* seperate the training python module; share the execution proivder instance
* fix build break
* fix cuda test crash; reorg the python module code base
* se correct env
* use provider customized hash func
* fixbuild break
* fix rocm break
* use const ref in argument
* rename the file
* move hash func to trainiing module
* Revert "Cleanup C# bindings to add EP (#8810)"
This reverts commit b21ea00020.
* Add back in a minimal set of changes.
Provide stubs in for a limited set of things
- things called from C# using a static lib of ORT built for mac/ios
- things in OrtApis that are not included in the build by default
- things in OrtApis that are excluded in a minimal build
* Cleanup order or EPs in test
* Fix unused function in ROCM build
Add cmake parameter and #ifdefs to allow for disabling sparse tensor support. This comes with a significant binary size cost so we want to be able to exclude it in a minimal build.
Fix C# add EP bindings.
Add stubs to ORT so that if EP is not included in the build we return a graceful error message.
Move declaration of stubs into C API and out for EP so they're in one place and are easier to use (no extra header required in the C/C++ world and consistent with the CUDA EP setup).
Fix inconsistency in ROCM EP.
Cleanup a few other things.
Add IsSparseTensor
Add CreateSparseTensor
Add utilities and test fully sparse instantiation
Fully sparse blocksparse
Add test and docs for fully sparse tensor instantiation
Rework creation API
Use API
Non string API
Retrofit of existing String API
Add tests
Add documentation
Address build issues (Winml pending)
Add inference test
Bump binary size
Add ifdef DISABLE CONTRIB
* Do not copy the model_data when session is started by CreateSessionFromArray
* Add config option for disabling copy model bytes
* Add one additional test
* Address CR comments
SparseTensor support
Implement Builder pattern
Fix support for 1-D and 2-D COO indices
Implement and test CSR support.
Handle shape inference for SparseTensors
Implement conversion for COO, CSR and tests.
Address the case where constant sparse initializer is the output.
Implement test infra for SparseTensors
Implement SparseDenseMatMul for Csr and COO and tested it.
Add hash for SparseToDenseMatMul
Finish shared provider refactor
Refactor GetOrCreate to Create
Working on py interface
Expose OrtDevice and use it in allocate_numpy
Adjust Sparse interfaces, add support for string SparseTensor. Add tests.
Add and test to_cuda()
Add accessors to format specific indices
Test values and indices views, read-only flag, after GC access
Add sparse related methods to OrtValue
Re-work SparseTensor wrapper, add OrtValue methods
Rework numpy_array_to_cuda/to_cpu
Add run_with_ort_values
Add models and test sparse_mat_mul with run_with_ort_values
Refactor sparse tensor to use a single buffer
Ifdef x86 Eigen CSR sparse matmul implementation
Exclude broken test, check for string type when copying cross device
Split pybind schema, regenerate docs, add exclusion
Conditionally exclude schema module
Update docs fix cuda build
Add test to a filter and renerate JS docs
Add conversion and test string support for sparse tensors
Exclude conversion utils from minimal build
Add CUDA Memcpy and adjust provider interfaces
* Add helper to check if node provides a graph output. The current approach unnecessarily creates a vector when most of the optimizers only care about a true/false response.
* Undo accidental change
* Fix a couple of issues due to copying from larger set of changes.
Switched the code to C++17. To build ONNX Runtime on old distros like CentOS 7, you need to install a newer GCC from additionary repos. If you build onnxruntime with the newer GCC, typically the result binary can't be distributed to other places because it depends on the new GCC's runtime libraries, something that the stock OS doesn't have. But on RHEL/CentOS, it can be better. We use Red Hat devtoolset 8/9/10 with CentOS7 building our code. The new library features(like std::filesystem) that not exists in the old C++ runtime will be statically linked into the applications with some restrictions:
1. GCC has dual ABI, but we can only use the old one. It means std::string is still copy-on-write and std::list::size() is still O(n). Also, if you build onnxruntime on CentOS 7 and link it with some binaries that were built on CentOS 8 or Ubuntu with the new ABI and export C++ symbols directly(instead of using a C API), the it won't work.
2. We still can't use std::optional. It is a limitation coming from macOS. We will solve it when we got macOS 11 build machines. It won't be too long.
