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[QNN-EP] Translate FP-to-Bool Cast by NotEqual. #24466
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[QNN-EP] Translate FP-to-Bool Cast by NotEqual. #24466
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@microsoft-github-policy-service agree company="Qualcomm" |
/azp run Linux QNN CI Pipeline,Windows x64 QNN CI Pipeline,Windows ARM64 QNN CI Pipeline,Linux Android Emulator QNN CI Pipeline |
Azure Pipelines successfully started running 4 pipeline(s). |
please fix the Windows build error and code format issue |
HTP currently does not support FP-to-Bool Cast due to some limitations. To unblock CLIP models, replace such Cast with NotEqual to achieve the same functionality. Test: Add UT testcase for FP/FP16 to Bool.
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/azp run Linux QNN CI Pipeline, Win_TRT_Minimal_CUDA_Test_CI, Windows ARM64 QNN CI Pipeline, Windows GPU Doc Gen CI Pipeline, Windows x64 QNN CI Pipeline |
Azure Pipelines successfully started running 5 pipeline(s). |
/azp run web_Debug / build_onnxruntime_web, web_Release / build_onnxruntime_web |
No pipelines are associated with this pull request. |
/azp run "web_Debug / build_onnxruntime_web", "web_Release / build_onnxruntime_web" |
No pipelines are associated with this pull request. |
Hi @vraspar FYI, to be cherry-picked for ORT 1.22.0 |
### Description Removes unnecessary std::move on an r-value expression. This caused a compiler warning/error in the Linux Android QNN pipeline. ### Motivation and Context Introduced by PR: #24466
### Description <!-- Describe your changes. --> For QNN-EP, build FP-to-Bool Cast into NotEqual. ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. --> HTP currently does not support FP-to-Bool Cast due to some limitations. To unblock CLIP models, replace such Cast with NotEqual to achieve the same functionality. Co-authored-by: minfhong-quic <minfhong-quic@quicinc.com> Signed-off-by: bfilipek <bartlomiej.filipek@intel.com>
…#24493) ### Description Removes unnecessary std::move on an r-value expression. This caused a compiler warning/error in the Linux Android QNN pipeline. ### Motivation and Context Introduced by PR: microsoft#24466 Signed-off-by: bfilipek <bartlomiej.filipek@intel.com>
### Description <!-- Describe your changes. --> For QNN-EP, build FP-to-Bool Cast into NotEqual. ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. --> HTP currently does not support FP-to-Bool Cast due to some limitations. To unblock CLIP models, replace such Cast with NotEqual to achieve the same functionality. Co-authored-by: minfhong-quic <minfhong-quic@quicinc.com>
### Description Removes unnecessary std::move on an r-value expression. This caused a compiler warning/error in the Linux Android QNN pipeline. ### Motivation and Context Introduced by PR: #24466
### Description Cherry pick the following into [rel-1.22.0](https://github.com/microsoft/onnxruntime/tree/rel-1.22.0) - (#24487) - (#24466) - (#24493) - (#24484) - (#24494) - (#24489) - (#24504) - (#24510) - (#24456) - (#24537) - (#24501) - (#24519) - (#24513) - (#24539) - (#24514) - (#24542) - (#24585) Not added: Planning to cherry pick Cuda Matmulnbits PRs once the fix for failing cuda pipeline is ready - (#24491) - (#24509) - (#24564) --------- Co-authored-by: Adrian Lizarraga <adlizarraga@microsoft.com> Co-authored-by: minfhong-quic <quic_minfhong@quicinc.com> Co-authored-by: minfhong-quic <minfhong-quic@quicinc.com> Co-authored-by: Justin Chu <justinchuby@users.noreply.github.com> Co-authored-by: Prathik Rao <prathik.rao@gmail.com> Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com> Co-authored-by: Ankan Banerjee <ankan.ban@gmail.com> Co-authored-by: Maximilian Müller <maximilianm@nvidia.com> Co-authored-by: Gaurav Garg <gaugarg@nvidia.com> Co-authored-by: iraut <iraut@nvidia.com> Co-authored-by: Hrishikesh Manohar <hrishikeshm@nvidia.com> Co-authored-by: Maximilian Müller <44298237+gedoensmax@users.noreply.github.com> Co-authored-by: Scott McKay <skottmckay@gmail.com> Co-authored-by: Jiajia Qin <jiajiaqin@microsoft.com> Co-authored-by: kunal-vaishnavi <115581922+kunal-vaishnavi@users.noreply.github.com> Co-authored-by: xhcao <xinghua.cao@intel.com>
### Description Cherry pick the following into [rel-1.22.0](https://github.com/microsoft/onnxruntime/tree/rel-1.22.0) - (microsoft#24487) - (microsoft#24466) - (microsoft#24493) - (microsoft#24484) - (microsoft#24494) - (microsoft#24489) - (microsoft#24504) - (microsoft#24510) - (microsoft#24456) - (microsoft#24537) - (microsoft#24501) - (microsoft#24519) - (microsoft#24513) - (microsoft#24539) - (microsoft#24514) - (microsoft#24542) - (microsoft#24585) Not added: Planning to cherry pick Cuda Matmulnbits PRs once the fix for failing cuda pipeline is ready - (microsoft#24491) - (microsoft#24509) - (microsoft#24564) --------- Co-authored-by: vraspar <vrajang@outlook.com> Co-authored-by: Adrian Lizarraga <adlizarraga@microsoft.com> Co-authored-by: minfhong-quic <quic_minfhong@quicinc.com> Co-authored-by: minfhong-quic <minfhong-quic@quicinc.com> Co-authored-by: Justin Chu <justinchuby@users.noreply.github.com> Co-authored-by: Prathik Rao <prathik.rao@gmail.com> Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com> Co-authored-by: Ankan Banerjee <ankan.ban@gmail.com> Co-authored-by: Maximilian Müller <maximilianm@nvidia.com> Co-authored-by: Gaurav Garg <gaugarg@nvidia.com> Co-authored-by: iraut <iraut@nvidia.com> Co-authored-by: Hrishikesh Manohar <hrishikeshm@nvidia.com> Co-authored-by: Maximilian Müller <44298237+gedoensmax@users.noreply.github.com> Co-authored-by: Scott McKay <skottmckay@gmail.com> Co-authored-by: Jiajia Qin <jiajiaqin@microsoft.com> Co-authored-by: kunal-vaishnavi <115581922+kunal-vaishnavi@users.noreply.github.com> Co-authored-by: xhcao <xinghua.cao@intel.com>
Description
For QNN-EP, build FP-to-Bool Cast into NotEqual.
Motivation and Context
HTP currently does not support FP-to-Bool Cast due to some limitations. To unblock CLIP models, replace such Cast with NotEqual to achieve the same functionality.