* Add ArmNN Execution Provider
Add a new execution provider targeting Arm architecture based on ArmNN.
Validated on NXP i.MX8QM CPU with ResNet50, MobileNetv2 and VGG models.
reviewed-by: mike.caraman@nxp.com
* Minor fixes
- renamed onnxruntime_ARMNN_RELU_USECPU to onnxruntime_ARMNN_RELU_USE_CPU
- fixed acl typo
* remove extra includes. added exception for ArmNN in test
* fix indentation
* Separated the activation implementation from the cpu and fixed the blockage from the endif
Co-authored-by: Andrei-Alexandru <andrei-alexandru.avram@nxp.com>
- Add support for ENABLE_LANGUAGE_INTEROP_OPS in training build which is enabled for nightly builds
- Fix passing of environment variables to `sudo docker run` in build definitions
- Fix setup.py package naming logic
* Add amd migraphx execution provider to onnx runtime
* rename MiGraphX to MIGraphX
* remove unnecessary changes in migraphx_execution_provider.cc
* add migraphx EP to tests
* add input requests of the batchnorm operator
* add to support an onnx operator PRelu
* update migrapx dockerfile and removed one unused line
* sync submodules with mater branch
* fixed a small bug
* fix various bugs to run msft real models correctly
* some code cleanup
* fix python file format
* fixed a code style issue
* add default provider for migraphx execution provider
Co-authored-by: Shucai Xiao <Shucai.Xiao@amd.com>
In this PR, we
1. create some APIs for creating NVTX objects
2. apply those APIs in pipeline-related operators and sequential executor.
As a result, we can explicitly see how a pipeline schedule is run by GPUs in
Nvidia's visual profiler. Note that these APIs are Linux only due to Nvidia's
limited support.
* [java] - adding a cuda enabled test.
* Adding --build_java to the windows gpu ci pipeline.
* Removing a stray line from the unit tests that always enabled CUDA for Java.
* Enable running PEP8 checks via flake8 as part of the build if flake8 is installed.
Update scripts in \tools and \onnxruntime\python. Excluding \onnxruntime\python\tools which needs a lot more work to be PEP8 compliant. Also excluding orttraining\tools for the same reason.
Install flake8 as part of the static_analysis build task in the Win-CPU CI so the checks are run in one CI build.
Update coding standards doc.
Detect os and arch and move the artifacts to a new folder.
Remove unnecesary jars so we cam focus on those we publish.
Add signing
Make signature simlper.
Fix indent.
Halt on 32-bit arch.
Credits: @Craigacp
* Merged PR 4616739: Update QLinear Ops fix 1D support layout
Update QLinear Ops fix 1D support layout
Related work items: #26011523
* Merged PR 4617257: Gather operator DML EP fails with scalar indices and 1D inputs
Fix gather with scalar value.
The ONNX conformance test case is in another PR:
// 0D, axis 1, rank 0 indices tensor
{
"op_type": "Gather",
"axis": 0,
"data": [1,2,3],
"indices": 0,
"output": 1,
"T": "float32"
}
* Merged PR 4632178: Re-enable ORT onnx_test_runner test case (DirectML ConvTranspose validation needs to be loosened to comply with ONNX definition of output_padding)
Re-enable 1D convolution tests.
Related work items: #23499747
* Merged PR 4656672: Make DML EP use Direct queue
While a Compute queue has benefits, Direct is consistent with Winml.
Related work items: #26324112
* Update DML nuget version
* Merged PR 4662079: Update DmlDev branch again from github master
Include Sheil's changes to fix namespace and header file include paths. Without this, the ONNX conformance tests all fail with E_NOTIMPL.
