Yuya Hanai
3 years ago
commit
28de7450b4
19 changed files with 11045 additions and 0 deletions
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example-*/config.make |
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example-*/*.sln |
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example-*/*.vcxproj |
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example-*/*.filters |
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example-*/*.xcodeproj |
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example-*/icon.rc |
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example-*/Makefile |
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example-*/openFrameworks-info.plist |
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example-*/Project.xcconfig |
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example-*/mediaAssets |
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example-*/ofxiOS-Info.plist |
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### https://raw.github.com/github/gitignore/ade08baee2cf60afd794432b3e779fe5844c545d/C++.gitignore |
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# Prerequisites |
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*.d |
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# Compiled Object files |
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*.slo |
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*.lo |
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*.o |
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*.obj |
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# Precompiled Headers |
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*.gch |
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*.pch |
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# Compiled Dynamic libraries |
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#*.so |
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#*.dylib |
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#*.dll |
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# Fortran module files |
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*.mod |
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*.smod |
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# Compiled Static libraries |
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#*.lai |
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#*.la |
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#*.a |
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#*.lib |
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# Executables |
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*.exe |
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*.out |
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*.app |
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### https://raw.github.com/github/gitignore/ade08baee2cf60afd794432b3e779fe5844c545d/Global/Windows.gitignore |
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# Windows thumbnail cache files |
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Thumbs.db |
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ehthumbs.db |
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ehthumbs_vista.db |
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# Dump file |
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*.stackdump |
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# Folder config file |
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[Dd]esktop.ini |
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# Recycle Bin used on file shares |
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$RECYCLE.BIN/ |
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# Windows Installer files |
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*.cab |
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*.msi |
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*.msm |
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*.msp |
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# Windows shortcuts |
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*.lnk |
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### https://raw.github.com/github/gitignore/ade08baee2cf60afd794432b3e779fe5844c545d/Global/macOS.gitignore |
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# General |
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.DS_Store |
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.AppleDouble |
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.LSOverride |
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# Icon must end with two \r |
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Icon |
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# Thumbnails |
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._* |
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# Files that might appear in the root of a volume |
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.DocumentRevisions-V100 |
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.fseventsd |
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.Spotlight-V100 |
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.TemporaryItems |
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.Trashes |
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.VolumeIcon.icns |
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.com.apple.timemachine.donotpresent |
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# Directories potentially created on remote AFP share |
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.AppleDB |
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.AppleDesktop |
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Network Trash Folder |
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Temporary Items |
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.apdisk |
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|
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|
### https://raw.github.com/github/gitignore/ade08baee2cf60afd794432b3e779fe5844c545d/Global/Xcode.gitignore |
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|
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# Xcode |
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# |
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# gitignore contributors: remember to update Global/Xcode.gitignore, Objective-C.gitignore & Swift.gitignore |
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|
||||
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## User settings |
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|
xcuserdata/ |
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||||
|
## compatibility with Xcode 8 and earlier (ignoring not required starting Xcode 9) |
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*.xcscmblueprint |
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*.xccheckout |
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## compatibility with Xcode 3 and earlier (ignoring not required starting Xcode 4) |
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build/ |
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DerivedData/ |
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*.moved-aside |
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*.pbxuser |
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!default.pbxuser |
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*.mode1v3 |
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!default.mode1v3 |
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*.mode2v3 |
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!default.mode2v3 |
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*.perspectivev3 |
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!default.perspectivev3 |
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|
### https://raw.github.com/github/gitignore/ade08baee2cf60afd794432b3e779fe5844c545d/VisualStudio.gitignore |
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|
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## Ignore Visual Studio temporary files, build results, and |
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## files generated by popular Visual Studio add-ons. |
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## |
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## Get latest from https://github.com/github/gitignore/blob/master/VisualStudio.gitignore |
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|
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# User-specific files |
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*.suo |
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*.user |
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*.userosscache |
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*.sln.docstates |
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# User-specific files (MonoDevelop/Xamarin Studio) |
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*.userprefs |
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# Build results |
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[Dd]ebug/ |
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[Dd]ebugPublic/ |
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[Rr]elease/ |
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[Rr]eleases/ |
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#x64/ |
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#x86/ |
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bld/ |
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# [Bb]in/ |
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[Oo]bj/ |
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[Ll]og/ |
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# Visual Studio 2015/2017 cache/options directory |
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.vs/ |
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# Uncomment if you have tasks that create the project's static files in wwwroot |
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#wwwroot/ |
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# Visual Studio 2017 auto generated files |
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Generated\ Files/ |
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# MSTest test Results |
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[Tt]est[Rr]esult*/ |
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[Bb]uild[Ll]og.* |
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# NUNIT |
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*.VisualState.xml |
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TestResult.xml |
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# Build Results of an ATL Project |
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[Dd]ebugPS/ |
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[Rr]eleasePS/ |
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dlldata.c |
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# Benchmark Results |
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BenchmarkDotNet.Artifacts/ |
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# .NET Core |
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project.lock.json |
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project.fragment.lock.json |
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artifacts/ |
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**/Properties/launchSettings.json |
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# StyleCop |
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StyleCopReport.xml |
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# Files built by Visual Studio |
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*_i.c |
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*_p.c |
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*_i.h |
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*.ilk |
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*.meta |
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*.obj |
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*.pch |
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*.pdb |
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*.pgc |
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*.pgd |
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*.rsp |
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*.sbr |
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*.tlb |
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*.tli |
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*.tlh |
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*.tmp |
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*.tmp_proj |
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*.log |
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*.vspscc |
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*.vssscc |
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.builds |
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*.pidb |
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*.svclog |
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*.scc |
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# Chutzpah Test files |
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_Chutzpah* |
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# Visual C++ cache files |
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ipch/ |
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*.aps |
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*.ncb |
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*.opendb |
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*.opensdf |
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*.sdf |
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*.cachefile |
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*.VC.db |
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*.VC.VC.opendb |
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# Visual Studio profiler |
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*.psess |
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*.vsp |
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*.vspx |
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*.sap |
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# Visual Studio Trace Files |
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*.e2e |
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|
# TFS 2012 Local Workspace |
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|
$tf/ |
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# Guidance Automation Toolkit |
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*.gpState |
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||||
|
# ReSharper is a .NET coding add-in |
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_ReSharper*/ |
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*.[Rr]e[Ss]harper |
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*.DotSettings.user |
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|
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|
# JustCode is a .NET coding add-in |
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.JustCode |
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|
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|
# TeamCity is a build add-in |
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_TeamCity* |
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|
||||
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# DotCover is a Code Coverage Tool |
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*.dotCover |
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# AxoCover is a Code Coverage Tool |
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.axoCover/* |
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!.axoCover/settings.json |
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# Visual Studio code coverage results |
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*.coverage |
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*.coveragexml |
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# NCrunch |
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_NCrunch_* |
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.*crunch*.local.xml |
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nCrunchTemp_* |
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# MightyMoose |
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*.mm.* |
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AutoTest.Net/ |
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|
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# Web workbench (sass) |
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.sass-cache/ |
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|
|
||||
|
# Installshield output folder |
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|
[Ee]xpress/ |
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|
|
||||
|
# DocProject is a documentation generator add-in |
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|
DocProject/buildhelp/ |
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DocProject/Help/*.HxT |
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DocProject/Help/*.HxC |
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DocProject/Help/*.hhc |
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DocProject/Help/*.hhk |
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DocProject/Help/*.hhp |
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DocProject/Help/Html2 |
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DocProject/Help/html |
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|
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# Click-Once directory |
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publish/ |
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# Publish Web Output |
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*.[Pp]ublish.xml |
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*.azurePubxml |
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# Note: Comment the next line if you want to checkin your web deploy settings, |
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# but database connection strings (with potential passwords) will be unencrypted |
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*.pubxml |
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*.publishproj |
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|
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# Microsoft Azure Web App publish settings. Comment the next line if you want to |
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# checkin your Azure Web App publish settings, but sensitive information contained |
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# in these scripts will be unencrypted |
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PublishScripts/ |
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|
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# NuGet Packages |
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*.nupkg |
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# The packages folder can be ignored because of Package Restore |
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**/[Pp]ackages/* |
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# except build/, which is used as an MSBuild target. |
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!**/[Pp]ackages/build/ |
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# Uncomment if necessary however generally it will be regenerated when needed |
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#!**/[Pp]ackages/repositories.config |
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# NuGet v3's project.json files produces more ignorable files |
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*.nuget.props |
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*.nuget.targets |
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|
