* added cache version for nuphar JIT binaries
Previously, when the user wrongfully loaded a JIT binary generated
from a Nuphar version different from the current used one, she
would get mysterious runtime failures, because we didn't perform
any version check on JIT binaries.
This change added cache versions to the Nuphar runtime and
JIT binaries. The Nuphar runtime will issue verbose message that
informs the user version-mismatch errors.
* address CR feedback
* include NUPHAR_CACHE_VERSION in python wheel
This change adds a new execution provider powered by [DirectML](https://aka.ms/DirectML).
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning on Windows. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers.
The DirectML execution provider is capable of greatly improving evaluation time of models using commodity GPU hardware, without sacrificing broad hardware support or requiring vendor-specific extensions to be installed.
**Note** that the DML EP code was moved verbatim from the existing WindowsAI project, which is why it doesn't yet conform to the onnxruntime coding style. This is something that can be fixed later; we would like to keep formatting/whitespace changes to a minimum for the time being to make it easier to port fixes from WindowsAI to ORT during this transition.
Summary of changes:
* Initial commit of DML EP files under onnxruntime/core/providers/dml
* Add cmake entries for building the DML EP and for pulling down the DirectML redist using nuget
* Add a submodule dependency on the Windows Implementation Library (WIL)
* Add docs under docs/execution_providers/DirectML-ExecutionProvider.md
* Add support for DML EP to provider tests and perf tests
* Add support for DML EP to fns_candy_style_transfer sample
* Add entries to the C ABI for instantiating the DML EP
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
* Fixed a bug of missing tvm in python wheel
* Put Nuphar Python scripts into wheel
* Add note book tutorial
* Some improvements in symbolic shape inference for quantized models
* Implement Nuphar execution provider
Nuphar execution provider is a TVM-based compilation provider. It has shown great speedups for RNN models using Scan.
This PR is mainly for a preview of the shared codegen library for other TVM-based providers.
* Fix submodules
* Fix TVM submodule
* Update Nuphar to latest and resolve confliction
* Remove stale files caused by merge -X theirs
* Revert heap buffer change to not introduce onnxruntime_framework into onnxruntime_perf_test
* Fix bad merge
* Merge from Nuphar
* Fix warning treated as error, revert some unnecessary changes
* Revert some more test changes
* Some more test revert or comments to make review easier
New tests could be added later
* One more revert of unnecessary changes
* More change revert. Test could be added back later.
* init
* Update DNNLibrary
* Update DNNLibrary, set compiler flags, it compiles now
* Add more missing flags, add test
* Update DNNLibrary
* Update Compile method, fix allocator and some other bugs
* Update DNNLibrary
* Implement CopyTensor
* Not delete state explicitly since it is managed by unique_ptr
* Add the missing files when SingleUnitTestProjct is ON
* misc changes
* Fix wrong name in provider factory
* Add my own test
* Update the code of add node into graph, and add the missing initializer into graph
* Fix the bug that re-build the graph produces extra output
* Update DNNLibrary
* Transpose nchw (ONNX) -> nhwc (NNAPI)
* Add license
* Add GetSupportedNodes method (implement it later)
* Rename onnxruntime_nnapi_test->onnxruntime_nnapi_squeezenet_test
* Update squeezenet_test.cpp after rebase master
* Remove squeezenet_test.cpp since it is almost same with the c++ sample
* Update DNNLibrary for GetSupportedNodes
* Update GetSupportedNodes
* Revert "Remove squeezenet_test.cpp since it is almost same with the c++ sample"
This reverts commit a97575fd9ff49e50ba1dc8d8154790d8cd86c48d.
* Update DNNLibrary
* Fix multiple outputs bug
* Remove GetKernelRegistry
* Revert "Revert "Remove squeezenet_test.cpp since it is almost same with the c++ sample""
This reverts commit 2a0670e9cbf10ea654111ce39e198a4be0ddd838.
* Set default memory type of NNAPI EP
* Add CPUOutput allocator
* Update DNNLibrary for multiple outputs
* Fix bug of nhwc->nchw
* Remove GetExecutionHandle()
* 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
* Initial commit for OpenVINO Execution Provider
OpenVINO Execution Provider provides the interface for ONNX Runtime
applications to access Intel's hardware accelerators using Intel's
OpenVINO Toolkit.
* Fixed bug in GetCapability to disable custom ops
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Added OPENVINO ci pipeline
Added new pipeline for openvino provider,
made changes to support the docker build and
onnxruntime build with openvino.
