* Update to flatbuffers v2.0.0 (#10866)
* Fix Reduced ops pipeline (#10861)
* Fix a couple of issues with the python package tools (#10858)
* Tweaks to the model utils
* Add handling for a dim_value of -1 when replacing the entire input shape. This occurs in models exported from PaddlePaddle
* make pytorch helpers accessible in package
* make QDQ helpers accessible in package
* Fix wrong percentile values returned during calibration (#10847)
* Use numpy.percentile to get the lookup value.
* Use 1.0 as float value rather than integer.
* Add missing cdf parameter for `np.percentile`.
* Use 100. instead of 1.0
* Remove print.
* Update from @yufenglee
* Add support for opset 16 to transpose optimizer. (#10841)
* Add support for opset 16 to transpose optimizer.
Only change required is for GridSample to be added to the layout sensitive ops. The existing handling for layout transpose works with that as the first input and first output are layout sensitive.
Update the optimize to be able to return an error message if it fails.
* Use separate build directories for full and mobile iOS packages. (#10835)
* Address performance issue with abseil flat_hash_table. (#10819)
When returning by value in a cross DLL call, the hash table
even though containing all the entries that are originally there
can not find at least some of them. Reverting to std::unordered_set
pending further investigation.
* Mark end of version 11 C API. (#10803)
* Mark end of version 11 C API
* Add static_assert
* avoid using LocalFree on FormatMessageW buffer (#10796)
* remove local free
* Remove local free from onnxruntime
* don't allocate
* Change to use constexpr to satisfy CPU build warning
* Integrate C-API tests into Pipelines for release packages (#10794)
* add c-api test for package
* fix bug for running c-api test for package
* refine run application script
* remove redundant code
* include CUDA test
* Remove testing CUDA EP temporarily
* fix bug
* Code refactor
* try to fix YAML bug
* try to fix YAML bug
* try to fix YAML bug
* fix bug for multiple directories in Pipelines
* fix bug
* add comments and fix bug
* Update c-api-noopenmp-packaging-pipelines.yml
* Remove failOnStandardError flag in Pipelines
* Detect runtime CUDA JIT and warn the user (#10781)
* Use cudaMalloc vs cudaDeviceSynchronize and show the total time
* Update convert_onnx_models_to_ort.py to support runtime optimizations. (#10765)
Add runtime optimization support to ONNX -> ORT format conversion script.
Replace `--optimization_level`, `--use_nnapi`, and `--use_coreml` with a new `--optimization_style` option.
* Add multithreading test and put a lock on nvinfer1::createInferRuntime() for TRT EP (#10714)
* Add multithread unit test and put lock on library call
* update code
* remove debug code
* add comment
* add one session multi-threads inference
* Put lock for build engine all the time
* Update naming and comment
* remove unnecessary lock
* Revert "remove unnecessary lock"
This reverts commit 9c2317b1d2273dec0ebdeb52160bc757839e5edc.
* Fix handling of nodes inserted by NHWC transformer. (#10904) (#10925)
* Revert "Upsample support NHWC (#10554)" (#10917)
This reverts commit bd08f11a58.
Co-authored-by: Yufeng Li <liyufeng1987@gmail.com>
* [python API] Change raise import error when `C:\Windows\System32\vcruntime140_1.dll` is not found to warning (#10927)
* remove throw if C:\\Windows\\System32\\vcruntime140_1.dll cannot be found
* Add comments and update warning message
* adding back accidentally removed line
Co-authored-by: gwang0000 <62914304+gwang0000@users.noreply.github.com>
* [js] Create npm packaging pipeline (#10886)
* create npm packaging pipeline
* fix indentations
* Update npm-packaging-pipeline.yml for Azure Pipelines
* Update npm-packaging-pipeline.yml for Azure Pipelines
* Update npm-packaging-pipeline.yml for Azure Pipelines
* react-native-ci as a template
* fix typos
* fix template paths
* add a depencendy
* change a stage name
* set different artifact name for each package
* fix typo
* Update npm-packaging-pipeline.yml for Azure Pipelines
Set a build Id for node npm package as a parameter
* Update npm-packaging-pipeline.yml for Azure Pipelines
Set a build Id for node npm package as a parameter
* Update npm-packaging-pipeline.yml for Azure Pipelines
* Follow up update for python API checking if `vcruntime140_1.dll` is available (#10927) (#10933)
Co-authored-by: Hariharan Seshadri <hasesh@microsoft.com>
Co-authored-by: Scott McKay <skottmckay@gmail.com>
Co-authored-by: Funtowicz Morgan <mfuntowicz@users.noreply.github.com>
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
Co-authored-by: Dmitri Smirnov <yuslepukhin@users.noreply.github.com>
Co-authored-by: Pranav Sharma <prs@microsoft.com>
Co-authored-by: Ryan Lai <rylai@microsoft.com>
Co-authored-by: Ryan Hill <38674843+RyanUnderhill@users.noreply.github.com>
Co-authored-by: Yi-Hong Lyu <yilyu@microsoft.com>
Co-authored-by: Yufeng Li <liyufeng1987@gmail.com>
Co-authored-by: Guoyu Wang <62914304+gwang-msft@users.noreply.github.com>
Co-authored-by: gwang0000 <62914304+gwang0000@users.noreply.github.com>
Co-authored-by: Sunghoon <35605090+hanbitmyths@users.noreply.github.com>
Current training optimizer kernels include CPU headers
that affects changes that we can make in the CPU code with C++14 compiler and
other refactoring efforts. Rearrange the kernel according to the established patterns
and do not include headers that are not needed.