* Increment DML nuget version
Co-authored-by: Nick Feeney <nickfe@microsoft.com>
Co-authored-by: Dwayne Robinson <dwayner@microsoft.com>
* Added aarch64 build pipeline
* Fix build error
* Remove auditwheel repair which doesn't work with cross compiling
* Statically link C++
* Added auditwheel repair back and fix stdlib.h
* Remove extra space
* dashboard integration - first phase
* change a field
* perf scripts
* addressing PR comments
* address comments and fix build
* minor
* make GetConfigFromData() const
* more update for comments
* addressing comments
* more on addressing comments
* minor
* fix build
* add condition check
* more on comments
* retrun status
* remove batch size
* on comments
* rename pkg path
* rename pkg path
* additional commentss
Co-authored-by: Ethan Tao <ettao@microsoft.com>
* add build inbox flag
* remove raw tests and wstring for utf filenames
* enable raw tests
* use ToWideString
* create new utf8 helper
* update string helper to utf8
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
* java - adding support for custom op libraries.
* Adding support for RunOptions and additional methods for SessionOptions and OrtSession.
As a result OrtEnvironment.LoggingLevel moved to be a top level enum
called OrtLoggingLevel.
* java - adding unit tests for RunOptions and SessionOptions.
* java - removing unused releaseNamesHandle method
* java - add test for custom op library.
* java - adding log verbosity methods, and tests for the same.
* java - fixes for custom op loading test on Windows.
* Cleanup after rebase on master.
1. Parallel all the activations ops.
2. Parallel the performance critical path of the LRN op, which makes the ONNX model zoo googlenet model runs 60% faster(latency reduced from 21ms to 13ms).
3. Make the Gemm-Activation fusion support with all the activations ops. Before this change, it only supports LeakyRelu/Relu/Sigmoid/Tanh.
4. Delete onnxruntime/test/framework/op_kernel_test.cc because the file is almost empty.
5. Remove the loggings in KernelRegistry::TryFindKernel, return Status with error message instead.
* initial change to transformer.py
* prepare e2e transformer tests
* refactor transformer tests
* put test python files in a flat folder
* fix typo pip install transform(s)
* python 3.6
* python version to 3.6 in install_ubuntu.sh
* remove argparser
* to use opset ver 12
* workaround loss_scale naming patch in case of loss_fn_
* assign self.loss_fn_ so it can be checked
* skip a few un-needed post-process steps
* fix loss_scale_input_name, clean up post process steps
* skip non-frontend tests
* move cpu/cuda related files to coresponding cpu/cuda folder (#3668)
Co-authored-by: Weixing Zhang <wezhan@microsoft.com>
* type cast for ratio is not necessary for dropout (#3682)
Co-authored-by: Weixing Zhang <wezhan@microsoft.com>
* thrustallocator is not needed since cub is used directly for gather now. (#3683)
Co-authored-by: Weixing Zhang <wezhan@microsoft.com>
* GatherND-12 Implementation (#3645)
* Renamed, UT passing
* Move GatherND CUDA Kerenl into onnxruntime
* Merge GatherNDOpTest
* Refactor Test code
* Merge CPU Kernel Impl
* Handle Negative Indice, Fix UT
* Improve CUDA kernel to handle negative index
* Minor Fixes
* Preserve GatherND-1 Cuda kernel
* Fix Mac build
* fix UT
* Fix Build
* fix GatherNDOpTest.double > CUDA error cudaErrorInvalidDeviceFunction:invalid device function
Co-authored-by: Sherlock Huang <bahuang@OrtTrainingDev3.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Peng Wang (pengwa) <pengwa@microsoft.com>
* update with reviewers' comments
* testBertTrainingGradientAccumulation was not using rtol and may fail occasionally with small (e-06) difference
* fix merge mistakes
Co-authored-by: liqun <liqun@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Weixing Zhang <weixingzhang@users.noreply.github.com>
Co-authored-by: Weixing Zhang <wezhan@microsoft.com>
Co-authored-by: Sherlock <baihan.huang@gmail.com>
Co-authored-by: Sherlock Huang <bahuang@OrtTrainingDev3.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Peng Wang (pengwa) <pengwa@microsoft.com>
* Enable iOS cross build on MacOS (step#1)
* Changed parallel option
* fixed style issues
* Enable ios arm64 crossbuild on MacOS
* Enable ios arm64 crossbuild on MacOS
* Enable parallel build for xcode
* Fix arm64 function not 4-byte aligned warning
* Rename onnxruntime_ios.cmake to onnxruntime_ios.toolchain.cmake
* change build.py to use the new ios toolchain file name
