* link to folder instead of READMEs inside folder (#3938)
otherwise hard to find the source code
* [Node.js binding] fix linux build (#3927)
* [Node.js binding] add build flag for node.js binding (#3948)
* [Nodejs binding] create a new pipeline to generate signed binaries (#4104)
* add yml files
* update pipeline
* fix yaml syntax
* yaml pop BuildCSharp
* udpate yaml
* do not stage codesign summary
* fix build: pipeline Node.js version to 12.16.3 (#4145)
* [Node.js binding] upgrade node-addon-api to 3.0 (#4148)
* [Node.js binding] add linux and mac package (#4157)
* try mac pipeline
* fix path separator
* copy prebuilds folder
* split esrp yaml for win/mac
* disable mac signing temporarily
* add linux
* fix indent
* add nodetool in linux
* add nodetool in win-ci-2019
* replace linux build by custom docker scripts
* use manylinux as node 12.16 not working on centos6
* try ubuntu
* loosen timeout for test case - multiple runs calls
* add script to support update nodejs binding version (#4164)
* [java] Adds a CUDA test (#3956)
* [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.
* Update OnnxRuntime.java for OS X environment. (#3985)
onnxruntime init failure due to wrong path of reading native libraries. In OS X 64 system, the arch name is detected as x86 which generates invalid path to read native libraries.
Exception java.lang.UnsatisfiedLinkError: no onnxruntime in java.library.path
at java.lang.ClassLoader.loadLibrary(ClassLoader.java:1867)
at java.lang.Runtime.loadLibrary0(Runtime.java:870)
at java.lang.System.loadLibrary(System.java:1122)
at ai.onnxruntime.OnnxRuntime.load(OnnxRuntime.java:174)
at ai.onnxruntime.OnnxRuntime.init(OnnxRuntime.java:81)
at ai.onnxruntime.OrtEnvironment.<clinit>(OrtEnvironment.java:24)
* Create Java publishing pipeline (#3944)
Create CPU and GPu Java publishing pipelines. Final jars are tested on all platforms. However, signing and publishing to maven are manual steps.
* Change group id to com.microsoft.onnxruntime per requirements.
* Java GPu artifact naming (#4179)
Modify gradle build so artifactID has _gpu for GPU builds.
Pass USE_CUDA flag on CUDA build
Adjust publishing pipelines to extract POM from a correct path.
Co-Authored-By: @Craigacp
* bump up ORT version to 1.3.1 (#4181)
* move back to toolset 14.16 to possibly work around nvcc bug (#4180)
* Symbolic shape inference exit on models without onnx opset used (#4090)
* Symbolic shape inference exit on models without onnx opset used
* Temporary fix for ConvTranspose with symbolic input dims
Co-authored-by: Changming Sun <me@sunchangming.com>
* Fix Nuphar test failure
* Enlarge the read buffer size in C#/Java test code (#4150)
1. Enlarge the read buffer size further, so that our code can run even faster. TODO: need apply the similar changes to python some other language bindings.
2. Add coreml_VGG16_ImageNet to the test exclusion set of x86_32. It is not a new model but previously we didn't run the test against x86_32.
* Temporarily disable windows static analysis CI job
* skip model coreml_Imputer-LogisticRegression_sklearn_load_breast_cancer
* Delete unused variable
Co-authored-by: Prasanth Pulavarthi <prasantp@microsoft.com>
Co-authored-by: Yulong Wang <yulongw@microsoft.com>
Co-authored-by: Adam Pocock <adam.pocock@oracle.com>
Co-authored-by: jji2019 <49252772+jji2019@users.noreply.github.com>
Co-authored-by: Dmitri Smirnov <yuslepukhin@users.noreply.github.com>
Co-authored-by: Dmitri Smirnov <dmitrism@microsoft.com>
Co-authored-by: George Wu <jywu@microsoft.com>
Co-authored-by: KeDengMS <kedeng@microsoft.com>
Co-authored-by: Changming Sun <me@sunchangming.com>
Co-authored-by: Changming Sun <chasun@microsoft.com>
* 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>
* add frontend minst test
* to use torch nightly with torchvision
* remove incorrect comment per reviewer's comment
* experiment torchvision import failure
* experiment install_deps.sh
* more experiment install_deps.sh
* experiment install_deps.sh with --upgrade
* Experiment with install_deps.sh.
* Experiment with install_ubuntu.sh.
* Use Ubuntu 18.04 and Python 3.6 for CI.
* Update cmake version for CI.
* Install MPI on Ubuntu 18.04 for CI.
* Increase tolerance for MNIST test.
* Go back to Ubuntu 16.04 for CI, fix installing from deadsnakes ppa.