3. Please avoid to use C++17 in CUDA files(*.cu). Also, the *.h files that they include(like core/framework/float16.h). This is Because CUDA 10.2 doesn't support C++17. You are welcome to use the new features in any *.cc files.
* prepare for C# to configure provider options
* add c# code
* revert modification
* Add update provider info configuration in trt ep side
* fix bugs
* fix bug for compiler error C2259
* Add c# test
* fix bug
* fix bug
* Properly deal with string
* Add c# api for accepting trt provider options
* fix bug
* Modify C# test
* add shared lib test
* Add get provider options functionality
* clean up
* clean up
* fix bug
* fix bugs for CI
* Fix bugs for CI and documentation
* Move TRT EP provider options related functions out of C API
* revert
* fix bug
* refactor
* add check for provider options string
* code refactor
* fix CI bug
* Fix CI bugs
* clean up
* fix bug
* Fix bug for Post Analysis
* fix accidental bug
* Add API_IMPL_BEGIN/API_IMPL_END
* clean up
* code refactor
* code refactor
* fix CI fail
* fix bug
* use string append
* Change the code to better handle strncpy and string append
* Output error message to android log instead of stderr
* Address CR comments, move macro to a helper function
* Address CR comments
* Fix ort minimal build break
* Update Vitis-AI EP support multiple DPU targets & specifically arm64 dpuczdx8g target
* Fix Vitis AI docker and default PyXIR versions
Co-authored-by: Jorn Tuyls <jornt@xilinx.com>
Co-authored-by: Jorn Tuyls <jornt.tuyls@gmail.com>
* First iteration of making cuda a shared provider.
Separated out shared OpKernel change, so doing this to merge with that change.
* More cuda shared library refactoring
* More cuda shared library refactoring
* More build options tested, converted the training ops over.
* Fix merge breaks
* Fix submodules
* Fix submodules
* Fix submodules
* Fix python
* Fix compile errors
* Duplicate symbol fix
* Test fix for ROCM provider
* Another ROCM test workaround
* ROCM Build Test
* ROCM build fix
* ROCM
* ROCM
* ROCM
* ROCM
* ROCM
* ROCM test
* Reduce header dependencies
* Remove redundant namespace
* Test fix for linux
* Fix linux build
* Fix Eigen build error
* Fix unused parameter warning
* Test link error
* Another linker test
* Linker test
* Linker test
* Another test
* Another build test
* Fix linux link error
* Build test
* Fix control flow ops to use common base class with core code
* Remove extra qualifiers
* Fix template syntax for linux
* Fix cuda memory leak
* Fix pybind
* Test disabling cast
* Cleanup
* Restore cuda in test
* Remove more header dependencies
* Test not adding cuda provider to session
* Make GetProviderInfo_CUDA throw
* No-op cuda provider creation
* Fix some setup issues
* Fix memory cleanup on unload
* Diagnostics
* Don't unload library
* Add diagnostics
* Fix deleting registry at right time.
* Test disabling profiler
* Fix merge break
* Revert profiler change
* Move unloading of shared providers into Environment
* Free more global allocations before library unloads
* Add more diagnostics
* Move unloading back to the OrtEnv as there are multiple Environments created during a session.
Remove some library dependencies for tests.
* Fix more cmake files
* ERROR -> WARNING
* Fix python shutdown
* Test not using dml in pipeline
* Change python version and disable dml
* Update python version
* Test adding unload method for shared providers
* Disable DLL test
* Python test
* Revert "Python test"
This reverts commit c7ec2cfe98.
* Revert "Disable DLL test"
This reverts commit e901cb93aa.
* Revert "Test adding unload method for shared providers"
This reverts commit c427b78799.
* Point to RyanWinGPU
* Revert python version
* Fix id_to_allocator_map
* Another python exit test
* Remove extra debug messages
Try a more clean python shutdown through DllMain
* Revert DllMain idea, it didn't work
* Merge conflicts
* Fix merge with master issues.