Signed-off-by: Luis Daniel Castellanos <luis.daniel.castellanos@intel.com>
* Enabled all unit tests for OpenVINO EP
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Fixed syntax issue in run_docker_build.sh file
* Added missing default OPENVINO_VERSION
Default value for OPENVINO_VERSION env was
missing causing the build to fail
* Added install Model Optimizer deps step
* Fixed python unit tests and some tests from onnx_backend_test_series
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Fixed indentation bug
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled some of the python backend tests for OpenVINO
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled some model tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Remove Duplicate checks for openvino in build.py
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Modified GetCapability for FP16
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled GPU FP32 tests that are not supported
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Convert modelProto to string and use it in compile
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Pass byte-array input args to MO
* Serialized ModelProto passed in-memory to MO
ModelOptimizer python module receives the serialized ModelProto
in-memory.
Uses appropriate ONNX function to load the serialized bytes.
* Make Py_Finalize compatible with older python versions
Also, remove pFunc unassigned variable possibility.
* Fallback if input dims of Matmul is greater than 2
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* fixup: Device #define syntax
* Updated the documentation
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Enable dynamic dim value
* removed commented out code
* Added Dockerfile for openvino EP
Updated instructions on dockerfiles/README.md file
Signed-off-by: Luis Daniel Castellanos <luis.daniel.castellanos@intel.com>
* Disabled fp16_inception_v1 test
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Code formatting with clang-format
Uses style from the .clang-format file in root directory.
* fixup: docker tag and build error fixes
* Heuristics to automatically detect batching
Distributes slices from batch into parallel infer-request objects.
* Handle disabled tests in GetCapability
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled average pool and max pool if ceil_mode is 1
Also dilations are not supported if they are greater than 1
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled Unsqueeze int32 test
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* changes to fix output results bug
* Disabled a few C++ unit tests for MYRIAD FP16
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Manually revert '9fe162bb Enable dynamic dim value'
Reverts compile time setting of dynamic shape
Reverting manually due to significantly huge auto-revert conflicts.
* Fixed unused variable warning
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled Mul test for GPU_FP16 due to accuracy issue
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* VPU documentation update
* Disabled inception_v1 for MYRIAD and HDDL
*Also disabled few C++ accuracy tests for HDDL
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* updates from upstream
* use the new CustomOpApis for I/O interfacing
* Pass initializers as subgraph meta-def inputs in GetCapability()
Requirement due to API changes introduced with PR# 1019.
* Remove obsolete functions
* Save indexes of graph inputs from fused_node info
Both inputs and initializers are passed as data inputs to the
infer function. To identify only inputs among them, save thier
index info from fused_node in Compile function.
* Documentation changes to enable VPU
* Fix VPU related changes in documentation
* Fix minor changes in documentation
* Fix VPU related changes in documentation
* Use Node.In/OutputDefs() to track graph inputs and outputs.
Don't use graph_viewer's GetInputs() or
GetInputsIncludingInitializers().
* Permit "SAME_UPPER" auto_pad attribute from MaxPool
* Disabled fp16_tiny_yolov2 in onnx model tests
* Updated documentation to include configuration guides for myriad and hddl
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Use 8 Infer requests only for VAD-R
* disable debug prints
* Clang-format source files
* Updated BUILD.md with OpenVINO R5 links
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled same upper python tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Update test exclusion syntax
* Change path of install_onnx.sh
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disable tiny_yolov2 in broken tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Revert "Change path of install_onnx.sh"
This reverts commit ba9db165f3be430f2aff1ef413299ed04637196a.
This change is only required for Intel internal CI pipeline until
the settings are matched with the upstream's CI pipeline.
* Added debug statements for debugging CI error
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Add --build_wheel to linux openvino pipeline
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Added -v option to onnx_test_runner for debugging
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Removed path change patch
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Added -c 1 to onnx_test_runner
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Refactor MO python invocation in separate function
Cleans up Model Optimizer python invocation check and conversion
logic. Invokes MO only once in GetCapability() and passes the
IR strings (xml and bin) to the Compiler as meta-def attributes.
* Add comments
* code cleanup and comments
* Code cleanup for GetCapability
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Removed unnecessary files
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Revert "Added -v option to onnx_test_runner for debugging"
This reverts commit d1dd70938a94d648df1a1dbbc2e48d0b97e49ec8.
* Revert "Added debug statements for debugging CI error"
This reverts commit b86d41afed2aa29c3508155d6f9c8d3a7263cc60.
* incorporate Status Code changes
* ComputeFunc returns Status::OK() on success
* Use test names to disable tests for MYRIAD and VAD-R
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Rename local identifiers from CNNNetwork to OpenVINO network
CNNNetwork is an OpenVINO's API class that represents more than
just convolutional neural networks (CNNs). Renaming helps to avoid
confusion that the API's only support CNN type models.
* Added error message if building on windows
* Removed duplicate option in Cmake
* Removed unnecessary parameters in activation_opt_test
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Refactor Map search and access logic for efficiently and cleanliness.
* use C++ style casts
* Use os.path.join for python directory path operations
* use C++ style casts
* EP classes should use onnxruntime namespace
* Clean up fixes from PR comments
* Don't explicitly shutdown Py interpreter
* Remove debug print statements
Prints will be re-enabled later with a logging mechanism with
debug/verbose printing options.