* Clean-up.
* Update ort_trainer.py from ort_training.
* Get default Ubuntu Python ver back to 3.5.
* Add underscore to opset_version parameter name in ORTTrainer constructor.
* Move loss/model wrap before the call for sample output.
* Update expected values for MNIST test.
Co-authored-by: liqun <liqun@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Sergii Dymchenko <sedymche@microsoft.com>
1. Pipeline changes for python 3.8
2. Fix a regression in setup.py which was just introduced in the previous commit.
Please notice, we still haven't made python 3.8 + Windows + CUDA work.
Remove gsl subodule and replace with a local copy of gsl-lite
Refactor for onnxruntime::make_unique
gsl::span size and index are now size_t
Remove lambda auto argument type detection.
Remove constexpr from fail_fast in gsl due to Linux not being happy.
Comment out std::stream support due to MacOS std lib broken.
Move make_unique into include/core/common so it is accessible for server builds.
Relax requirements for onnxruntime/test/providers/cpu/ml/write_scores_test.cc
due to x86 build.
Add ONNXRUNTIME_ROOT to Server Lib includes so gsl is recognized
* Update cuda for python wheels
* Update cuda for python wheels
* Update cuda for python wheels
* Update azure-pipelines-py-packaging.yml
* Update to cuda 10
* Only test win gpu
* Update cuda for python wheels
* Use manylinux2010 image to build linux python wheels
Allow wheels built to truly be compliant with a manylinux policy
* call install_onnx with relative path
* use caller path
* get abs path of current script
* process unicode char
* replace script name
* add suffix as part of match
* match only the end of path
* add version filter to failed tests
* exclude test from backend
* exclude shrink from opset 9
* fix compile err
* exclude certain version of constant shape
* enable flatten test
* fix compile err
* comment mvn test
* disable constantofshape test in x86
* disable x86 test
* get model version from imported opset
* test linux x86 case
* disable nonzero opset 10
* make mutex const
* test filter by commit id
* adjust substr offset
* Limit test platform
* remove change impacting TFModleInfo.h
* refactoring
* refactoring
* test x86 pipeline with filter
* add comment
* restrict version extraction on non-win
* restrict version extraction on non-win
* add tag
* exclude case from backend test
* remove dup
* remove dup
* make script runnable
* hard code adsolute path
* refactor log
* fix x86 compile err
* fix x86 compile err
* fix x86 compile err
* sync with latest tensorrt
* switch to regex
* fix cpu pipeline err
* test filter
* disable nonzero from all versions
* Accomodate missing optional 'axes' when 'steps' is present in Slice op (#946)
* Accomodate missing optional axes when steps is present in Slice implementation
* PR feedback
* Update package links (#937)
* Update package links
* Minor fix
* Update README.md
* Minor edit
* Update onnx commit (#949)
* Update onnx commit
* disable failing tests which don't have to be fixed for this release
* dummy change to fix file permission
* fix file permission
* move files
* move files
* Remove NonMaxSuppression from Contrib op, move it to Onnx domain, opset 10
* move NMS out of namespace contrib
* update data type in UT
* update to latest onnx
* white list the node test for Mod which is not implemented yet
* Exclude unreferenced global data and op doc strings in the opschema object. The first causes a decrease in the binary size by at least 85k. The latter reduces resident memory size.
* Update onnx to incorporate my PR that fixes SetDoc compiler warnings
* Update onnx
* Support updated function schema in ORT
* Update onnx related commit hash
* Check out an older commit in ONNX
* Add support for subgraph attribute
* Add comments
* sync onnx and maintain old version history for removed exp ops in onnx runtime.
* update
* updating to specific onnx commit - remove exp ops.
* update
* disable the 3 failures to push the change as it's blocking folks.
* update test
* Update cast kernel to support to/from string
* Update namespace
* Add support for literal numeric case
* Update to support -INF test
* Update kernel registration for cast
* Update ONNX to 1.4.1
* Update registy api
* Resolve some comments
* Update cast kernel implementation
* Resolve comments
* Fixed test data in onnx
* Update cast kernel implementation
* Resolve PR comments
* Update cast_op.cc
* Update onnx commits info
* Update comments
* Update ONNX version to pickup Scan spec change that adds scan_output_axes.
Add logic to transpose an output
- write to temporary buffer when executing subgraph
- transpose temporary buffer into Scan output when execution completes
Add unit tests
* Update to ONNX dbf3581835e3a05716e10587511d7ab3b2cdc386 to pickup inferencing bugfix.
Update test to match.
* Disable some tests for opset 9 operators that haven't been implemented yet.
