-
Notifications
You must be signed in to change notification settings - Fork 3k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Add attrProto.release_s interface #22977
Conversation
Hi @jywu-msft , Can you please review this PR? |
/azp run Linux CPU CI Pipeline, Linux CPU Minimal Build E2E CI Pipeline, Linux GPU CI Pipeline, Linux GPU TensorRT CI Pipeline, Linux OpenVINO CI Pipeline, MacOS CI Pipeline, ONNX Runtime Web CI Pipeline, onnxruntime-binary-size-checks-ci-pipeline, Linux QNN CI Pipeline |
/azp run Windows ARM64 QNN CI Pipeline, Windows CPU CI Pipeline, Windows GPU TensorRT CI Pipeline, Windows x64 QNN CI Pipeline, orttraining-linux-ci-pipeline, orttraining-linux-gpu-ci-pipeline |
Azure Pipelines successfully started running 9 pipeline(s). |
Azure Pipelines successfully started running 4 pipeline(s). |
/azp run Big Models, Linux Android Emulator QNN CI Pipeline, Windows GPU CUDA CI Pipeline, Windows GPU DML CI Pipeline, Windows GPU Doc Gen CI Pipeline |
Azure Pipelines successfully started running 5 pipeline(s). |
it's failing lint checks. Warning (CLANGFORMAT) format
[2024-12-05T17:58:49Z DEBUG lintrunner::persistent_data] Writing run info to /home/cloudtest/.local/share/lintrunner/90a885e688310be9e42a550e10042c91e89bfa0b1be8a7cf0128dbb937830178/runs/2024-12-05T17-57-19.950Z_80015b8980a08df67e03e2596acef487771aed65e28b72d8c60a6140007f8e7c You can reproduce these results locally by using |
|
/azp run Linux CPU CI Pipeline, Linux CPU Minimal Build E2E CI Pipeline, Linux GPU CI Pipeline, Linux GPU TensorRT CI Pipeline, Linux OpenVINO CI Pipeline, MacOS CI Pipeline, ONNX Runtime Web CI Pipeline, onnxruntime-binary-size-checks-ci-pipeline, Linux QNN CI Pipeline |
/azp run Windows ARM64 QNN CI Pipeline, Windows CPU CI Pipeline, Windows GPU TensorRT CI Pipeline, Windows x64 QNN CI Pipeline, orttraining-linux-ci-pipeline, orttraining-linux-gpu-ci-pipeline |
/azp run Big Models, Linux Android Emulator QNN CI Pipeline, Windows GPU CUDA CI Pipeline, Windows GPU DML CI Pipeline, Windows GPU Doc Gen CI Pipeline |
Azure Pipelines successfully started running 4 pipeline(s). |
Azure Pipelines successfully started running 9 pipeline(s). |
Azure Pipelines successfully started running 5 pipeline(s). |
### Description Add AttributeProto.release_s interface, which is used to obtain the string in the attribute using move semantics instead of copying it ### Motivation and Context The ep_context node stores a lot of information in attributes, which may cause the memory usage to increase. Use this interface to avoid memory waste --------- Co-authored-by: GenMing Zhong <[email protected]> Co-authored-by: genmingz <[email protected]>
### Description Add AttributeProto.release_s interface, which is used to obtain the string in the attribute using move semantics instead of copying it ### Motivation and Context The ep_context node stores a lot of information in attributes, which may cause the memory usage to increase. Use this interface to avoid memory waste --------- Co-authored-by: GenMing Zhong <[email protected]> Co-authored-by: genmingz <[email protected]>
### Description Add AttributeProto.release_s interface, which is used to obtain the string in the attribute using move semantics instead of copying it ### Motivation and Context The ep_context node stores a lot of information in attributes, which may cause the memory usage to increase. Use this interface to avoid memory waste --------- Co-authored-by: GenMing Zhong <[email protected]> Co-authored-by: genmingz <[email protected]>
Description
Add AttributeProto.release_s interface, which is used to obtain the string in the attribute using move semantics instead of copying it
Motivation and Context
The ep_context node stores a lot of information in attributes, which may cause the memory usage to increase. Use this interface to avoid memory waste