* Decrement ref counts for used pyObjects
* Restore build instructions for other compilers
Content under the "Using other compilers" section has been
accidentally deleted by a previous commit. Restoring back that
content from the latest upstream repo.
* CMake code cleanup
Code clean up, commenting and formatting of CMake code.
* Don't pass the unused device_info parameter to OpenVINOGraph ctor.
* Add support for multiple I/O data types
Adds support for the following tensor data types for graph inputs
and outputs:
1) float
2) float16
3) int32
4) int16
5) int8
6) uint16
7) uint8
* cleanup setup.py module list definition
* Deduce index of input using tracked input index map
Ignores initializers in case they are ordered before inputs.
* Removed debug statement in MO code
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* PR feedback
* Removed per_sample_tolerance for openvino
* Removed unnecessary disabled tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Removed debug function
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled tiny_yolo_v2 due to accuracy issues
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Changed the disabled reason for broken tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled Reshape with no input
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Python formatting with Autopep8
* Minor fix for MYRIAD devices
* Added zero dimension check
*Removed setting batch size for the network
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Set the threshold to larger value for MNIST
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Removed setting higher threshold in provider_test_utils
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Check for --use_openvino in python wheel setup.py
Add openvino modules to the setup script for building the wheel
package only for --use_openvino a build option.
* Removed nullptr checks for GetNode()
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* added tools for doc gen, added doc
* doc updated
* some fixes
* hooked up with build.py
* hooked up with build.py and fail on nonupdated doc
* update
* updated cmake files for trt
* added trt execution provider
* added trt basic test
* removed trt_path action attribute
* Add files via upload
* Update build.py
* Update trt_allocator.h
* fixed issues found by reviewers
* changed cast operator
* added comment for custom kernel implementation
* changed auto to auto&
* changed to function compile APIs for TRT execution provider
* changed to function compile APIs for TRT execution provider
* added new DType DInt64
* adapted to the changes of onnxruntime_c_api
* removed trt kernel (use function compile instead)
* updated onnx-tensorrt submodule
* set default memory type to TRT fused kernel
* resolve merge conflict
* fixed the issue that USE_CUDA conflicts with USE_TRT
* construct graph by adding nodes in topological order
* made changes for Windows
* change buffers type
* bypass HasImplementationOf check for TRT XP because TRT kernel is not registered
* added domain to version info in rebuilt model proto
* added trt to test option list
* added DomainToVersionMap() to GraphViewer
* removed Copy()
* fixed broken code
* format the code to clang format
* used local reference to the frequently used values
* fixed a couple of issues according to reviewers feedback
* fixed a couple of issues according to reviewers feedback
* added python binding for TRT and enable use_cuda when use_trt is on
* fixed a redefinition issue
* changed shared_ptr to unique_ptr on trt engines, and made a few changes required by reviewers
* enabled trtexecution provider for unit tests
* renamed trt to tensorrt
* added tesorrt to python binding
* update submodule onnx and onnx-tensorrt
* made a couple of minor changes based on reviewer's feedback
* added CUDA_CHECK
* removed test code
* fixed broken code after merge
* updated onnx-tensorrt submodule
* added post processing to align trt inputs/outputs with graph inputs/outputs
* updated onnx submodule
* added CUDA fallback for TensorRT and fixed TensorRT cmake issue
* added ci pipeline for tensorrt and removed some redundent code from trt xp
* fixed syntax issue
* updated onnx-tensorrt submodule
* fix trt build problem by: (#602)
1. Add additional /wd for debug build
2. Add io.h for additional targets
3. Bring back mb version of getopt
* Update install_ubuntu.sh
* Update linux-gpu-tensorrt-ci-pipeline.yml
* Update linux-gpu-tensorrt-ci-pipeline.yml
* Update run_build.sh
* Update run_build.sh
* Update run_build.sh
* Update run_build.sh
* fixed the issue that GetKernelRegistry returns nullptr
* merged master to this branch
* moved some data types to private
* fixed tensorrt CI pipeline issue
* customized test data for TensorRT pipeline
* added onnx-tensorrt in json file and fixed an issue in ci script
* added comments
* add option numpy_version to build against the installed numpy version and not 1.15.0 (hardcoded version number), default is still 1.15.0
* add option skip_keras_test to skip keras test even if keras is installed (still enabled by default)
disable unnecessary warnings about ubuntu
* enable option PRIVATE for the compilation of the Python bindings (settings recommended on pybind11 documentation)
* test on debian 9
* Create a project for graph optimizer.
Move optimizer related code to the folder optimizer.
* Fix build failures.
* rebase and fix build failures.
* fix build failure.
* fix build failure with cuda path.
* fix python build failure.
* Move two transformers(memcpy and insert_cast) from framework to optimizer.
* rebase.
* SessionState should not depend on optimizer.