* Comments
* Undo edit to file
* Cleanup + new training ops
* Revert yml changes
* Fix another merge error
* ROCM fix
* ROCM fix v2
* Put back Linux hack, it is necessary
* Stupid fixes
* Fix submodule out of sync
* ROCM fix 3
* ROCM 4
* Test java fix
* Fix typos
* Java test on my VM
* Fix build error
* Spotless fix
* Leave temp file around to load properly
* Fix cleanup on exit
* Fix break
* Java comments
* Remove LongformerAttentionBase workaround
* Spotless fix
* Switch yml back to regular build pool
* Revert "Switch yml back to regular build pool"
This reverts commit be35fc2a5a.
* Code review feedback
* Fix errors due to merge
* Spotless fix
* Fix minimal build
* Java fix for non cuda case
* Java fix for CPU build
* Fix Nuphar?
* Fix nuphar 2
* Fix formatting
* Revert "Remove LongformerAttentionBase workaround"
This reverts commit 648679b370.
* Training fix
* Another java fix
* Formatting
* Formatting
* For orttraining
* Last orttraining build fix...
* training fixes
* Fix test provider error
* Missing pass command
* Removed in wrong spot
* Python typo
* Python typos
* Python crash on exit, possibly due to unloading of libraries.
* Remove test_execution_provider from training build
Only enable python atexit on windows
Remove assert on provider library exit
* Still can't unload providers in python, alas.
* Disable Nvtx temporarily
* MPI Kernels for Training
* MPI Kernels part 2
* Patch through INcclService
* Oops, wrong CMakeLists
* Missing namespace
* Fix missing ()
* Move INcclService::GetInstance around to link nicer
* Missing }
* Missing MPI libraries for Cuda
* Add extra GetType functions used by MPI
* Missing Nccl library
* Remove LOGS statements as a test
* Add in a couple more missing GetType methods
* Update comments
* Missed a logging reference in mpi_context.h
* Convert aten_op to shared (due to marge with master)
* Test moving DistributedRunContext instance into shared provider layer
(with purpose error to verify it's being built properly)
* Test passed, now with fix
* Missing static
* Oops, scope DistributedRunContext to just NCCL
* Merge related issues and code review feedback.
* Merge error
* Bump to rel-1.9.1 (#7684)
* Formatting
* Code review feedback for Java build on non Windows
* Remove cupti library dependency from core library
* Test Java pipeline fix
* Linux build fix
* Revert "Linux build fix"
This reverts commit a73a811516.
* Revert "Remove cupti library dependency from core library"
This reverts commit 6a889ee8bf.
* Packaging pipeline fixes to copy cuda shared provider for tensorrt & standard packages
* Add cuda to Tensorrt nuget package
* onnxruntime_common still has a cuda header dependency
Co-authored-by: ashbhandare <ash.bhandare@gmail.com>
* Merge set custom allocator to master
* Add documentation for the new API.
Reset global env in testCustomArenaAllocator so won't have a registered allocator of type arena (from previous test)
* Add a session option config that will allow to disable loading model with initializers that have an external data (+test it).
* Add the model used for the test and its external initializers data
* Change the session config option that disable external initializers to a build option.
* Addressing PR comments
* Moved GraphTransformerConfiguration to a separate file and added strategy option to PropagateCastOps transformation.
* Added testing both FloodFill and InsertAndReduce stratigies for cast propagation.
* Added AddConsumer and RemoveConsumer functions to in graph.h for efficient graph editing.
* Added PropagateCastOps code documentation
* Added GraphTransformationConfiguration class hierarchy information
* Added RemoveInputOutputUpDownCasts
Fix an issue where a log message got skipped.
A log call like this:
```
LOGS(...) << "message";
```
expands to something like this:
```
if (<output enabled>)
logging::Capture(...).Stream() << "message";
```
This if statement without brackets is handy for logging arbitrary arguments with the `<<` operator. However, it has other drawbacks like possibly associating with a subsequent `else`.
```
if (cond)
LOGS(...) << "a";
else
<do something> // not run when !cond
// equivalently:
if (cond)
if (<output enabled>)
logging::Capture(...).Stream() << "a";
else
<do something> // not run when !cond
```
Updated the logging macros to handle this case by replacing `if (<enabled>) logging::Capture(...).Stream()` with `if (!<enabled>) {} else logging::Capture(...).Stream()`.
Thanks @tlh20 for the idea for the fix!