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# Microsoft Azure Build Output |
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csx/ |
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*.build.csdef |
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# Microsoft Azure Emulator |
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ecf/ |
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rcf/ |
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# Windows Store app package directories and files |
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AppPackages/ |
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BundleArtifacts/ |
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Package.StoreAssociation.xml |
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_pkginfo.txt |
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*.appx |
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|
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# Visual Studio cache files |
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# files ending in .cache can be ignored |
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*.[Cc]ache |
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# but keep track of directories ending in .cache |
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!*.[Cc]ache/ |
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|
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# Others |
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ClientBin/ |
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~$* |
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*~ |
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*.dbmdl |
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*.dbproj.schemaview |
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*.jfm |
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*.pfx |
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*.publishsettings |
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orleans.codegen.cs |
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# Including strong name files can present a security risk |
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# (https://github.com/github/gitignore/pull/2483#issue-259490424) |
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#*.snk |
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|
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# Since there are multiple workflows, uncomment next line to ignore bower_components |
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# (https://github.com/github/gitignore/pull/1529#issuecomment-104372622) |
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#bower_components/ |
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|
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# RIA/Silverlight projects |
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Generated_Code/ |
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|
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# Backup & report files from converting an old project file |
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# to a newer Visual Studio version. Backup files are not needed, |
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# because we have git ;-) |
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_UpgradeReport_Files/ |
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Backup*/ |
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UpgradeLog*.XML |
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UpgradeLog*.htm |
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|
||||
|
# SQL Server files |
||||
|
*.mdf |
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|
*.ldf |
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*.ndf |
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|
||||
|
# Business Intelligence projects |
||||
|
*.rdl.data |
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*.bim.layout |
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*.bim_*.settings |
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|
||||
|
# Microsoft Fakes |
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|
FakesAssemblies/ |
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|
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# GhostDoc plugin setting file |
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*.GhostDoc.xml |
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|
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# Node.js Tools for Visual Studio |
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.ntvs_analysis.dat |
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node_modules/ |
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|
||||
|
# TypeScript v1 declaration files |
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typings/ |
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|
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|
# Visual Studio 6 build log |
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|
*.plg |
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|
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# Visual Studio 6 workspace options file |
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*.opt |
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|
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|
# Visual Studio 6 auto-generated workspace file (contains which files were open etc.) |
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*.vbw |
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|
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# Visual Studio LightSwitch build output |
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|
**/*.HTMLClient/GeneratedArtifacts |
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**/*.DesktopClient/GeneratedArtifacts |
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**/*.DesktopClient/ModelManifest.xml |
||||
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**/*.Server/GeneratedArtifacts |
||||
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**/*.Server/ModelManifest.xml |
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_Pvt_Extensions |
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|
||||
|
# Paket dependency manager |
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|
.paket/paket.exe |
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paket-files/ |
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|
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# FAKE - F# Make |
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.fake/ |
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|
||||
|
# JetBrains Rider |
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.idea/ |
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*.sln.iml |
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|
||||
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# CodeRush |
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.cr/ |
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|
||||
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# Python Tools for Visual Studio (PTVS) |
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__pycache__/ |
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*.pyc |
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|
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# Cake - Uncomment if you are using it |
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# tools/** |
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# !tools/packages.config |
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|
||||
|
# Tabs Studio |
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*.tss |
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|
||||
|
# Telerik's JustMock configuration file |
||||
|
*.jmconfig |
||||
|
|
||||
|
# BizTalk build output |
||||
|
*.btp.cs |
||||
|
*.btm.cs |
||||
|
*.odx.cs |
||||
|
*.xsd.cs |
||||
|
|
||||
|
# OpenCover UI analysis results |
||||
|
OpenCover/ |
||||
|
|
||||
|
# Azure Stream Analytics local run output |
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|
ASALocalRun/ |
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|
|
||||
|
# MSBuild Binary and Structured Log |
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*.binlog |
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@ -0,0 +1,8 @@ |
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# ofxOnnxRuntime |
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[OnnxRuntime](https://github.com/microsoft/onnxruntime) tiny wrapper for openFrameworks |
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## Tested environment |
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- MacBookPro 2018 Intel + macOS Catalina |
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## ToDo |
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- check M1 Mac (should work), Windows CPU&GPU, Linux CPU&GPU |
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meta: |
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ADDON_NAME = ofxOnnxRuntime |
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ADDON_DESCRIPTION = "ONNX Runtime addon for OpenFrameworks" |
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ADDON_AUTHOR = Yuya Hanai |
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ADDON_TAGS = "ONNX" |
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ADDON_URL = https://github.com/hanasaan/ofxOnnxRuntime |
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||||
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common: |
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ADDON_INCLUDES = libs/onnxruntime/include |
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ADDON_INCLUDES += src |
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osx: |
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ADDON_LDFLAGS = -Xlinker -rpath -Xlinker @executable_path |
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vs: |
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@ -0,0 +1 @@ |
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ofxOnnxRuntime |
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#include "ofMain.h" |
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#include "ofxOnnxRuntime.h" |
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// code from
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//https://github.com/microsoft/onnxruntime-inference-examples/blob/main/c_cxx/MNIST/MNIST.cpp
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template <typename T> |
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static void softmax(T& input) { |
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float rowmax = *std::max_element(input.begin(), input.end()); |
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std::vector<float> y(input.size()); |
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float sum = 0.0f; |
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for (size_t i = 0; i != input.size(); ++i) { |
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sum += y[i] = std::exp(input[i] - rowmax); |
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} |
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for (size_t i = 0; i != input.size(); ++i) { |
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input[i] = y[i] / sum; |
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} |
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} |
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||||
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// This is the structure to interface with the MNIST model
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// After instantiation, set the input_image_ data to be the 28x28 pixel image of the number to recognize
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// Then call Run() to fill in the results_ data with the probabilities of each
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// result_ holds the index with highest probability (aka the number the model thinks is in the image)
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struct MNIST { |
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MNIST() { |
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auto memory_info = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU); |
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input_tensor_ = Ort::Value::CreateTensor<float>(memory_info, input_image_.data(), input_image_.size(), input_shape_.data(), input_shape_.size()); |
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output_tensor_ = Ort::Value::CreateTensor<float>(memory_info, results_.data(), results_.size(), output_shape_.data(), output_shape_.size()); |
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} |
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std::ptrdiff_t Run() { |
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const char* input_names[] = {"Input3"}; |
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const char* output_names[] = {"Plus214_Output_0"}; |
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||||
|
session_.Run(Ort::RunOptions{nullptr}, input_names, &input_tensor_, 1, output_names, &output_tensor_, 1); |
||||
|
softmax(results_); |
||||
|
result_ = std::distance(results_.begin(), std::max_element(results_.begin(), results_.end())); |
||||
|
return result_; |
||||
|
} |
||||
|
|
||||
|
static constexpr const int width_ = 28; |
||||
|
static constexpr const int height_ = 28; |
||||
|
|
||||
|
std::array<float, width_ * height_> input_image_{}; |
||||
|
std::array<float, 10> results_{}; |
||||
|
int64_t result_{0}; |
||||
|
|
||||
|
private: |
||||
|
Ort::Env env; |
||||
|
Ort::Session session_{env, ofToDataPath("mnist-8.onnx", true).c_str(), Ort::SessionOptions{nullptr}}; |
||||
|
|
||||
|
Ort::Value input_tensor_{nullptr}; |
||||
|
std::array<int64_t, 4> input_shape_{1, 1, width_, height_}; |
||||
|
|
||||
|
Ort::Value output_tensor_{nullptr}; |
||||
|
std::array<int64_t, 2> output_shape_{1, 10}; |
||||
|
}; |
||||
|
|
||||
|
class ofApp : public ofBaseApp{ |
||||
|
shared_ptr<MNIST> mnist; |
||||
|
ofFbo fbo_render; |
||||
|
ofFbo fbo_classification; |
||||
|
ofFloatPixels pix; |
||||
|
bool prev_pressed = false; |
||||
|
glm::vec2 prev_pt; |
||||
|
public: |
||||
|
void setup() |
||||
|
{ |
||||
|
ofSetVerticalSync(true); |
||||
|
ofSetFrameRate(60); |
||||
|
|
||||
|
mnist = make_shared<MNIST>(); |
||||
|
|
||||
|
fbo_render.allocate(280, 280, GL_RGB, 0); |
||||
|
fbo_render.getTexture().setTextureMinMagFilter(GL_NEAREST, GL_NEAREST); |
||||
|
fbo_render.begin(); |
||||
|
ofClear(0); |
||||
|
fbo_render.end(); |
||||
|
fbo_classification.allocate(28, 28, GL_R32F, 0); |
||||
|
|
||||
|
pix.setFromExternalPixels(&mnist->input_image_.front(), 28, 28, 1); |
||||
|
} |
||||
|
|
||||
|
void update() |
||||
|
{ |
||||
|
if (ofGetMousePressed()) { |
||||
|
auto pt = glm::vec2(ofGetMouseX(), ofGetMouseY() - 60); |
||||
|
fbo_render.begin(); |
||||
|
ofPushStyle(); |
||||
|
ofSetColor(255); |
||||
|
if (prev_pressed) { |
||||
|
ofSetLineWidth(20); |
||||
|
ofDrawLine(prev_pt, pt); |
||||
|
} |
||||
|
ofDrawCircle(pt.x, pt.y, 10); |
||||
|
ofPopStyle(); |
||||
|
fbo_render.end(); |
||||
|
|
||||
|
fbo_classification.begin(); |
||||
|
ofClear(0); |
||||
|
fbo_render.draw(0, 0, fbo_classification.getWidth(), fbo_classification.getHeight()); |
||||
|
fbo_classification.end(); |
||||
|
fbo_classification.readToPixels(pix); |
||||
|
mnist->Run(); |
||||
|
prev_pt = pt; |
||||
|
prev_pressed = true; |
||||
|
} else { |
||||
|
prev_pressed = false; |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
void draw() |
||||
|
{ |
||||
|
ofClear(128); |
||||
|
|
||||
|
fbo_render.draw(0, 60); |
||||
|
fbo_classification.draw(0, 340); |
||||
|
|
||||
|
// render result
|
||||
|
for (int i=0; i<10; ++i) { |
||||
|
stringstream ss; |
||||
|
ss << i << ":" << std::fixed << std::setprecision(3) << mnist->results_[i]; |
||||
|
ofDrawBitmapString(ss.str(), 300, 70 + i * 30); |
||||
|
ofPushStyle(); |
||||
|
ofSetColor(0, 255, 0); |
||||
|
ofDrawRectangle(360.0, 55 + i * 30, mnist->results_[i] * 300.0, 20); |
||||
|
ofPopStyle(); |
||||
|
} |
||||
|
|
||||
|
stringstream ss; |
||||
|
ss << "FPS : " << ofGetFrameRate() << endl; |
||||
|
ss << "Draw any digit (0-9) here" << endl; |
||||
|
ss << "Press c to clear buffer"; |
||||
|
ofDrawBitmapStringHighlight(ss.str(), 10, 20); |
||||
|
} |
||||
|
|
||||
|
void keyPressed(int key) |
||||
|
{ |
||||
|
if (key == 'c') { |
||||
|
fbo_render.begin(); |
||||
|
ofClear(0); |
||||
|
fbo_render.end(); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
void keyReleased(int key) {} |
||||
|
void mouseMoved(int x, int y ) {} |
||||
|
void mouseDragged(int x, int y, int button) {} |
||||
|
|
||||
|
void mousePressed(int x, int y, int button) { |
||||
|
|
||||
|
} |
||||
|
|
||||
|
void mouseReleased(int x, int y, int button) {} |
||||
|
void windowResized(int w, int h) {} |
||||
|
void dragEvent(ofDragInfo dragInfo) {} |
||||
|
void gotMessage(ofMessage msg) {} |
||||
|
|
||||
|
}; |
||||
|
|
||||
|
//========================================================================
|
||||
|
int main( ){ |
||||
|
ofSetupOpenGL(640,400,OF_WINDOW); // <-------- setup the GL context
|
||||
|
|
||||
|
// this kicks off the running of my app
|
||||
|
// can be OF_WINDOW or OF_FULLSCREEN
|
||||
|
// pass in width and height too:
|
||||
|
ofRunApp(new ofApp()); |
||||
|
|
||||
|
} |
||||
@ -0,0 +1,21 @@ |
|||||
|
MIT License |
||||
|
|
||||
|
Copyright (c) Microsoft Corporation |
||||
|
|
||||
|
Permission is hereby granted, free of charge, to any person obtaining a copy |
||||
|
of this software and associated documentation files (the "Software"), to deal |
||||
|
in the Software without restriction, including without limitation the rights |
||||
|
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell |
||||
|
copies of the Software, and to permit persons to whom the Software is |
||||
|
furnished to do so, subject to the following conditions: |
||||
|
|
||||
|
The above copyright notice and this permission notice shall be included in all |
||||
|
copies or substantial portions of the Software. |
||||
|
|
||||
|
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
||||
|
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
||||
|
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
||||
|
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
||||
|
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
||||
|
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
||||
|
SOFTWARE. |
||||
File diff suppressed because it is too large
@ -0,0 +1,19 @@ |
|||||
|
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
|
// Licensed under the MIT License.
|
||||
|
|
||||
|
#include "onnxruntime_c_api.h" |
||||
|
|
||||
|
#ifdef __cplusplus |
||||
|
extern "C" { |
||||
|
#endif |
||||
|
|
||||
|
/**
|
||||
|
* \param use_arena zero: false. non-zero: true. |
||||
|
*/ |
||||
|
ORT_EXPORT |
||||
|
ORT_API_STATUS(OrtSessionOptionsAppendExecutionProvider_CPU, _In_ OrtSessionOptions* options, int use_arena) |
||||
|
ORT_ALL_ARGS_NONNULL; |
||||
|
|
||||
|
#ifdef __cplusplus |
||||
|
} |
||||
|
#endif |
||||
File diff suppressed because it is too large
@ -0,0 +1,975 @@ |
|||||
|
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
|
// Licensed under the MIT License.
|
||||
|
|
||||
|
// Summary: The Ort C++ API is a header only wrapper around the Ort C API.
|
||||
|
//
|
||||
|
// The C++ API simplifies usage by returning values directly instead of error codes, throwing exceptions on errors
|
||||
|
// and automatically releasing resources in the destructors.
|
||||
|
//
|
||||
|
// Each of the C++ wrapper classes holds only a pointer to the C internal object. Treat them like smart pointers.
|
||||
|
// To create an empty object, pass 'nullptr' to the constructor (for example, Env e{nullptr};).
|
||||
|
//
|
||||
|
// Only move assignment between objects is allowed, there are no copy constructors. Some objects have explicit 'Clone'
|
||||
|
// methods for this purpose.
