WindowsAI build failing due to deprecated .NET5 SDK missing in build
image
.NET5 was deprecated last year, and recently the build machine images
have been updated to not include this SDK.
Unblock failing builds by force insalling .NET5 SDK as part of the build
pipeline.
### Description
Add sbyte specific test case support.
### Motivation and Context
C# Test Data loading code and comparators are missing sbyte (Int8)
specializations.
This fails a test
### Description
<!-- Describe your changes. -->
I fixed some broken links in the C API documentation, but then did a
quick pass over all of the links I could find and then fixed those.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
I got some 404's when exploring the documentation and wanted to fix it.
### Description
Reenable disabled opset18 tests
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
Re-work `OrtApi::GetAvailableProviders` in a way that the data is
returned in a single allocation.
Fix exception safety issues and fix `Release` function.
Remove warning suppressions.
Fix exception safety issue in C++ API.
Fix exception safety issue in C# API.
Move EP name length enforcement to the implementation.
### Motivation and Context
The original motivation comes from
https://github.com/microsoft/onnxruntime/issues/14378.
However, the API is already implemented.
Cc: @prabhat00155
### Description
<!-- Describe your changes. -->
Remove exclusions for ONNX model tests that now pass due to kernels
being implemented.
Update ONNX update doc to point to correct location for tests.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Run as many tests as possible.
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
### Description
To Implement Resize 18.
This PR depends on https://github.com/microsoft/onnxruntime/pull/13765.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
<!-- Describe your changes. -->
Skip tests for opset18 models that we haven't implemented kernels for
yet.
Slice was checked in today so those failures should go away.
Resize: #13890 (all resize failures are fixed by this PR as confirmed in
output
[here](https://dev.azure.com/aiinfra/530acbc4-21bc-487d-8cd8-348ff451d2ff/_apis/build/builds/264725/logs/729))
Col2Im: #12311
ScatterND and ScatterElement: #14224
Pad (should also fix CenterCropPad failures): #14219 Bitwise ops: #14197
Optional: Unknown if we're intending to support this in 1.14
Not sure about SoftPlus as that is failing due to `Could not find an
implementation for Exp(1)`. ORT supports Exp from opset 6 and on, and it
seems incorrect for the test model created for opset 18 to be using a
version of Exp that is so old. Would have expected it to use the latest
- Exp(13). @liqunfu is this something that requires a fix to the ONNX
model?
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Fix pipeline
### Description
Enable creating dedicated build for on device training. With this PR we
can build a lean binary for on device training using flag
--enable_training_apis. This binary includes only the essentials like
training ops, optimizers etc and NOT features like Aten fallback,
strided tensors, gradient builders etc . This binary also removes all
the deprecated components like training::TrainingSession and OrtTrainer
etc
### Motivation and Context
This enables our partners to create a lean binary for on device
training.
### Description
1. Renames all references of on device training to training apis. This
is to keep the naming general. Nothing really prevents us from using the
same apis on servers\non-edge devices.
2. Update ENABLE_TRAINING option: With this PR when this option is
enabled, training apis and torch interop is also enabled.
3. Refactoring for onnxruntime_ENABLE_TRAINING_TORCH_INTEROP option:
- Removed user facing option
- Setting onnxruntime_ENABLE_TRAINING_TORCH_INTEROP to ON when
onnxruntime_ENABLE_TRAINING is ON as we always build with torch interop.
Once this PR is merged when --enable_training is selected we will do a
"FULL Build" for training (with all the training entry points and
features).
Training entry points include:
1. ORTModule
2. Training APIs
Features include:
1. ATen Fallback
2. All Training OPs includes communication and collectives
3. Strided Tensor Support
4. Python Op (torch interop)
5. ONNXBlock (Front end tools for training artifacts prep when using
trianing apis)
### Motivation and Context
Intention is to simply the options for building training enabled builds.
This is part of the larger work item to create dedicated build for
learning on the edge scenarios with just training apis enabled.
### Description
<!-- Describe your changes. -->
Add ability to set RunOptions config entries. Largely a cut-and-paste of
the existing code for setting SessionOptions config entries.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
#13936
### Description
This PR fixes some typos in the training apis.