Work on minimizing memory management calls by
reducing number of allocations and copies.
Replace std::unordered_set to InlinedHashSet
and add usage of InlinedVector.
Employ std::move() to minimize copying and memory allocations.
Remove copying of the const shared data into each of the
PropagateCast transformer instances.
Move inlined_containers.h header to include/common
Adjust AsSpan imlementation for C++ < 17
* Fix incorrect type constraint registration for RoiAlign. This led to the input type not actually being checked when matching a kernel as the invalid constraint name is treated as a missing optional input.
* fix missing dependency for the unit test exe. Whilst it doesn't link against the CUDA providers lib, without the dependency VS doesn't know it needs to rebuild the library if there are changes.
* Add check for invalid type constraints.
* Fix invalid registrations for other kernels.
* Add hash replacement logic to provide backwards compatibility in ORT format models when the registration is fixed.
* Add tests
* Fix UT
* UT
* UTs
* enable ROCm UT
* fix build attempt
* minor
* fix UT
* fix UT
* fix UTs
Co-authored-by: Ethan Tao <ettao@microsoft.com@orttrainingdev7.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: root <root@GCRAMDRR1-MI100-087.redmond.corp.microsoft.com>
* Export numpy_T as onnx transpose
* further fixes, test
Co-authored-by: Aishwarya Bhandare <aibhanda@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Add abseil and inlined containers typedefs
Introduce TensorShapeVector for shape building.
Use gsl::span<const T> to make interfaces accept different types of vector like args.
Introduce InineShapeVectorT for shape capacity typed instantiations
Refactor cuda slice along with provider shared interfaces
Refactor Concat, Conv, Pad
Build with Conv Einsum and ConvTranspose refactored.
Remove TesnorShape::GetDimsAsVector()
Refactor SliceIterator and SliceIteratorBase
Refactor broadcast
Refactor Pads for twice as long
Remove memory planner intermediate shapes vector
Refactor orttraining
Fix passing TenshroShapeVector to tests
Remove abseil copy and submodule, use FetchContent_Declare/Fetch
Path with separate command
Make RocmAsyncBuffer accept anything convertible to span. Adjust Linux GPU pipeline.
* clearing map for eager mode backends
* clearing map for eager mode backends manager
* making OrtBackendsManager an extern variable and trying to delete it
* cleaning backends manager when the python interpret exits
* adding ifdef for eager mode code
* disabling warning for pybind state file
* disabling warning for python module file
* running clang auto format and reducing redundancy
* remove new line
* moving declaration to a new header file
* adding the header file for eager mode for python module
* removing source files for eager mode
* add source file for python module in eager mode
* Update orttraining/orttraining/python/orttraining_python_module_eager.h
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
* fix deadlock in model.train model forward run only
* fix tests
* clear the grad_fns before every forward run
* add clean up on exit
* fix
* refine code comments
* fix aten view op
* add test case
* fix signature
* fix the build
Co-authored-by: Cheng Tang <chenta@microsoft.com@orttrainingdev9.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
In a reduced ops build, some source files get updated. This change moves the updated files into the build directory. This way, it is easier to simultaneously manage different build directories (with possibly different reduced ops configurations) based on a single source directory.