|
||||
|
|
||||
|
#pragma once |
||||
|
#include "onnxruntime_c_api.h" |
||||
|
#include <cstddef> |
||||
|
#include <array> |
||||
|
#include <memory> |
||||
|
#include <stdexcept> |
||||
|
#include <string> |
||||
|
#include <vector> |
||||
|
#include <utility> |
||||
|
#include <type_traits> |
||||
|
|
||||
|
#ifdef ORT_NO_EXCEPTIONS |
||||
|
#include <iostream> |
||||
|
#endif |
||||
|
|
||||
|
/** \brief All C++ Onnxruntime APIs are defined inside this namespace
|
||||
|
* |
||||
|
*/ |
||||
|
namespace Ort { |
||||
|
|
||||
|
/** \brief All C++ methods that can fail will throw an exception of this type
|
||||
|
* |
||||
|
* If <tt>ORT_NO_EXCEPTIONS</tt> is defined, then any error will result in a call to abort() |
||||
|
*/ |
||||
|
struct Exception : std::exception { |
||||
|
Exception(std::string&& string, OrtErrorCode code) : message_{std::move(string)}, code_{code} {} |
||||
|
|
||||
|
OrtErrorCode GetOrtErrorCode() const { return code_; } |
||||
|
const char* what() const noexcept override { return message_.c_str(); } |
||||
|
|
||||
|
private: |
||||
|
std::string message_; |
||||
|
OrtErrorCode code_; |
||||
|
}; |
||||
|
|
||||
|
#ifdef ORT_NO_EXCEPTIONS |
||||
|
#define ORT_CXX_API_THROW(string, code) \ |
||||
|
do { \ |
||||
|
std::cerr << Ort::Exception(string, code) \ |
||||
|
.what() \ |
||||
|
<< std::endl; \ |
||||
|
abort(); \ |
||||
|
} while (false) |
||||
|
#else |
||||
|
#define ORT_CXX_API_THROW(string, code) \ |
||||
|
throw Ort::Exception(string, code) |
||||
|
#endif |
||||
|
|
||||
|
// This is used internally by the C++ API. This class holds the global variable that points to the OrtApi, it's in a template so that we can define a global variable in a header and make
|
||||
|
// it transparent to the users of the API.
|
||||
|
template <typename T> |
||||
|
struct Global { |
||||
|
static const OrtApi* api_; |
||||
|
}; |
||||
|
|
||||
|
// If macro ORT_API_MANUAL_INIT is defined, no static initialization will be performed. Instead, user must call InitApi() before using it.
|
||||
|
template <typename T> |
||||
|
#ifdef ORT_API_MANUAL_INIT |
||||
|
const OrtApi* Global<T>::api_{}; |
||||
|
inline void InitApi() { Global<void>::api_ = OrtGetApiBase()->GetApi(ORT_API_VERSION); } |
||||
|
#else |
||||
|
const OrtApi* Global<T>::api_ = OrtGetApiBase()->GetApi(ORT_API_VERSION); |
||||
|
#endif |
||||
|
|
||||
|
/// This returns a reference to the OrtApi interface in use
|
||||
|
inline const OrtApi& GetApi() { return *Global<void>::api_; } |
||||
|
|
||||
|
/// This is a C++ wrapper for OrtApi::GetAvailableProviders() and returns a vector of strings representing the available execution providers.
|
||||
|
std::vector<std::string> GetAvailableProviders(); |
||||
|
|
||||
|
// This is used internally by the C++ API. This macro is to make it easy to generate overloaded methods for all of the various OrtRelease* functions for every Ort* type
|
||||
|
// This can't be done in the C API since C doesn't have function overloading.
|
||||
|
#define ORT_DEFINE_RELEASE(NAME) \ |
||||
|
inline void OrtRelease(Ort##NAME* ptr) { GetApi().Release##NAME(ptr); } |
||||
|
|
||||
|
ORT_DEFINE_RELEASE(Allocator); |
||||
|
ORT_DEFINE_RELEASE(MemoryInfo); |
||||
|
ORT_DEFINE_RELEASE(CustomOpDomain); |
||||
|
ORT_DEFINE_RELEASE(Env); |
||||
|
ORT_DEFINE_RELEASE(RunOptions); |
||||
|
ORT_DEFINE_RELEASE(Session); |
||||
|
ORT_DEFINE_RELEASE(SessionOptions); |
||||
|
ORT_DEFINE_RELEASE(TensorTypeAndShapeInfo); |
||||
|
ORT_DEFINE_RELEASE(SequenceTypeInfo); |
||||
|
ORT_DEFINE_RELEASE(MapTypeInfo); |
||||
|
ORT_DEFINE_RELEASE(TypeInfo); |
||||
|
ORT_DEFINE_RELEASE(Value); |
||||
|
ORT_DEFINE_RELEASE(ModelMetadata); |
||||
|
ORT_DEFINE_RELEASE(ThreadingOptions); |
||||
|
ORT_DEFINE_RELEASE(IoBinding); |
||||
|
ORT_DEFINE_RELEASE(ArenaCfg); |
||||
|
|
||||
|
#undef ORT_DEFINE_RELEASE |
||||
|
|
||||
|
/** \brief IEEE 754 half-precision floating point data type
|
||||
|
* \details It is necessary for type dispatching to make use of C++ API |
||||
|
* The type is implicitly convertible to/from uint16_t. |
||||
|
* The size of the structure should align with uint16_t and one can freely cast |
||||
|
* uint16_t buffers to/from Ort::Float16_t to feed and retrieve data. |
||||
|
* |
||||
|
* Generally, you can feed any of your types as float16/blfoat16 data to create a tensor |
||||
|
* on top of it, providing it can form a continuous buffer with 16-bit elements with no padding. |
||||
|
* And you can also feed a array of uint16_t elements directly. For example, |
||||
|
* |
||||
|
* \code{.unparsed} |
||||
|
* uint16_t values[] = { 15360, 16384, 16896, 17408, 17664}; |
||||
|
* constexpr size_t values_length = sizeof(values) / sizeof(values[0]); |
||||
|
* std::vector<int64_t> dims = {values_length}; // one dimensional example
|
||||
|
* Ort::MemoryInfo info("Cpu", OrtDeviceAllocator, 0, OrtMemTypeDefault); |
||||
|
* // Note we are passing bytes count in this api, not number of elements -> sizeof(values)
|
||||
|
* auto float16_tensor = Ort::Value::CreateTensor(info, values, sizeof(values), |
||||
|
* dims.data(), dims.size(), ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16); |
||||
|
* \endcode |
||||
|
* |
||||
|
* Here is another example, a little bit more elaborate. Let's assume that you use your own float16 type and you want to use |
||||
|
* a templated version of the API above so the type is automatically set based on your type. You will need to supply an extra |
||||
|
* template specialization. |
||||
|
* |
||||
|
* \code{.unparsed} |
||||
|
* namespace yours { struct half {}; } // assume this is your type, define this:
|
||||
|
* namespace Ort { |
||||
|
* template<> |
||||
|
* struct TypeToTensorType<yours::half> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16; }; |
||||
|
* } //namespace Ort
|
||||
|
* |
||||
|
* std::vector<yours::half> values; |
||||
|
* std::vector<int64_t> dims = {values.size()}; // one dimensional example
|
||||
|
* Ort::MemoryInfo info("Cpu", OrtDeviceAllocator, 0, OrtMemTypeDefault); |
||||
|
* // Here we are passing element count -> values.size()
|
||||
|
* auto float16_tensor = Ort::Value::CreateTensor<yours::half>(info, values.data(), values.size(), dims.data(), dims.size()); |
||||
|
* |
||||
|
* \endcode |
||||
|
*/ |
||||
|
struct Float16_t { |
||||
|
uint16_t value; |
||||
|
constexpr Float16_t() noexcept : value(0) {} |
||||
|
constexpr Float16_t(uint16_t v) noexcept : value(v) {} |
||||
|
constexpr operator uint16_t() const noexcept { return value; } |
||||
|
constexpr bool operator==(const Float16_t& rhs) const noexcept { return value == rhs.value; }; |
||||
|
constexpr bool operator!=(const Float16_t& rhs) const noexcept { return value != rhs.value; }; |
||||
|
}; |
||||
|
|
||||
|
static_assert(sizeof(Float16_t) == sizeof(uint16_t), "Sizes must match"); |
||||
|
|
||||
|
/** \brief bfloat16 (Brain Floating Point) data type
|
||||
|
* \details It is necessary for type dispatching to make use of C++ API |
||||
|
* The type is implicitly convertible to/from uint16_t. |
||||
|
* The size of the structure should align with uint16_t and one can freely cast |
||||
|
* uint16_t buffers to/from Ort::BFloat16_t to feed and retrieve data. |
||||
|
* |
||||
|
* See also code examples for Float16_t above. |
||||
|
*/ |
||||
|
struct BFloat16_t { |
||||
|
uint16_t value; |
||||
|
constexpr BFloat16_t() noexcept : value(0) {} |
||||
|
constexpr BFloat16_t(uint16_t v) noexcept : value(v) {} |
||||
|
constexpr operator uint16_t() const noexcept { return value; } |
||||
|
constexpr bool operator==(const BFloat16_t& rhs) const noexcept { return value == rhs.value; }; |
||||
|
constexpr bool operator!=(const BFloat16_t& rhs) const noexcept { return value != rhs.value; }; |
||||
|
}; |
||||
|
|
||||
|
static_assert(sizeof(BFloat16_t) == sizeof(uint16_t), "Sizes must match"); |
||||
|
|
||||
|
/** \brief Used internally by the C++ API. C++ wrapper types inherit from this
|
||||
|
* |
||||
|
* This is a zero cost abstraction to wrap the C API objects and delete them on destruction. |
||||
|
* There is a secondary class 'Unowned<T>' that is used to prevent deletion on destruction (Used for return types that are |
||||
|
* not owned by the caller) |
||||
|
* |
||||
|
*/ |
||||
|
template <typename T> |
||||
|
struct Base { |
||||
|
using contained_type = T; |
||||
|
|
||||
|
Base() = default; |
||||
|
Base(T* p) : p_{p} { |
||||
|
if (!p) |
||||
|
ORT_CXX_API_THROW("Allocation failure", ORT_FAIL); |
||||
|
} |
||||
|
~Base() { OrtRelease(p_); } |
||||
|
|
||||
|
operator T*() { return p_; } |
||||
|
operator const T*() const { return p_; } |
||||
|
|
||||
|
/// \brief Releases ownership of the contained pointer
|
||||
|
T* release() { |
||||
|
T* p = p_; |
||||
|
p_ = nullptr; |
||||
|
return p; |
||||
|
} |
||||
|
|
||||
|
protected: |
||||
|
Base(const Base&) = delete; |
||||
|
Base& operator=(const Base&) = delete; |
||||
|
Base(Base&& v) noexcept : p_{v.p_} { v.p_ = nullptr; } |
||||
|
void operator=(Base&& v) noexcept { |
||||
|
OrtRelease(p_); |
||||
|
p_ = v.release(); |
||||
|
} |
||||
|
|
||||
|
T* p_{}; |
||||
|
|
||||
|
template <typename> |
||||
|
friend struct Unowned; // This friend line is needed to keep the centos C++ compiler from giving an error
|
||||
|
}; |
||||
|
|
||||
|
/** \brief Wraps an object that inherits from Ort::Base and stops it from deleting the contained pointer on destruction
|
||||
|
* |
||||
|
* This has the effect of making it not own the memory held by Ort::Base. |
||||
|
*/ |
||||
|
template <typename T> |
||||
|
struct Unowned : T { |
||||
|
Unowned(typename T::contained_type* p) : T{p} {} |
||||
|
Unowned(Unowned&& v) : T{v.p_} {} |
||||
|
~Unowned() { this->release(); } |
||||
|
}; |
||||
|
|
