* Enabling fasterrcnn variant and vehicle detector
* changes for 2021_2 branch
* yolov3_pytorch commit
* fixed braces in basic_backend.cc
* ci information added
* faster rcnn variant and vehicle detector changes were made in 2021.1 and not in 2021.2
* some changes to support unit tests
* disable some tests which are failing
* fix myriad tests for vehicle detector
* Did some cleanup
*cleaned up comments
*Disabled Add_Broadcast_0x1 and Add_Broadcast_1x0
tests on MYRIAD_FP16 backend due to a bug
*cleaned up capability_2021_2.cc file
*Removed extra conditions which were added
for some validation in backend_utils
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* yolov3 pytorch workaround to ensure that the output names are matched
* gemmoptest fixed on myriad
* Fixed MYRIADX CPP Test Failures
*Expand,GatherND,Range,Round op's
are only supported in model
*where op with float input data
types are not supported and fixed
*Scatter and ScatterElements op's with
negative axis are fixed
*Reshape op with 0 dim value are not
supported and fixed
*Disabled InstanceNorm_2 test on MYRIADX
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* make changes to yolov3 pytorch
* Fixed python unit tests
*Fixed failing python tests on vpu,
GPU and CPU
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixes POW op failures on GPU_FP16
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Clean up capability_2021_2.cc
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Updated docx for MultiThreading option
*Added extra info on setting the num_of_threads
option using the API and it's actual usage
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* fixed slice and removed extra prints
* Disabled failing python tests
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Minor changes added in capabilty_2021_2
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* made changes to slice to avoid failures
* Disabling FP16 support for GPU_FP32
->Inferencing an FP16 model on GPU_FP32
leads to accuracy mismatches. so, we would
rather use GPU_FP16 to infer an FP16 model
on GPU Device
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Updated docx for Inferencing a FP16 Model
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* fix for mask rcnn
* Script for installing openvino from source
* Updated with openvino 2021.2 online installation
* code comment fixes
fixed accuracy mismatch for div
* Update OpenvinoEP-ExecutionProvider.md
updated for 2021.2 branch
* Update README.md
updated dockerfile documentation
* Update BUILD.md
build.md update documentation
* permissiong change of install_openvino.sh
* made changes to align with microsoft onnxruntime changes
* Updated with ov 2021.2.200
Co-authored-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
Co-authored-by: sfatimar <sahar.fatima@intel/com>
Co-authored-by: MaajidKhan <n.maajidkhan@gmail.com>
Co-authored-by: mohdansx <mohdx.ansari@intel.com>
* build for .net5
* only reference cswinrt for .net5
* remove netstandard2.0 references
* upgrade language version
* net5
* remove extra comment closure
* add targetframework
* set target framework
* remove net*
* pep8 errors
* make test project build with .net windows SDK projection
* disable c# builds for non-x64 builds
* fix pep8 errors
* disable for store build
* fix tests
* remove cswinrt and sdk references from package
* bump cswinrt down to 1.0.1
* fix bin path
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
* ReduceL2Grad and ClipGrad.
* fix win build and amd ci pipeline
* resolve comments.
Co-authored-by: Vincent Wang <weicwang@AiFramework2080ti2.corp.microsoft.com>
Fix a typo in tools/ci_build/github/azure-pipelines/templates/get-docker-image-steps.yml.
Add logging to tools/ci_build/get_docker_image.py for easier debugging.
* Added Onnxruntime_GCOV_COVERAGE flag for Android.
* Set CMAKE_SYSTEM_NAME explicityly for Android.
* Added GCOV_PREFIX option to collect code coverage data.
Added a new python script to generate code coverage info.
Modified build pipeline to geneate Android code coverage info
* Added build command line option --android_coverage
* Added a comment describing the GCOV environment variables
* Fixed PEP8 issues.
* Added --android_coverage option to the build command.
* Increased Android emulator memory from 3K to 8K.
* Increased Android partition-size from 2GB to 4GB to overcome no-space-left-on-device error
* Removed source_dir from command line args.
* Use cwd absolute path to run tests.
* Added commands to output the contents of /data/local/tmp on the emulator.
* Added run_adb_shell function.
* Format changes.
* Removed keywd argument cwd.
* Removed Android in the --build_dir path.
* Removed commands added for debugging.
* Removed exxtra new-lines.
* Fix MacOs build pipeline failures by uninstalling openssl before running build script.
* Revert "Fix MacOs build pipeline failures by uninstalling openssl before running build script."
This reverts commit 90d0568fe533e9456c20d061a2d435c8fea48266.
* Change dir to the build directory where the tar file is copied.
* Changed the option from --android_coverage to --code_coverage
* Moved steps to generate Android code coverage to run_nnap_code_coverage.sh
* Require --android option if --code_coverage is specified.
* No code coverage needed for onnx_test_runner.
* Expect that the emulator is running when the script is executed.
