exported from Phabricator. Differential Revision: D46755034 |
…rs at channel dim with channels as multiple of 4 (pytorch#103718) Summary: Pull Request resolved: pytorch#103718 The original `cat_feature_mult4ch` assumes input tensors are of 4d and use `tensor.sizes()[1]` to obtain the channel info of the tensor. This will cause bugs when the input tensors are of 3D. We generalize `cat_feature_mult4ch` to make it cover both 3D and 4D. Test Plan: Test for 3D tensors with channels as multiple of 4 is show below. Full test result is in P771032677. ``` (base) luwei@luwei-mbp fbsource % buck run --target-platforms ovr_config//platform/macos:arm64-fbsource //xplat/caffe2:pt_vulkan_api_test_binAppleMac\#macosx-arm64 -c pt.vulkan_full_precision=1 -- --gtest_filter="*cat_3d_dim0_mult4ch_success*" Building: finished in 0.1 sec (100%) 263/2812 jobs, 0/2812 updated Total time: 0.1 sec BUILD SUCCEEDED Running main() from xplat/third-party/gmock/googletest-1.12.1/googletest/src/gtest_main.cc Note: Google Test filter = *cat_3d_dim0_mult4ch_success* [==========] Running 1 test from 1 test suite. [----------] Global test environment set-up. [----------] 1 test from VulkanAPITest [ RUN ] VulkanAPITest.cat_3d_dim0_mult4ch_success [ OK ] VulkanAPITest.cat_3d_dim0_mult4ch_success (129 ms) [----------] 1 test from VulkanAPITest (129 ms total) [----------] Global test environment tear-down [==========] 1 test from 1 test suite ran. (129 ms total) [ PASSED ] 1 test. ``` Reviewed By: SS-JIA Differential Revision: D46755034 fbshipit-source-id: 112216ff29bbe50ef7e8723782c7d0322beddc63
copyrightly
force-pushed
the
export-D46755034
branch
from
e1bf5bf
to
ee6d0b0
Compare
|
This pull request was exported from Phabricator. Differential Revision: D46755034 |
|
@pytorchbot merge (Initiating merge automatically since Phabricator Diff has merged) |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary: The original
cat_feature_mult4chassumes input tensors are of 4d and usetensor.sizes()[1]to obtain the channel info of the tensor. This will cause bugs when the input tensors are of 3D. We generalizecat_feature_mult4chto make it cover both 3D and 4D.Test Plan:
Test for 3D tensors with channels as multiple of 4 is show below. Full test result is in P771032677.
Reviewed By: SS-JIA
Differential Revision: D46755034