||||
|
struct AllocatorWithDefaultOptions; |
||||
|
struct MemoryInfo; |
||||
|
struct Env; |
||||
|
struct TypeInfo; |
||||
|
struct Value; |
||||
|
struct ModelMetadata; |
||||
|
|
||||
|
/** \brief The Env (Environment)
|
||||
|
* |
||||
|
* The Env holds the logging state used by all other objects. |
||||
|
* <b>Note:</b> One Env must be created before using any other Onnxruntime functionality |
||||
|
*/ |
||||
|
struct Env : Base<OrtEnv> { |
||||
|
explicit Env(std::nullptr_t) {} ///< Create an empty Env object, must be assigned a valid one to be used
|
||||
|
|
||||
|
/// \brief Wraps OrtApi::CreateEnv
|
||||
|
Env(OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = ""); |
||||
|
|
||||
|
/// \brief Wraps OrtApi::CreateEnvWithCustomLogger
|
||||
|
Env(OrtLoggingLevel logging_level, const char* logid, OrtLoggingFunction logging_function, void* logger_param); |
||||
|
|
||||
|
/// \brief Wraps OrtApi::CreateEnvWithGlobalThreadPools
|
||||
|
Env(const OrtThreadingOptions* tp_options, OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = ""); |
||||
|
|
||||
|
/// \brief Wraps OrtApi::CreateEnvWithCustomLoggerAndGlobalThreadPools
|
||||
|
Env(const OrtThreadingOptions* tp_options, OrtLoggingFunction logging_function, void* logger_param, |
||||
|
OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = ""); |
||||
|
|
||||
|
/// \brief C Interop Helper
|
||||
|
explicit Env(OrtEnv* p) : Base<OrtEnv>{p} {} |
||||
|
|
||||
|
Env& EnableTelemetryEvents(); ///< Wraps OrtApi::EnableTelemetryEvents
|
||||
|
Env& DisableTelemetryEvents(); ///< Wraps OrtApi::DisableTelemetryEvents
|
||||
|
|
||||
|
Env& CreateAndRegisterAllocator(const OrtMemoryInfo* mem_info, const OrtArenaCfg* arena_cfg); ///< Wraps OrtApi::CreateAndRegisterAllocator
|
||||
|
}; |
||||
|
|
||||
|
/** \brief Custom Op Domain
|
||||
|
* |
||||
|
*/ |
||||
|
struct CustomOpDomain : Base<OrtCustomOpDomain> { |
||||
|
explicit CustomOpDomain(std::nullptr_t) {} ///< Create an empty CustomOpDomain object, must be assigned a valid one to be used
|
||||
|
|
||||
|
/// \brief Wraps OrtApi::CreateCustomOpDomain
|
||||
|
explicit CustomOpDomain(const char* domain); |
||||
|
|
||||
|
void Add(OrtCustomOp* op); ///< Wraps CustomOpDomain_Add
|
||||
|
}; |
||||
|
|
||||
|
struct RunOptions : Base<OrtRunOptions> { |
||||
|
explicit RunOptions(std::nullptr_t) {} ///< Create an empty RunOptions object, must be assigned a valid one to be used
|
||||
|
RunOptions(); ///< Wraps OrtApi::CreateRunOptions
|
||||
|
|
||||
|
RunOptions& SetRunLogVerbosityLevel(int); ///< Wraps OrtApi::RunOptionsSetRunLogVerbosityLevel
|
||||
|
int GetRunLogVerbosityLevel() const; ///< Wraps OrtApi::RunOptionsGetRunLogVerbosityLevel
|
||||
|
|
||||
|
RunOptions& SetRunLogSeverityLevel(int); ///< Wraps OrtApi::RunOptionsSetRunLogSeverityLevel
|
||||
|
int GetRunLogSeverityLevel() const; ///< Wraps OrtApi::RunOptionsGetRunLogSeverityLevel
|
||||
|
|
||||
|
RunOptions& SetRunTag(const char* run_tag); ///< wraps OrtApi::RunOptionsSetRunTag
|
||||
|
const char* GetRunTag() const; ///< Wraps OrtApi::RunOptionsGetRunTag
|
||||
|
|
||||
|
RunOptions& AddConfigEntry(const char* config_key, const char* config_value); ///< Wraps OrtApi::AddRunConfigEntry
|
||||
|
|
||||
|
/** \brief Terminates all currently executing Session::Run calls that were made using this RunOptions instance
|
||||
|
* |
||||
|
* If a currently executing session needs to be force terminated, this can be called from another thread to force it to fail with an error |
||||
|
* Wraps OrtApi::RunOptionsSetTerminate |
||||
|
*/ |
||||
|
RunOptions& SetTerminate(); |
||||
|
|
||||
|
/** \brief Clears the terminate flag so this RunOptions instance can be used in a new Session::Run call without it instantly terminating
|
||||
|
* |
||||
|
* Wraps OrtApi::RunOptionsUnsetTerminate |
||||
|
*/ |
||||
|
RunOptions& UnsetTerminate(); |
||||
|
}; |
||||
|
|
||||
|
/** \brief Options object used when creating a new Session object
|
||||
|
* |
||||
|
* Wraps ::OrtSessionOptions object and methods |
||||
|
*/ |
||||
|
struct SessionOptions : Base<OrtSessionOptions> { |
||||
|
explicit SessionOptions(std::nullptr_t) {} ///< Create an empty SessionOptions object, must be assigned a valid one to be used
|
||||
|
SessionOptions(); ///< Wraps OrtApi::CreateSessionOptions
|
||||
|
explicit SessionOptions(OrtSessionOptions* p) : Base<OrtSessionOptions>{p} {} ///< Used for interop with the C API
|
||||
|
|
||||
|
SessionOptions Clone() const; ///< Creates and returns a copy of this SessionOptions object. Wraps OrtApi::CloneSessionOptions
|
||||
|
|
||||
|
SessionOptions& SetIntraOpNumThreads(int intra_op_num_threads); ///< Wraps OrtApi::SetIntraOpNumThreads
|
||||
|
SessionOptions& SetInterOpNumThreads(int inter_op_num_threads); ///< Wraps OrtApi::SetInterOpNumThreads
|
||||
|
SessionOptions& SetGraphOptimizationLevel(GraphOptimizationLevel graph_optimization_level); ///< Wraps OrtApi::SetSessionGraphOptimizationLevel
|
||||
|
|
||||
|
SessionOptions& EnableCpuMemArena(); ///< Wraps OrtApi::EnableCpuMemArena
|
||||
|
SessionOptions& DisableCpuMemArena(); ///< Wraps OrtApi::DisableCpuMemArena
|
||||
|
|
||||
|
SessionOptions& SetOptimizedModelFilePath(const ORTCHAR_T* optimized_model_file); ///< Wraps OrtApi::SetOptimizedModelFilePath
|
||||
|
|
||||
|
SessionOptions& EnableProfiling(const ORTCHAR_T* profile_file_prefix); ///< Wraps OrtApi::EnableProfiling
|
||||
|
SessionOptions& DisableProfiling(); ///< Wraps OrtApi::DisableProfiling
|
||||
|
|
||||
|
SessionOptions& EnableOrtCustomOps(); ///< Wraps OrtApi::EnableOrtCustomOps
|
||||
|
|
||||
|
SessionOptions& EnableMemPattern(); ///< Wraps OrtApi::EnableMemPattern
|
||||
|
SessionOptions& DisableMemPattern(); ///< Wraps OrtApi::DisableMemPattern
|
||||
|
|
||||
|
SessionOptions& SetExecutionMode(ExecutionMode execution_mode); ///< Wraps OrtApi::SetSessionExecutionMode
|
||||
|
|
||||
|
SessionOptions& SetLogId(const char* logid); ///< Wraps OrtApi::SetSessionLogId
|
||||
|
SessionOptions& SetLogSeverityLevel(int level); ///< Wraps OrtApi::SetSessionLogSeverityLevel
|
||||
|
|
||||
|
SessionOptions& Add(OrtCustomOpDomain* custom_op_domain); ///< Wraps OrtApi::AddCustomOpDomain
|
||||
|
|
||||
|
SessionOptions& DisablePerSessionThreads(); ///< Wraps OrtApi::DisablePerSessionThreads
|
||||
|
|
||||
|
SessionOptions& AddConfigEntry(const char* config_key, const char* config_value); ///< Wraps OrtApi::AddSessionConfigEntry
|
||||
|
SessionOptions& AddInitializer(const char* name, const OrtValue* ort_val); ///< Wraps OrtApi::AddInitializer
|
||||
|
|
||||
|
SessionOptions& AppendExecutionProvider_CUDA(const OrtCUDAProviderOptions& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_CUDA
|
||||
|
SessionOptions& AppendExecutionProvider_ROCM(const OrtROCMProviderOptions& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_ROCM
|
||||
|
SessionOptions& AppendExecutionProvider_OpenVINO(const OrtOpenVINOProviderOptions& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_OpenVINO
|
||||
|
SessionOptions& AppendExecutionProvider_TensorRT(const OrtTensorRTProviderOptions& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_TensorRT
|
||||
|
|
||||
|
SessionOptions& SetCustomCreateThreadFn(OrtCustomCreateThreadFn ort_custom_create_thread_fn); ///< Wraps OrtApi::SessionOptionsSetCustomCreateThreadFn
|
||||
|
SessionOptions& SetCustomThreadCreationOptions(void* ort_custom_thread_creation_options); ///< Wraps OrtApi::SessionOptionsSetCustomThreadCreationOptions
|
||||
|
SessionOptions& SetCustomJoinThreadFn(OrtCustomJoinThreadFn ort_custom_join_thread_fn); ///< Wraps OrtApi::SessionOptionsSetCustomJoinThreadFn
|
||||
|
}; |
||||
|
|
||||
|
/** \brief Wrapper around ::OrtModelMetadata
|
||||
|
* |
||||
|
*/ |
||||
|
struct ModelMetadata : Base<OrtModelMetadata> { |
||||
|
explicit ModelMetadata(std::nullptr_t) {} ///< Create an empty ModelMetadata object, must be assigned a valid one to be used
|
||||
|
explicit ModelMetadata(OrtModelMetadata* p) : Base<OrtModelMetadata>{p} {} ///< Used for interop with the C API
|
||||
|
|
||||
|
char* GetProducerName(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetProducerName
|
||||
|
char* GetGraphName(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetGraphName
|
||||
|
char* GetDomain(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetDomain
|
||||
|
char* GetDescription(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetDescription
|
||||
|
char* GetGraphDescription(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetGraphDescription
|
||||
|
char** GetCustomMetadataMapKeys(OrtAllocator* allocator, _Out_ int64_t& num_keys) const; ///< Wraps OrtApi::ModelMetadataGetCustomMetadataMapKeys
|
||||
|
char* LookupCustomMetadataMap(const char* key, OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataLookupCustomMetadataMap
|
||||
|
int64_t GetVersion() const; ///< Wraps OrtApi::ModelMetadataGetVersion
|
||||
|
}; |
||||
|
|
||||
|
/** \brief Wrapper around ::OrtSession
|
||||
|
* |
||||
|
*/ |
||||
|
struct Session : Base<OrtSession> { |
||||
|
explicit Session(std::nullptr_t) {} ///< Create an empty Session object, must be assigned a valid one to be used
|
||||
|
Session(Env& env, const ORTCHAR_T* model_path, const SessionOptions& options); ///< Wraps OrtApi::CreateSession
|
||||
|
Session(Env& env, const ORTCHAR_T* model_path, const SessionOptions& options, OrtPrepackedWeightsContainer* prepacked_weights_container); ///< Wraps OrtApi::CreateSessionWithPrepackedWeightsContainer
|
||||
|
Session(Env& env, const void* model_data, size_t model_data_length, const SessionOptions& options); ///< Wraps OrtApi::CreateSessionFromArray
|
||||
|
|
||||
|
/** \brief Run the model returning results in an Ort allocated vector.