* Fixed the title in the buildpipeline step.
* Fixed the formatting issue.
* Added a command line argument, ORT_ROOT, to run_nnapi_code_coverage.sh script
Co-authored-by: Satya Jandhyala <satyajandhyala@Satyas-Mac-mini.local>
The current image cache cleanup is not removing many images. Upon examining the cache container registry logs, it appears there are some infrequent pulls of old images which may be made by something other than CI builds (perhaps some automated scan of the registry).
This change adds a minimum access count for images in the cache so that infrequently but periodically accessed images can be removed. The idea is that images used by CI builds that are worth caching will have a higher volume of accesses.
Update training Python packaging build to use get_docker_image.py.
Remove BUILD_EXTR_PAR docker build argument.
Update get_docker_image.py to check again for the image in the cache after building and before pushing to reduce the chance of a redundant push.
Description: Add ORT minimal with NNAPI EP to Android CI
Motivation and Context
The added build/test to Android CI will only run UT, additional onnx_test_runner with customer .ort models will be added later
Fix Python 3.5 compatibility issue in tools/ci_build/get_docker_image.py.
Fix line endings in tools/ci_build/github/azure-pipelines/clean-build-docker-image-cache-pipeline.yml.
* Run only required steps relevant to fuzz testing.
* Exit status non-zero for any uncaught exception other than ort_exception in the driver code
Co-authored-by: Satya Jandhyala <sajandhy@microsoft.com>
Follow up to #5811 to automate cleanup of the build docker image cache.
Added a script and build definition to clean up docker images that haven't been accessed recently.
* Remove nGraph Execution Provider
Pursuant to nGraph deprecation notice: https://github.com/microsoft/onnxruntime/blob/master/docs/execution_providers/nGraph-ExecutionProvider.md#deprecation-notice
**Deprecation Notice**
| | |
| --- | --- |
| Deprecation Begins | June 1, 2020 |
| Removal Date | December 1, 2020 |
Starting with the OpenVINO™ toolkit 2020.2 release, all of the features
previously available through nGraph have been merged into the OpenVINO™
toolkit. As a result, all the features previously available through
ONNX RT Execution Provider for nGraph have been merged with ONNX RT
Execution Provider for OpenVINO™ toolkit.
Therefore, ONNX RT Execution Provider for **nGraph** will be deprecated
starting June 1, 2020 and will be completely removed on December 1,
2020. Users are recommended to migrate to the ONNX RT Execution Provider
for OpenVINO™ toolkit as the unified solution for all AI inferencing on
Intel® hardware.
* Remove nGraph Licence info from ThirdPartyNotices.txt
* Use simple Test.Run() for tests without EP exclusions
To be consistent with rest of test code.
* Remove nGraph EP functions from Java code
* Added fuzz testing using ORT model.
* The onnxruntime_security_fuzz driver code should accept either ONNX or ORT (based on the file extension) input file if /f flag is provided.
* Added ValidateOrtFormatModelDoesNotRunOptimizersInFullBuild test.
* Added win-ci-fuzz-testing.yml to run build pipeline.
* Prevent out-of-range access in the graph.cpp.
This PR adds infrastructure to automatically cache docker images used in CI builds in a container registry.
Currently, build images are pulled from a container registry for some builds and built every time for others. The container registry requires maintenance to keep the images up to date and building images every time wastes build agent resources.
With this change, a given build image can be looked up in a cache container registry and if present, pulled, and otherwise, built and pushed. The uniqueness of a build image is determined by a hash digest of the dockerfile, docker build context directory, and certain "docker build" options. This digest is part of the image tag in the cache container repository.
The cache container registry will need to be cleaned up periodically. This is not automated yet.
Transitions from the ORT-only DML NuGet (hosted on the onnxruntime_public feed) to the new unified DirectML NuGet (Microsoft.AI.DirectML) on nuget.org. In addition, the Microsoft.AI.MachineLearning (WinML) and Microsoft.ML.OnnxRuntime.DirectML packages now take a dependency on the Microsoft.AI.DirectML package. This means we can remove the extra copy of DML binaries in these packages since they will be installed by the DML package.
* Add validation of operator registrations to the reduction script
- the script has all the logic to process the registrations, and there's a CI that uses it
Fix some operator registrations
* Fix CUDA PRelu registration
* Refactor to split out kernel registration file parsing and use in the exclude ops script and an op registration validation script.
Run op validation in minimal build CI
* Fix PEP8 error and some comments
* Add copy sparse model in minimal CI
* Add squeeze 13 support
* fix small typo
* Add ut for squeeze in NNAPI
* Fix some issue in the UT and code
* Modify based on the master change
* Fix build break
* Create an Azure Pipeline to merge cpp and python e2e pipelines into one. Still keep cpp 2e2 pipeline until this new pipeline is stable.
Co-authored-by: liqun <liqun@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