We need to add more tests and make sure they are all run on the CIs to
capture such issues. These changes are out of scope of this PR.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Co-authored-by: Ashwini Khade <askhade@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
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<blockquote>
<h2>13.0.2</h2>
<ul>
<li>New feature - Add support for DateOnly and TimeOnly</li>
<li>New feature - Add UnixDateTimeConverter.AllowPreEpoch property</li>
<li>New feature - Add copy constructor to JsonSerializerSettings</li>
<li>New feature - Add JsonCloneSettings with property to disable copying
annotations</li>
<li>Change - Add nullable annotation to JToken.ToObject(Type,
JsonSerializer)</li>
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<li>Fix - Fixed MaxDepth when used with ToObject inside of a
JsonConverter</li>
<li>Fix - Fixed deserializing mismatched JToken types in properties</li>
<li>Fix - Fixed merging enumerable content and validate content</li>
<li>Fix - Fixed using $type with arrays of more than two dimensions</li>
<li>Fix - Fixed rare race condition in name table when deserializing on
device with ARM processors</li>
<li>Fix - Fixed deserializing via constructor with ignored base type
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<li>Fix - Fixed MaxDepth not being used with ISerializable
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Add missing headers</li>
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Add JsonCloneSettings to disable copy annotations (<a
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<li><a
href="d0a328e8a4"><code>d0a328e</code></a>
Fix MaxDepth not being used with ISerializable deserialization (<a
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Fix deserializing via constructor with ignored base type properties (<a
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<li>New feature - Add UnixDateTimeConverter.AllowPreEpoch property</li>
<li>New feature - Add copy constructor to JsonSerializerSettings</li>
<li>New feature - Add JsonCloneSettings with property to disable copying
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<li>Change - Add nullable annotation to JToken.ToObject(Type,
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<li>Fix - Fixed merging enumerable content and validate content</li>
<li>Fix - Fixed using $type with arrays of more than two dimensions</li>
<li>Fix - Fixed rare race condition in name table when deserializing on
device with ARM processors</li>
<li>Fix - Fixed deserializing via constructor with ignored base type
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<li>Fix - Fixed MaxDepth not being used with ISerializable
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Update to 13.0.2-beta2</li>
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Fix deserializing via constructor with ignored base type properties (<a
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<li>New feature - Add UnixDateTimeConverter.AllowPreEpoch property</li>
<li>New feature - Add copy constructor to JsonSerializerSettings</li>
<li>New feature - Add JsonCloneSettings with property to disable copying
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<li>Change - Add nullable annotation to JToken.ToObject(Type,
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<li>Fix - Fixed using $type with arrays of more than two dimensions</li>
<li>Fix - Fixed rare race condition in name table when deserializing on
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<li>Fix - Fixed deserializing via constructor with ignored base type
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<li>Fix - Fixed MaxDepth not being used with ISerializable
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Add missing headers</li>
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Update to 13.0.2-beta3</li>
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Fix deserializing via constructor with ignored base type properties (<a
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This reverts commit 87d5703b14.
### Motivation and Context
There was a bug in Linux CUDA installation.
The OS image is updated.
The TestCUDAProviderOptions could be reenabled.
### Description
This PR enables building nuget packages locally for on device training
using --build_nuget arg.
This PR also enables the C# bindings by default in the managed package.
If a user triggers any training apis when the native binary is not built
for training, an exception with message "Training is disabled in the
current build. Please build ONNXRuntime from source with the build flags
enable_training and enable_training_on_device. " is thrown.
Build command for creating nuget packes for on device training:
build.bat --enable_training --enable_training_on_device --build_nuget
2 Nuget packages are built
1. Microsoft.ML.OnnxRuntime.Managed
2. Microsoft.ML.OnnxRuntime.Training OR
Microsoft.ML.OnnxRuntime.Training.Gpu
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
Skip quantized model C# tests on GPU too.
### Motivation and Context
It looks the current test result isn't reasonable.
https://github.com/onnx/models/issues/581
Once we update the image, the quantized model [test data will be
generated with
VNNI](ba629906dd),
the CI would be broken.
### Description
<!-- Describe your changes. -->
Skip the test with --filter in runtest.sh
### Motivation and Context
Recently, the Zip-Nuget-Java-Nodejs Packaging Pipeline always failed in
Nuget_Test_Linux_GPU.
To unblock the packaging workflow, skip the test in Nuget_Test_Linux_GPU
temporally.
the exception message is below.