|
||||
|
* |
||||
|
* Wraps OrtApi::Run |
||||
|
* |
||||
|
* The caller provides a list of inputs and a list of the desired outputs to return. |
||||
|
* |
||||
|
* See the output logs for more information on warnings/errors that occur while processing the model. |
||||
|
* Common errors are.. (TODO) |
||||
|
* |
||||
|
* \param[in] run_options |
||||
|
* \param[in] input_names Array of null terminated strings of length input_count that is the list of input names |
||||
|
* \param[in] input_values Array of Value objects of length input_count that is the list of input values |
||||
|
* \param[in] input_count Number of inputs (the size of the input_names & input_values arrays) |
||||
|
* \param[in] output_names Array of C style strings of length output_count that is the list of output names |
||||
|
* \param[in] output_count Number of outputs (the size of the output_names array) |
||||
|
* \return A std::vector of Value objects that directly maps to the output_count (eg. output_name[0] is the first entry of the returned vector) |
||||
|
*/ |
||||
|
std::vector<Value> Run(const RunOptions& run_options, const char* const* input_names, const Value* input_values, size_t input_count, |
||||
|
const char* const* output_names, size_t output_count); |
||||
|
|
||||
|
/** \brief Run the model returning results in user provided outputs
|
||||
|
* Same as Run(const RunOptions&, const char* const*, const Value*, size_t,const char* const*, size_t) |
||||
|
*/ |
||||
|
void Run(const RunOptions& run_options, const char* const* input_names, const Value* input_values, size_t input_count, |
||||
|
const char* const* output_names, Value* output_values, size_t output_count); |
||||
|
|
||||
|
void Run(const RunOptions& run_options, const struct IoBinding&); ///< Wraps OrtApi::RunWithBinding
|
||||
|
|
||||
|
size_t GetInputCount() const; ///< Returns the number of model inputs
|
||||
|
size_t GetOutputCount() const; ///< Returns the number of model outputs
|
||||
|
size_t GetOverridableInitializerCount() const; ///< Returns the number of inputs that have defaults that can be overridden
|
||||
|
|
||||
|
char* GetInputName(size_t index, OrtAllocator* allocator) const; ///< Wraps OrtApi::SessionGetInputName
|
||||
|
char* GetOutputName(size_t index, OrtAllocator* allocator) const; ///< Wraps OrtApi::SessionGetOutputName
|
||||
|
char* GetOverridableInitializerName(size_t index, OrtAllocator* allocator) const; ///< Wraps OrtApi::SessionGetOverridableInitializerName
|
||||
|
char* EndProfiling(OrtAllocator* allocator) const; ///< Wraps OrtApi::SessionEndProfiling
|
||||
|
uint64_t GetProfilingStartTimeNs() const; ///< Wraps OrtApi::SessionGetProfilingStartTimeNs
|
||||
|
ModelMetadata GetModelMetadata() const; ///< Wraps OrtApi::SessionGetModelMetadata
|
||||
|
|
||||
|
TypeInfo GetInputTypeInfo(size_t index) const; ///< Wraps OrtApi::SessionGetInputTypeInfo
|
||||
|
TypeInfo GetOutputTypeInfo(size_t index) const; ///< Wraps OrtApi::SessionGetOutputTypeInfo
|
||||
|
TypeInfo GetOverridableInitializerTypeInfo(size_t index) const; ///< Wraps OrtApi::SessionGetOverridableInitializerTypeInfo
|
||||
|
}; |
||||
|
|
||||
|
/** \brief Wrapper around ::OrtTensorTypeAndShapeInfo
|
||||
|
* |
||||
|
*/ |
||||
|
struct TensorTypeAndShapeInfo : Base<OrtTensorTypeAndShapeInfo> { |
||||
|
explicit TensorTypeAndShapeInfo(std::nullptr_t) {} ///< Create an empty TensorTypeAndShapeInfo object, must be assigned a valid one to be used
|
||||
|
explicit TensorTypeAndShapeInfo(OrtTensorTypeAndShapeInfo* p) : Base<OrtTensorTypeAndShapeInfo>{p} {} ///< Used for interop with the C API
|
||||
|
|
||||
|
ONNXTensorElementDataType GetElementType() const; ///< Wraps OrtApi::GetTensorElementType
|
||||
|
size_t GetElementCount() const; ///< Wraps OrtApi::GetTensorShapeElementCount
|
||||
|
|
||||
|
size_t GetDimensionsCount() const; ///< Wraps OrtApi::GetDimensionsCount
|
||||
|
void GetDimensions(int64_t* values, size_t values_count) const; ///< Wraps OrtApi::GetDimensions
|
||||
|
void GetSymbolicDimensions(const char** values, size_t values_count) const; ///< Wraps OrtApi::GetSymbolicDimensions
|
||||
|
|
||||
|
std::vector<int64_t> GetShape() const; ///< Uses GetDimensionsCount & GetDimensions to return a std::vector of the shape
|
||||
|
}; |
||||
|
|
||||
|
/** \brief Wrapper around ::OrtSequenceTypeInfo
|
||||
|
* |
||||
|
*/ |
||||
|
struct SequenceTypeInfo : Base<OrtSequenceTypeInfo> { |
||||
|
explicit SequenceTypeInfo(std::nullptr_t) {} ///< Create an empty SequenceTypeInfo object, must be assigned a valid one to be used
|
||||
|
explicit SequenceTypeInfo(OrtSequenceTypeInfo* p) : Base<OrtSequenceTypeInfo>{p} {} ///< Used for interop with the C API
|
||||
|
|
||||
|
TypeInfo GetSequenceElementType() const; ///< Wraps OrtApi::GetSequenceElementType
|
||||
|
}; |
||||
|
|
||||
|
/** \brief Wrapper around ::OrtMapTypeInfo
|
||||
|
* |
||||
|
*/ |
||||
|
struct MapTypeInfo : Base<OrtMapTypeInfo> { |
||||
|
explicit MapTypeInfo(std::nullptr_t) {} ///< Create an empty MapTypeInfo object, must be assigned a valid one to be used
|
||||
|
explicit MapTypeInfo(OrtMapTypeInfo* p) : Base<OrtMapTypeInfo>{p} {} ///< Used for interop with the C API
|
||||
|
|
||||
|
ONNXTensorElementDataType GetMapKeyType() const; ///< Wraps OrtApi::GetMapKeyType
|
||||
|
TypeInfo GetMapValueType() const; ///< Wraps OrtApi::GetMapValueType
|
||||
|
}; |
||||
|
|
||||
|
struct TypeInfo : Base<OrtTypeInfo> { |
||||
|
explicit TypeInfo(std::nullptr_t) {} ///< Create an empty TypeInfo object, must be assigned a valid one to be used
|
||||
|
explicit TypeInfo(OrtTypeInfo* p) : Base<OrtTypeInfo>{p} {} ///< C API Interop
|
||||
|
|
||||
|
Unowned<TensorTypeAndShapeInfo> GetTensorTypeAndShapeInfo() const; ///< Wraps OrtApi::CastTypeInfoToTensorInfo
|
||||
|
Unowned<SequenceTypeInfo> GetSequenceTypeInfo() const; ///< Wraps OrtApi::CastTypeInfoToSequenceTypeInfo
|
||||
|
Unowned<MapTypeInfo> GetMapTypeInfo() const; ///< Wraps OrtApi::CastTypeInfoToMapTypeInfo
|
||||
|
|
||||
|
ONNXType GetONNXType() const; |
||||
|
}; |
||||
|
|
||||
|
struct Value : Base<OrtValue> { |
||||
|
// This structure is used to feed sparse tensor values
|
||||
|
// information for use with FillSparseTensor<Format>() API
|
||||
|
// if the data type for the sparse tensor values is numeric
|
||||
|
// use data.p_data, otherwise, use data.str pointer to feed
|
||||
|
// values. data.str is an array of const char* that are zero terminated.
|
||||
|
// number of strings in the array must match shape size.
|
||||
|
// For fully sparse tensors use shape {0} and set p_data/str
|
||||
|
// to nullptr.
|
||||
|
struct OrtSparseValuesParam { |
||||
|
const int64_t* values_shape; |
||||
|
size_t values_shape_len; |
||||
|
union { |
||||
|
const void* p_data; |
||||
|
const char** str; |
||||
|
} data; |
||||
|
}; |
||||
|
|
||||
|
// Provides a way to pass shape in a single
|
||||
|
// argument
|
||||
|
struct Shape { |
||||
|
const int64_t* shape; |
||||
|
size_t shape_len; |
||||
|
}; |
||||
|
|
||||
|
/// \brief Wraps OrtApi::CreateTensorWithDataAsOrtValue
|
||||
|
template <typename T> |
||||
|
static Value CreateTensor(const OrtMemoryInfo* info, T* p_data, size_t p_data_element_count, const int64_t* shape, size_t shape_len); |
||||
|
/// \brief Wraps OrtApi::CreateTensorWithDataAsOrtValue
|
||||
|
static Value CreateTensor(const OrtMemoryInfo* info, void* p_data, size_t p_data_byte_count, const int64_t* shape, size_t shape_len, |
||||
|
ONNXTensorElementDataType type); |
||||
|
|
||||
|
#if !defined(DISABLE_SPARSE_TENSORS) |
||||
|
/// <summary>
|
||||
|
/// This is a simple forwarding method to the other overload that helps deducing
|
||||
|
/// data type enum value from the type of the buffer.
|
||||
|
/// </summary>
|
||||
|
/// <typeparam name="T">numeric datatype. This API is not suitable for strings.</typeparam>
|
||||
|
/// <param name="info">Memory description where the user buffers reside (CPU vs GPU etc)</param>
|
||||
|
/// <param name="p_data">pointer to the user supplied buffer, use nullptr for fully sparse tensors</param>
|
||||
|
/// <param name="dense_shape">a would be dense shape of the tensor</param>
|
||||
|
/// <param name="values_shape">non zero values shape. Use a single 0 shape for fully sparse tensors.</param>
|
||||
|
/// <returns></returns>
|
||||
|
template <typename T> |
||||
|
static Value CreateSparseTensor(const OrtMemoryInfo* info, T* p_data, const Shape& dense_shape, |
||||
|
const Shape& values_shape); |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Creates an OrtValue instance containing SparseTensor. This constructs
|
||||
|
/// a sparse tensor that makes use of user allocated buffers. It does not make copies
|
||||
|
/// of the user provided data and does not modify it. The lifespan of user provided buffers should
|
||||
|
/// eclipse the life span of the resulting OrtValue. This call constructs an instance that only contain
|
||||
|
/// a pointer to non-zero values. To fully populate the sparse tensor call Use<Format>Indices() API below
|
||||
|
/// to supply a sparse format specific indices.
|
||||
|
/// This API is not suitable for string data. Use CreateSparseTensor() with allocator specified so strings
|
||||
|
/// can be properly copied into the allocated buffer.
|
||||
|
/// </summary>
|
||||
|
/// <param name="info">Memory description where the user buffers reside (CPU vs GPU etc)</param>
|
||||
|
/// <param name="p_data">pointer to the user supplied buffer, use nullptr for fully sparse tensors</param>
|
||||
|
/// <param name="dense_shape">a would be dense shape of the tensor</param>
|
||||
|
/// <param name="values_shape">non zero values shape. Use a single 0 shape for fully sparse tensors.</param>
|
||||
|
/// <param name="type">data type</param>
|
||||
|
/// <returns>Ort::Value instance containing SparseTensor</returns>
|
||||
|
static Value CreateSparseTensor(const OrtMemoryInfo* info, void* p_data, const Shape& dense_shape, |
||||
|
const Shape& values_shape, ONNXTensorElementDataType type); |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Supplies COO format specific indices and marks the contained sparse tensor as being a COO format tensor.
|
||||
|
/// Values are supplied with a CreateSparseTensor() API. The supplied indices are not copied and the user
|
||||
|
/// allocated buffers lifespan must eclipse that of the OrtValue.
|
||||
|
/// The location of the indices is assumed to be the same as specified by OrtMemoryInfo argument at the creation time.
|
||||
|
/// </summary>
|
||||
|
/// <param name="indices_data">pointer to the user allocated buffer with indices. Use nullptr for fully sparse tensors.</param>
|
||||
|
/// <param name="indices_num">number of indices entries. Use 0 for fully sparse tensors</param>
|
||||
|
void UseCooIndices(int64_t* indices_data, size_t indices_num); |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Supplies CSR format specific indices and marks the contained sparse tensor as being a CSR format tensor.
|
||||
|
/// Values are supplied with a CreateSparseTensor() API. The supplied indices are not copied and the user
|
||||
|
/// allocated buffers lifespan must eclipse that of the OrtValue.
|
||||
|
/// The location of the indices is assumed to be the same as specified by OrtMemoryInfo argument at the creation time.
|
||||
|
/// </summary>
|
||||
|
/// <param name="inner_data">pointer to the user allocated buffer with inner indices or nullptr for fully sparse tensors</param>
|
||||
|
/// <param name="inner_num">number of csr inner indices or 0 for fully sparse tensors</param>
|
||||
|
/// <param name="outer_data">pointer to the user allocated buffer with outer indices or nullptr for fully sparse tensors</param>
|
||||
|
/// <param name="outer_num">number of csr outer indices or 0 for fully sparse tensors</param>
|
||||
|
void UseCsrIndices(int64_t* inner_data, size_t inner_num, int64_t* outer_data, size_t outer_num); |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Supplies BlockSparse format specific indices and marks the contained sparse tensor as being a BlockSparse format tensor.
|
||||
|
/// Values are supplied with a CreateSparseTensor() API. The supplied indices are not copied and the user
|
||||
|
/// allocated buffers lifespan must eclipse that of the OrtValue.
|
||||
|
/// The location of the indices is assumed to be the same as specified by OrtMemoryInfo argument at the creation time.
|
||||
|
/// </summary>
|
||||
|
/// <param name="indices_shape">indices shape or a {0} for fully sparse</param>
|
||||
|
/// <param name="indices_data">user allocated buffer with indices or nullptr for fully spare tensors</param>
|
||||
|
void UseBlockSparseIndices(const Shape& indices_shape, int32_t* indices_data); |
||||
|
|
||||
|
#endif // !defined(DISABLE_SPARSE_TENSORS)
|
||||
|
|
||||
|
// \brief Wraps OrtApi::CreateTensorAsOrtValue
|
||||
|
template <typename T> |
||||
|
static Value CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len); |
||||
|
// \brief Wraps OrtApi::CreateTensorAsOrtValue
|
||||
|
static Value CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len, ONNXTensorElementDataType type); |
||||
|
|
||||
|
#if !defined(DISABLE_SPARSE_TENSORS) |
||||
|
/// <summary>
|
||||
|
/// This is a simple forwarding method the below CreateSparseTensor.
|
||||
|
/// This helps to specify data type enum in terms of C++ data type.
|
||||
|
/// Use CreateSparseTensor<T>
|
||||
|
/// </summary>
|
||||
|
/// <typeparam name="T">numeric data type only. String data enum must be specified explicitly.</typeparam>
|
||||
|
/// <param name="allocator">allocator to use</param>
|
||||
|
/// <param name="dense_shape">a would be dense shape of the tensor</param>
|
||||
|
/// <returns>Ort::Value</returns>
|
||||
|
template <typename T> |
||||
|
static Value CreateSparseTensor(OrtAllocator* allocator, const Shape& dense_shape); |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Creates an instance of OrtValue containing sparse tensor. The created instance has no data.
|
||||
|
/// The data must be supplied by on of the FillSparseTensor<Format>() methods that take both non-zero values
|
||||
|
/// and indices. The data will be copied into a buffer that would be allocated using the supplied allocator.
|
||||
|
/// Use this API to create OrtValues that contain sparse tensors with all supported data types including
|
||||
|
/// strings.
|
||||
|
/// </summary>
|
||||
|
/// <param name="allocator">allocator to use. The allocator lifespan must eclipse that of the resulting OrtValue</param>
|
||||
|
/// <param name="dense_shape">a would be dense shape of the tensor</param>
|
||||
|
/// <param name="type">data type</param>
|
||||
|
/// <returns>an instance of Ort::Value</returns>
|
||||
|
static Value CreateSparseTensor(OrtAllocator* allocator, const Shape& dense_shape, ONNXTensorElementDataType type); |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API will allocate memory using the allocator instance supplied to the CreateSparseTensor() API
|
||||
|
/// and copy the values and COO indices into it. If data_mem_info specifies that the data is located
|
||||
|
/// at difference device than the allocator, a X-device copy will be performed if possible.
|
||||
|
/// </summary>
|
||||
|
/// <param name="data_mem_info">specified buffer memory description</param>
|
||||
|
/// <param name="values_param">values buffer information.</param>
|
||||
|
/// <param name="indices_data">coo indices buffer or nullptr for fully sparse data</param>
|
||||
|
/// <param name="indices_num">number of COO indices or 0 for fully sparse data</param>
|
||||
|
void FillSparseTensorCoo(const OrtMemoryInfo* data_mem_info, const OrtSparseValuesParam& values_param, |
||||
|
const int64_t* indices_data, size_t indices_num); |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API will allocate memory using the allocator instance supplied to the CreateSparseTensor() API
|
||||
|
/// and copy the values and CSR indices into it. If data_mem_info specifies that the data is located
|
||||
|
/// at difference device than the allocator, a X-device copy will be performed if possible.
|
||||
|
/// </summary>
|
||||
|
/// <param name="data_mem_info">specified buffer memory description</param>
|
||||
|
/// <param name="values">values buffer information</param>
|
||||
|
/// <param name="inner_indices_data">csr inner indices pointer or nullptr for fully sparse tensors</param>
|
||||
|
/// <param name="inner_indices_num">number of csr inner indices or 0 for fully sparse tensors</param>
|
||||
|
/// <param name="outer_indices_data">pointer to csr indices data or nullptr for fully sparse tensors</param>
|
||||
|
/// <param name="outer_indices_num">number of csr outer indices or 0</param>
|
||||
|
void FillSparseTensorCsr(const OrtMemoryInfo* data_mem_info, |
||||
|
const OrtSparseValuesParam& values, |
||||
|
const int64_t* inner_indices_data, size_t inner_indices_num, |
||||
|
const int64_t* outer_indices_data, size_t outer_indices_num); |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API will allocate memory using the allocator instance supplied to the CreateSparseTensor() API
|
||||
|
/// and copy the values and BlockSparse indices into it. If data_mem_info specifies that the data is located
|
||||
|
/// at difference device than the allocator, a X-device copy will be performed if possible.
|
||||
|
/// </summary>
|
||||
|
/// <param name="data_mem_info">specified buffer memory description</param>
|
||||
|
/// <param name="values">values buffer information</param>
|
||||
|
/// <param name="indices_shape">indices shape. use {0} for fully sparse tensors</param>
|
||||
|
/// <param name="indices_data">pointer to indices data or nullptr for fully sparse tensors</param>
|
||||
|
void FillSparseTensorBlockSparse(const OrtMemoryInfo* data_mem_info, |
||||
|
const OrtSparseValuesParam& values, |
||||
|
const Shape& indices_shape, |
||||
|
const int32_t* indices_data); |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API returns the sparse data format this OrtValue holds in a sparse tensor.
|
||||
|
/// If the sparse tensor was not fully constructed, i.e. Use*() or Fill*() API were not used
|
||||
|
/// the value returned is ORT_SPARSE_UNDEFINED.
|
||||
|
/// </summary>
|
||||
|
/// <returns>Format enum</returns>
|
||||
|
OrtSparseFormat GetSparseFormat() const; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API returns type and shape information for stored non-zero values of the
|
||||
|
/// sparse tensor. Use GetSparseTensorValues() to obtain values buffer pointer.
|
||||
|
/// </summary>
|
||||
|
/// <returns>TensorTypeAndShapeInfo values information</returns>
|
||||
|
TensorTypeAndShapeInfo GetSparseTensorValuesTypeAndShapeInfo() const; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API returns type and shape information for the specified indices. Each supported
|
||||
|
/// indices have their own enum values even if a give format has more than one kind of indices.
|
||||
|
/// Use GetSparseTensorIndicesData() to obtain pointer to indices buffer.
|
||||
|
/// </summary>
|
||||
|
/// <param name="format">enum requested</param>
|
||||
|
/// <returns>type and shape information</returns>
|
||||
|
TensorTypeAndShapeInfo GetSparseTensorIndicesTypeShapeInfo(OrtSparseIndicesFormat format) const; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API retrieves a pointer to the internal indices buffer. The API merely performs
|
||||
|
/// a convenience data type casting on the return type pointer. Make sure you are requesting
|
||||
|
/// the right type, use GetSparseTensorIndicesTypeShapeInfo();
|
||||
|
/// </summary>
|
||||
|
/// <typeparam name="T">type to cast to</typeparam>
|
||||
|
/// <param name="indices_format">requested indices kind</param>
|
||||
|
/// <param name="num_indices">number of indices entries</param>
|
||||
|
/// <returns>Pinter to the internal sparse tensor buffer containing indices. Do not free this pointer.</returns>
|
||||
|
template <typename T> |
||||
|
const T* GetSparseTensorIndicesData(OrtSparseIndicesFormat indices_format, size_t& num_indices) const; |
||||
|
|
||||
|
#endif // !defined(DISABLE_SPARSE_TENSORS)
|
||||
|
|
||||
|
static Value CreateMap(Value& keys, Value& values); ///< Wraps OrtApi::CreateValue
|
||||
|
static Value CreateSequence(std::vector<Value>& values); ///< Wraps OrtApi::CreateValue
|
||||
|
|
||||
|
template <typename T> |
||||
|
static Value CreateOpaque(const char* domain, const char* type_name, const T&); ///< Wraps OrtApi::CreateOpaqueValue
|
||||
|
|
||||
|
template <typename T> |
||||
|
void GetOpaqueData(const char* domain, const char* type_name, T&) const; ///< Wraps OrtApi::GetOpaqueValue
|
||||
|
|
||||
|
explicit Value(std::nullptr_t) {} ///< Create an empty Value object, must be assigned a valid one to be used
|
||||
|
explicit Value(OrtValue* p) : Base<OrtValue>{p} {} ///< Used for interop with the C API
|
||||
|
Value(Value&&) = default; |
||||
|
Value& operator=(Value&&) = default; |
||||
|
|
||||
|
bool IsTensor() const; ///< Returns true if Value is a tensor, false for other types like map/sequence/etc
|
||||
|
bool HasValue() const; /// < Return true if OrtValue contains data and returns false if the OrtValue is a None
|
||||
|
|
||||
|
#if !defined(DISABLE_SPARSE_TENSORS) |
||||
|
/// <summary>
|
||||
|
/// Returns true if the OrtValue contains a sparse tensor
|
||||
|
/// </summary>
|
||||
|
/// <returns></returns>
|
||||
|
bool IsSparseTensor() const; |
||||
|
#endif |
||||
|
|
||||
|
size_t GetCount() const; // If a non tensor, returns 2 for map and N for sequence, where N is the number of elements
|
||||
|
Value GetValue(int index, OrtAllocator* allocator) const; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// This API returns a full length of string data contained within either a tensor or a sparse Tensor.
|
||||
|
/// For sparse tensor it returns a full length of stored non-empty strings (values). The API is useful
|
||||
|
/// for allocating necessary memory and calling GetStringTensorContent().
|
||||
|
/// </summary>
|
||||
|
/// <returns>total length of UTF-8 encoded bytes contained. No zero terminators counted.</returns>
|
||||
|
size_t GetStringTensorDataLength() const; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API copies all of the UTF-8 encoded string data contained within a tensor or a sparse tensor
|
||||
|
/// into a supplied buffer. Use GetStringTensorDataLength() to find out the length of the buffer to allocate.
|
||||
|
/// The user must also allocate offsets buffer with the number of entries equal to that of the contained
|
||||
|
/// strings.
|
||||
|
///
|
||||
|
/// Strings are always assumed to be on CPU, no X-device copy.
|
||||
|
/// </summary>
|
||||
|
/// <param name="buffer">user allocated buffer</param>
|
||||
|
/// <param name="buffer_length">length in bytes of the allocated buffer</param>
|
||||
|
/// <param name="offsets">a pointer to the offsets user allocated buffer</param>
|
||||
|
/// <param name="offsets_count">count of offsets, must be equal to the number of strings contained.
|
||||
|
/// that can be obtained from the shape of the tensor or from GetSparseTensorValuesTypeAndShapeInfo()
|
||||
|
/// for sparse tensors</param>
|
||||
|
void GetStringTensorContent(void* buffer, size_t buffer_length, size_t* offsets, size_t offsets_count) const; |
||||
|
|
||||
|
template <typename T> |
||||
|
T* GetTensorMutableData(); ///< Wraps OrtApi::GetTensorMutableData
|
||||
|
|
||||
|
template <typename T> |
||||
|
const T* GetTensorData() const; ///< Wraps OrtApi::GetTensorMutableData
|
||||
|
|
||||
|
#if !defined(DISABLE_SPARSE_TENSORS) |
||||
|
/// <summary>
|
||||
|
/// The API returns a pointer to an internal buffer of the sparse tensor
|
||||
|
/// containing non-zero values. The API merely does casting. Make sure you
|
||||
|
/// are requesting the right data type by calling GetSparseTensorValuesTypeAndShapeInfo()
|
||||
|
/// first.