```
[xUnit.net 00:07:26.28] TestCUDAProviderOptions [FAIL]
Failed TestCUDAProviderOptions [1 m 19 s]
Error Message:
Microsoft.ML.OnnxRuntime.OnnxRuntimeException : [ErrorCode:RuntimeException] Non-zero status code returned while running FusedConv node. Name:'' Status Message: /onnxruntime_src/onnxruntime/core/framework/bfc_arena.cc:342 void* onnxruntime::BFCArena::AllocateRawInternal(size_t, bool) Available memory of 11416064 is smaller than requested bytes of 134217728
Stack Trace:
at Microsoft.ML.OnnxRuntime.NativeApiStatus.VerifySuccess(IntPtr nativeStatus)
at Microsoft.ML.OnnxRuntime.InferenceSession.RunImpl(RunOptions options, IntPtr[] inputNames, IntPtr[] inputValues, IntPtr[] outputNames, DisposableList`1 cleanupList)
at Microsoft.ML.OnnxRuntime.InferenceSession.Run(IReadOnlyCollection`1 inputs, IReadOnlyCollection`1 outputNames, RunOptions options)
at Microsoft.ML.OnnxRuntime.InferenceSession.Run(IReadOnlyCollection`1 inputs, IReadOnlyCollection`1 outputNames)
at Microsoft.ML.OnnxRuntime.InferenceSession.Run(IReadOnlyCollection`1 inputs)
at Microsoft.ML.OnnxRuntime.Tests.CUDATest.TestCUDAProviderOptions() in /mnt/vss/_work/1/s/csharp/test/Microsoft.ML.OnnxRuntime.Tests.NetCoreApp/InferenceTest.netcore.cs:line 93
Failed! - Failed: 1, Passed: 0, Skipped: 0, Total: 1, Duration: < 1 ms - /mnt/vss/_work/1/s/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests/bin/Debug/netcoreapp3.1/Microsoft.ML.OnnxRuntime.EndToEndTests.dll (netcoreapp3.1)
Done executing task "Microsoft.TestPlatform.Build.Tasks.VSTestTask" -- FAILED.
1>Done building target "VSTest" in project "Microsoft.ML.OnnxRuntime.EndToEndTests.csproj" -- FAILED.
1>Done Building Project "/mnt/vss/_work/1/s/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests/Microsoft.ML.OnnxRuntime.EndToEndTests.csproj" (VSTest target(s)) -- FAILED.
```
Patch Protobuf and ONNX's cmake files and enforce BinSkim check.
This PR has overlap with #13523 . I would prefer to get this one merged
first so that we can finished the BinSkim work, and I try to make this
PR as small as possible.
### Description
* Add getter/setter to access and update C# OrtEnv log level
* Add C API about updating ort env with custom log level to support the
setter above (Following [pybind
implementation](952c99304a/onnxruntime/python/onnxruntime_pybind_state.cc (L923-L924)))
* Add test case to verify getter & setter
### Motivation and Context
* For C++/Python, the log level can be adjusted via OrtEnv, and this
feature is missing in C# binding
### Description
Training C# bindings (ReleaseTrainingSession and ReleaseCheckpointState)
broke after an API order change in Training C API. This PR fixes this
issue.
### Motivation and Context
Bug Fix for Training C# bindings
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
* Add asm statement to model.mm to force linker to link against CoreML.Framework.
Update targets.xml as per Rolf's suggestions
* Remove explicit numpy version from macos build. We don't specify it for other CIs and the version specified doesn't have a pre-built 3.10 wheel. This leads to the CI attempting to build numpy which fails.
* Fix SAME_UPPER/SAME_LOWER (auto_pad attribute) in ConvTranspose
* Bump ONNX 1.10.2 globally
* load ONNX_VERSION from VERSION_NUMBER
* /
* revert deprecate warning in ORT 1.12
* add a comment about why removing cntk_simple_seg
* correct the implem in DML as well
Add csharp\sample\InferenceSample\Microsoft.ML.OnnxRuntime.InferenceSample.Maui so we have an equivalent setup for MAUI as for the other platforms.
This provides a setup to do some basic local testing of using an InferenceSession in a MAUI app.
The generated bindings causes C# build errors that require workaround code. Disabling generation should avoid the need for any workarounds.
As the user has the C# ORT package with the C# to C bindings there's no need for binding generation that calls the ORT Java API (which is C# -> Java ->C).
* Update C# runtest.sh for opset 17
Should have been part of https://github.com/microsoft/onnxruntime/pull/11924
* get appropriate opset version from onnx doc
* use absolute rather than relative path
* fix typo in var name
* Add net6 targets.
Remove maccatalyst as we don't have a native build targetting that.
* Set platform in macos targets
* Add targetFramework entries
* Move NativeLib.DllName definition and set using preprocessor values for simplicity. Couldn't get it to build with the preprocessor based setup when it was in a separate file.
Update the nuspec generation to set platform version for .net6 targets. TODO: Validate versions. I copied them from the managed nuget package the packaging pipeline generated prior to adding targets. Possibly w could/should lower some of the versions.
Hopefully the need to specify a version goes away when the release version of VS2022 supports .net6.
* Try android 31.1 as https://github.com/actions/virtual-environments/blob/main/images/win/Windows2022-Readme.md suggests that should be available on the CI machines
* Fix patch version mismatch
Add some extra debug info in case it helps
* Debug nuget location in CI
* Add workspace entry back in
* Add steps
* One more attempt with hardcoded nuget.exe path and original android31.0 version
* Better fix - found explicit nuget download and updated version there.
* flake8 fixes
* Fix black complaints.
* Exit Microsoft_ML_OnnxRuntime_CheckPrerequisites for net6 iOS.
* Removed outdated comment