|
||||
|
/// </summary>
|
||||
|
/// <typeparam name="T">numeric data types only. Use GetStringTensor*() to retrieve strings.</typeparam>
|
||||
|
/// <returns>a pointer to the internal values buffer. Do not free this pointer.</returns>
|
||||
|
template <typename T> |
||||
|
const T* GetSparseTensorValues() const; |
||||
|
#endif |
||||
|
|
||||
|
template <typename T> |
||||
|
T& At(const std::vector<int64_t>& location); |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API returns type information for data contained in a tensor. For sparse
|
||||
|
/// tensors it returns type information for contained non-zero values.
|
||||
|
/// It returns dense shape for sparse tensors.
|
||||
|
/// </summary>
|
||||
|
/// <returns>TypeInfo</returns>
|
||||
|
TypeInfo GetTypeInfo() const; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API returns type information for data contained in a tensor. For sparse
|
||||
|
/// tensors it returns type information for contained non-zero values.
|
||||
|
/// It returns dense shape for sparse tensors.
|
||||
|
/// </summary>
|
||||
|
/// <returns>TensorTypeAndShapeInfo</returns>
|
||||
|
TensorTypeAndShapeInfo GetTensorTypeAndShapeInfo() const; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API returns a byte length of UTF-8 encoded string element
|
||||
|
/// contained in either a tensor or a spare tensor values.
|
||||
|
/// </summary>
|
||||
|
/// <param name="element_index"></param>
|
||||
|
/// <returns>byte length for the specified string element</returns>
|
||||
|
size_t GetStringTensorElementLength(size_t element_index) const; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// The API copies UTF-8 encoded bytes for the requested string element
|
||||
|
/// contained within a tensor or a sparse tensor into a provided buffer.
|
||||
|
/// Use GetStringTensorElementLength() to obtain the length of the buffer to allocate.
|
||||
|
/// </summary>
|
||||
|
/// <param name="buffer_length"></param>
|
||||
|
/// <param name="element_index"></param>
|
||||
|
/// <param name="buffer"></param>
|
||||
|
void GetStringTensorElement(size_t buffer_length, size_t element_index, void* buffer) const; |
||||
|
|
||||
|
void FillStringTensor(const char* const* s, size_t s_len); |
||||
|
void FillStringTensorElement(const char* s, size_t index); |
||||
|
}; |
||||
|
|
||||
|
// Represents native memory allocation
|
||||
|
struct MemoryAllocation { |
||||
|
MemoryAllocation(OrtAllocator* allocator, void* p, size_t size); |
||||
|
~MemoryAllocation(); |
||||
|
MemoryAllocation(const MemoryAllocation&) = delete; |
||||
|
MemoryAllocation& operator=(const MemoryAllocation&) = delete; |
||||
|
MemoryAllocation(MemoryAllocation&&) noexcept; |
||||
|
MemoryAllocation& operator=(MemoryAllocation&&) noexcept; |
||||
|
|
||||
|
void* get() { return p_; } |
||||
|
size_t size() const { return size_; } |
||||
|
|
||||
|
private: |
||||
|
OrtAllocator* allocator_; |
||||
|
void* p_; |
||||
|
size_t size_; |
||||
|
}; |
||||
|
|
||||
|
struct AllocatorWithDefaultOptions { |
||||
|
AllocatorWithDefaultOptions(); |
||||
|
|
||||
|
operator OrtAllocator*() { return p_; } |
||||
|
operator const OrtAllocator*() const { return p_; } |
||||
|
|
||||
|
void* Alloc(size_t size); |
||||
|
// The return value will own the allocation
|
||||
|
MemoryAllocation GetAllocation(size_t size); |
||||
|
void Free(void* p); |
||||
|
|
||||
|
const OrtMemoryInfo* GetInfo() const; |
||||
|
|
||||
|
private: |
||||
|
OrtAllocator* p_{}; |
||||
|
}; |
||||
|
|
||||
|
struct MemoryInfo : Base<OrtMemoryInfo> { |
||||
|
static MemoryInfo CreateCpu(OrtAllocatorType type, OrtMemType mem_type1); |
||||
|
|
||||
|
explicit MemoryInfo(std::nullptr_t) {} |
||||
|
explicit MemoryInfo(OrtMemoryInfo* p) : Base<OrtMemoryInfo>{p} {} ///< Used for interop with the C API
|
||||
|
MemoryInfo(const char* name, OrtAllocatorType type, int id, OrtMemType mem_type); |
||||
|
|
||||
|
std::string GetAllocatorName() const; |
||||
|
OrtAllocatorType GetAllocatorType() const; |
||||
|
int GetDeviceId() const; |
||||
|
OrtMemType GetMemoryType() const; |
||||
|
|
||||
|
bool operator==(const MemoryInfo& o) const; |
||||
|
}; |
||||
|
|
||||
|
struct Allocator : public Base<OrtAllocator> { |
||||
|
Allocator(const Session& session, const MemoryInfo&); |
||||
|
|
||||
|
void* Alloc(size_t size) const; |
||||
|
// The return value will own the allocation
|
||||
|
MemoryAllocation GetAllocation(size_t size); |
||||
|
void Free(void* p) const; |
||||
|
Unowned<const MemoryInfo> GetInfo() const; |
||||
|
}; |
||||
|
|
||||
|
struct IoBinding : public Base<OrtIoBinding> { |
||||
|
explicit IoBinding(Session& session); |
||||
|
void BindInput(const char* name, const Value&); |
||||
|
void BindOutput(const char* name, const Value&); |
||||
|
void BindOutput(const char* name, const MemoryInfo&); |
||||
|
std::vector<std::string> GetOutputNames() const; |
||||
|
std::vector<std::string> GetOutputNames(Allocator&) const; |
||||
|
std::vector<Value> GetOutputValues() const; |
||||
|
std::vector<Value> GetOutputValues(Allocator&) const; |
||||
|
void ClearBoundInputs(); |
||||
|
void ClearBoundOutputs(); |
||||
|
void SynchronizeInputs(); |
||||
|
void SynchronizeOutputs(); |
||||
|
|
||||
|
private: |
||||
|
std::vector<std::string> GetOutputNamesHelper(OrtAllocator*) const; |
||||
|
std::vector<Value> GetOutputValuesHelper(OrtAllocator*) const; |
||||
|
}; |
||||
|
|
||||
|
/*! \struct Ort::ArenaCfg
|
||||
|
* \brief it is a structure that represents the configuration of an arena based allocator |
||||
|
* \details Please see docs/C_API.md for details |
||||
|
*/ |
||||
|
struct ArenaCfg : Base<OrtArenaCfg> { |
||||
|
explicit ArenaCfg(std::nullptr_t) {} ///< Create an empty ArenaCfg object, must be assigned a valid one to be used
|
||||
|
/**
|
||||
|
* Wraps OrtApi::CreateArenaCfg |
||||
|
* \param max_mem - use 0 to allow ORT to choose the default |
||||
|
* \param arena_extend_strategy - use -1 to allow ORT to choose the default, 0 = kNextPowerOfTwo, 1 = kSameAsRequested |
||||
|
* \param initial_chunk_size_bytes - use -1 to allow ORT to choose the default |
||||
|
* \param max_dead_bytes_per_chunk - use -1 to allow ORT to choose the default |
||||
|
* See docs/C_API.md for details on what the following parameters mean and how to choose these values |
||||
|
*/ |
||||
|
ArenaCfg(size_t max_mem, int arena_extend_strategy, int initial_chunk_size_bytes, int max_dead_bytes_per_chunk); |
||||
|
}; |
||||
|
|
||||
|
//
|
||||
|
// Custom OPs (only needed to implement custom OPs)
|
||||
|
//
|
||||
|
|
||||
|
struct CustomOpApi { |
||||
|
CustomOpApi(const OrtApi& api) : api_(api) {} |
||||
|
|
||||
|
template <typename T> // T is only implemented for std::vector<float>, std::vector<int64_t>, float, int64_t, and string
|
||||
|
T KernelInfoGetAttribute(_In_ const OrtKernelInfo* info, _In_ const char* name); |
||||
|
|
||||
|
OrtTensorTypeAndShapeInfo* GetTensorTypeAndShape(_In_ const OrtValue* value); |
||||
|
size_t GetTensorShapeElementCount(_In_ const OrtTensorTypeAndShapeInfo* info); |
||||
|
ONNXTensorElementDataType GetTensorElementType(const OrtTensorTypeAndShapeInfo* info); |
||||
|
size_t GetDimensionsCount(_In_ const OrtTensorTypeAndShapeInfo* info); |
||||
|
void GetDimensions(_In_ const OrtTensorTypeAndShapeInfo* info, _Out_ int64_t* dim_values, size_t dim_values_length); |
||||
|
void SetDimensions(OrtTensorTypeAndShapeInfo* info, _In_ const int64_t* dim_values, size_t dim_count); |
||||
|
|
||||
|
template <typename T> |
||||
|
T* GetTensorMutableData(_Inout_ OrtValue* value); |
||||
|
template <typename T> |
||||
|
const T* GetTensorData(_Inout_ const OrtValue* value); |
||||
|
|
||||
|
const OrtMemoryInfo* GetTensorMemoryInfo(_In_ const OrtValue* value); |
||||
|
|
||||
|
std::vector<int64_t> GetTensorShape(const OrtTensorTypeAndShapeInfo* info); |
||||
|
void ReleaseTensorTypeAndShapeInfo(OrtTensorTypeAndShapeInfo* input); |
||||
|
size_t KernelContext_GetInputCount(const OrtKernelContext* context); |
||||
|
const OrtValue* KernelContext_GetInput(const OrtKernelContext* context, _In_ size_t index); |
||||
|
size_t KernelContext_GetOutputCount(const OrtKernelContext* context); |
||||
|
OrtValue* KernelContext_GetOutput(OrtKernelContext* context, _In_ size_t index, _In_ const int64_t* dim_values, size_t dim_count); |
||||
|
void* KernelContext_GetGPUComputeStream(const OrtKernelContext* context); |
||||
|
|
||||
|
void ThrowOnError(OrtStatus* result); |
||||
|
|
||||
|
private: |
||||
|
const OrtApi& api_; |
||||
|
}; |
||||
|
|
||||
|
template <typename TOp, typename TKernel> |
||||
|
struct CustomOpBase : OrtCustomOp { |
||||
|
CustomOpBase() { |
||||
|
OrtCustomOp::version = ORT_API_VERSION; |
||||
|
OrtCustomOp::CreateKernel = [](const OrtCustomOp* this_, const OrtApi* api, const OrtKernelInfo* info) { return static_cast<const TOp*>(this_)->CreateKernel(*api, info); }; |
||||
|
OrtCustomOp::GetName = [](const OrtCustomOp* this_) { return static_cast<const TOp*>(this_)->GetName(); }; |
||||
|
|
||||
|
OrtCustomOp::GetExecutionProviderType = [](const OrtCustomOp* this_) { return static_cast<const TOp*>(this_)->GetExecutionProviderType(); }; |
||||
|
|
||||
|
OrtCustomOp::GetInputTypeCount = [](const OrtCustomOp* this_) { return static_cast<const TOp*>(this_)->GetInputTypeCount(); }; |
||||
|
OrtCustomOp::GetInputType = [](const OrtCustomOp* this_, size_t index) { return static_cast<const TOp*>(this_)->GetInputType(index); }; |
||||
|
|
||||
|
OrtCustomOp::GetOutputTypeCount = [](const OrtCustomOp* this_) { return static_cast<const TOp*>(this_)->GetOutputTypeCount(); }; |
||||
|
OrtCustomOp::GetOutputType = [](const OrtCustomOp* this_, size_t index) { return static_cast<const TOp*>(this_)->GetOutputType(index); }; |
||||
|
|
||||
|
OrtCustomOp::KernelCompute = [](void* op_kernel, OrtKernelContext* context) { static_cast<TKernel*>(op_kernel)->Compute(context); }; |
||||
|
OrtCustomOp::KernelDestroy = [](void* op_kernel) { delete static_cast<TKernel*>(op_kernel); }; |
||||
|
|
||||
|
OrtCustomOp::GetInputCharacteristic = [](const OrtCustomOp* this_, size_t index) { return static_cast<const TOp*>(this_)->GetInputCharacteristic(index); }; |
||||
|
OrtCustomOp::GetOutputCharacteristic = [](const OrtCustomOp* this_, size_t index) { return static_cast<const TOp*>(this_)->GetOutputCharacteristic(index); }; |
||||
|
} |
||||
|
|
||||
|
// Default implementation of GetExecutionProviderType that returns nullptr to default to the CPU provider
|
||||
|
const char* GetExecutionProviderType() const { return nullptr; } |
||||
|
|
||||
|
// Default implementations of GetInputCharacteristic() and GetOutputCharacteristic() below
|
||||
|
// (inputs and outputs are required by default)
|
||||
|
OrtCustomOpInputOutputCharacteristic GetInputCharacteristic(size_t /*index*/) const { |
||||
|
return OrtCustomOpInputOutputCharacteristic::INPUT_OUTPUT_REQUIRED; |
||||
|
} |
||||
|
|
||||
|
OrtCustomOpInputOutputCharacteristic GetOutputCharacteristic(size_t /*index*/) const { |
||||
|
return OrtCustomOpInputOutputCharacteristic::INPUT_OUTPUT_REQUIRED; |
||||
|
} |
||||
|
}; |
||||
|
|
||||
|
} // namespace Ort
|
||||
|
|
||||
|
#include "onnxruntime_cxx_inline.h" |
||||
File diff suppressed because it is too large
@ -0,0 +1,27 @@ |
|||||
|
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
|
// Licensed under the MIT License.
|
||||
|
|
||||
|
#pragma once |
||||
|
|
||||
|
/*
|
||||
|
* This file defines RunOptions Config Keys and format of the Config Values. |
||||
|
* |
||||
|
* The Naming Convention for a RunOptions Config Key, |
||||
|
* "[Area][.[SubArea1].[SubArea2]...].[Keyname]" |
||||
|
* Such as "ep.cuda.use_arena" |
||||
|
* The Config Key cannot be empty |
||||
|
* The maximum length of the Config Key is 128 |
||||
|
* |
||||
|
* The string format of a RunOptions Config Value is defined individually for each Config. |
||||
|
* The maximum length of the Config Value is 1024 |
||||
|
*/ |
||||
|
|
||||
|
// Key for enabling shrinkages of user listed device memory arenas.
|
||||
|
// Expects a list of semi-colon separated key value pairs separated by colon in the following format:
|
||||
|
// "device_0:device_id_0;device_1:device_id_1"
|
||||
|
// No white-spaces allowed in the provided list string.
|
||||
|
// Currently, the only supported devices are : "cpu", "gpu" (case sensitive).
|
||||
|
// If "cpu" is included in the list, DisableCpuMemArena() API must not be called (i.e.) arena for cpu should be enabled.
|
||||
|
// Example usage: "cpu:0;gpu:0" (or) "gpu:0"
|
||||
|
// By default, the value for this key is empty (i.e.) no memory arenas are shrunk
|
||||
|
static const char* const kOrtRunOptionsConfigEnableMemoryArenaShrinkage = "memory.enable_memory_arena_shrinkage"; |
||||
@ -0,0 +1,98 @@ |
|||||
|
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
|
// Licensed under the MIT License.
|
||||
|
|
||||
|
#pragma once |
||||
|
|
||||
|
/*
|
||||
|
* This file defines SessionOptions Config Keys and format of the Config Values. |
||||
|
* |
||||
|
* The Naming Convention for a SessionOptions Config Key, |
||||
|
* "[Area][.[SubArea1].[SubArea2]...].[Keyname]" |
||||
|
* Such as "ep.cuda.use_arena" |
||||
|
* The Config Key cannot be empty |
||||
|
* The maximum length of the Config Key is 128 |
||||
|
* |
||||
|
* The string format of a SessionOptions Config Value is defined individually for each Config. |
||||
|
* The maximum length of the Config Value is 1024 |
||||
|
*/ |
||||
|
|
||||
|
// Key for disable PrePacking,
|
||||
|
// If the config value is set to "1" then the prepacking is disabled, otherwise prepacking is enabled (default value)
|
||||
|
static const char* const kOrtSessionOptionsConfigDisablePrepacking = "session.disable_prepacking"; |
||||
|
|
||||
|
// A value of "1" means allocators registered in the env will be used. "0" means the allocators created in the session
|
||||
|
// will be used. Use this to override the usage of env allocators on a per session level.
|
||||
|
static const char* const kOrtSessionOptionsConfigUseEnvAllocators = "session.use_env_allocators"; |
||||
|
|
||||
|
// Set to 'ORT' (case sensitive) to load an ORT format model.
|
||||
|
// If unset, model type will default to ONNX unless inferred from filename ('.ort' == ORT format) or bytes to be ORT
|
||||
|
static const char* const kOrtSessionOptionsConfigLoadModelFormat = "session.load_model_format"; |
||||
|
|
||||
|
// Set to 'ORT' (case sensitive) to save optimized model in ORT format when SessionOptions.optimized_model_path is set.
|
||||
|
// If unset, format will default to ONNX unless optimized_model_filepath ends in '.ort'.
|
||||
|
static const char* const kOrtSessionOptionsConfigSaveModelFormat = "session.save_model_format"; |
||||
|
|
||||
|
// If a value is "1", flush-to-zero and denormal-as-zero are applied. The default is "0".
|
||||
|
// When multiple sessions are created, a main thread doesn't override changes from succeeding session options,
|
||||
|
// but threads in session thread pools follow option changes.
|
||||
|
// When ORT runs with OpenMP, the same rule is applied, i.e. the first session option to flush-to-zero and
|
||||
|
// denormal-as-zero is only applied to global OpenMP thread pool, which doesn't support per-session thread pool.
|
||||
|
// Note that an alternative way not using this option at runtime is to train and export a model without denormals
|
||||
|
// and that's recommended because turning this option on may hurt model accuracy.
|
||||
|
static const char* const kOrtSessionOptionsConfigSetDenormalAsZero = "session.set_denormal_as_zero"; |
||||
|
|
||||
|
// It controls to run quantization model in QDQ (QuantizelinearDeQuantizelinear) format or not.
|
||||
|
// "0": enable. ORT does fusion logic for QDQ format.
|
||||
|
// "1": disable. ORT doesn't do fusion logic for QDQ format.
|
||||
|
// Its default value is "0"
|
||||
|
static const char* const kOrtSessionOptionsDisableQuantQDQ = "session.disable_quant_qdq"; |
||||
|
|
||||
|
// Enable or disable gelu approximation in graph optimization. "0": disable; "1": enable. The default is "0".
|
||||
|
// GeluApproximation has side effects which may change the inference results. It is disabled by default due to this.
|
||||
|
static const char* const kOrtSessionOptionsEnableGeluApproximation = "optimization.enable_gelu_approximation"; |
||||
|
|
||||
|
// Enable or disable using device allocator for allocating initialized tensor memory. "1": enable; "0": disable. The default is "0".
|
||||
|
// Using device allocators means the memory allocation is made using malloc/new.
|
||||
|
static const char* const kOrtSessionOptionsUseDeviceAllocatorForInitializers = "session.use_device_allocator_for_initializers"; |
||||
|
|
||||
|
// Configure whether to allow the inter_op/intra_op threads spinning a number of times before blocking
|
||||
|
// "0": thread will block if found no job to run
|
||||
|
// "1": default, thread will spin a number of times before blocking
|
||||
|
static const char* const kOrtSessionOptionsConfigAllowInterOpSpinning = "session.inter_op.allow_spinning"; |
||||
|
static const char* const kOrtSessionOptionsConfigAllowIntraOpSpinning = "session.intra_op.allow_spinning"; |
||||
|
|
||||
|
// Key for using model bytes directly for ORT format
|
||||
|
// If a session is created using an input byte array contains the ORT format model data,
|
||||
|
// By default we will copy the model bytes at the time of session creation to ensure the model bytes
|
||||
|
// buffer is valid.
|
||||
|
// Setting this option to "1" will disable copy the model bytes, and use the model bytes directly. The caller
|
||||
|
// has to guarantee that the model bytes are valid until the ORT session using the model bytes is destroyed.
|
||||
|
static const char* const kOrtSessionOptionsConfigUseORTModelBytesDirectly = "session.use_ort_model_bytes_directly"; |
||||
|
|
||||
|
// Save information for replaying graph optimizations later instead of applying them directly.
|
||||
|
//
|
||||
|
// When an ONNX model is loaded, ORT can perform various optimizations on the graph.
|
||||
|
// However, when an ORT format model is loaded, these optimizations are typically not available - this scenario must
|
||||
|
// be supported by minimal builds.
|
||||
|
// When loading an ONNX model, ORT can optionally save the effects of some optimizations for later replay in an ORT
|
||||
|
// format model. These are known as "runtime optimizations" - in an ORT format model, they happen at runtime.
|
||||
|
//
|
||||
|
// Note: This option is only applicable when loading an ONNX model and saving an ORT format model.
|
||||
|
//
|
||||
|
// Note: Runtime optimizations are only supported for certain optimizations at the extended level or higher.
|
||||
|
// Unsupported optimizations at those levels are not applied at all, while optimizations at other levels are applied
|
||||
|
// directly.
|
||||
|
//
|
||||
|
// "0": disabled, "1": enabled
|
||||
|
// The default is "0".
|
||||
|
static const char* const kOrtSessionOptionsConfigSaveRuntimeOptimizations = "optimization.save_runtime_optimizations"; |
||||
|
|
||||
|
// Note: The options specific to an EP should be specified prior to appending that EP to the session options object in
|
||||
|
// order for them to take effect.
|
||||
|
|
||||
|
// Specifies a list of stop op types. Nodes of a type in the stop op types and nodes downstream from them will not be
|
||||
|
// run by the NNAPI EP.
|
||||
|
// The value should be a ","-delimited list of op types. For example, "Add,Sub".
|
||||
|
// If not specified, the default set of stop ops is used. To specify an empty stop ops types list and disable stop op
|
||||
|
// exclusion, set the value to "".
|
||||
|
static const char* const kOrtSessionOptionsConfigNnapiEpPartitioningStopOps = "ep.nnapi.partitioning_stop_ops"; |
||||
@ -0,0 +1,18 @@ |
|||||
|
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
|
// Licensed under the MIT License.
|
||||
|
|
||||
|
#pragma once |
||||
|
|
||||
|
#include <string> |
||||
|
#include <unordered_map> |
||||
|
#include <vector> |
||||
|
|
||||
|
namespace onnxruntime { |
||||
|
|
||||
|
// data types for execution provider options
|
||||
|
|
||||
|
using ProviderOptions = std::unordered_map<std::string, std::string>; |
||||
|
using ProviderOptionsVector = std::vector<ProviderOptions>; |
||||
|
using ProviderOptionsMap = std::unordered_map<std::string, ProviderOptions>; |
||||
|
|
||||
|
} // namespace onnxruntime
|
||||
@ -0,0 +1,14 @@ |
|||||
|
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
|
// Licensed under the MIT License.
|
||||
|
|
||||
|
#include "onnxruntime_c_api.h" |
||||
|
|
||||
|
#ifdef __cplusplus |
||||
|
extern "C" { |
||||
|
#endif |
||||
|
|
||||
|
ORT_API_STATUS(OrtSessionOptionsAppendExecutionProvider_Tensorrt, _In_ OrtSessionOptions* options, int device_id); |
||||
|
|
||||
|
#ifdef __cplusplus |
||||
|
} |
||||
|
#endif |
||||
Binary file not shown.
@ -0,0 +1,3 @@ |
|||||
|
#pragma once |
||||
|
|
||||
|
#include <onnxruntime_cxx_api.h> |
||||
Loading…
Reference in new issue