Add an optimizer that can remove leftover Q->DQ pairs. Depending on the model this may help with performance and/or improve accuracy. Optional as it could make things worse so user needs to be aware of this and test what works best for their scenario. Enable with SessionOptions config param `session.enable_quant_qdq_cleanup`
Hide Inlined Hash set and maps guts behind template forward declarations.
Currently CUDA 10.2 compiler can not compile abseil but provider interfaces
use those types in their signatures. InlinedVector seems to be fine.
Introduce core/common/inlined_containers_fwd.h header
* Add experimental API for editing model name
* Change EditModelName to 'SetName'
* Change API to pass c_string
* Update SetName to edit the proto
* Test that the model proto gets changed
* Remove comments
* Skip inbox tests
* Use filehelper path
Co-authored-by: Numfor Mbiziwo-Tiapo <numform@microsoft.com>
Prev merged pull request has a bug:
#10521
It was aimed to detect current CPU core micro-architecture and select a best suited kernel. Unfortunately it assumes that a thread can never migrate from one core to another.
This change tries to fix that problem. It introduces about 2-5% performance degradation on symmetric quantized matmul
Co-authored-by: Chen Fu <fuchen@microsoft.com>
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
* add support for bool type
* add TVM EP support for tests
* include TVM EP in python test pool
* fix pylint
* moved technical imports to a separate file
* clean up post build actions & move _ld_preload.py extension to CMake level
* add files for include TVM EP into CI
* implement custom logger for TVM
* replace TVM logging with ONNX RT logging
* update link for TVM EP tutorial
* clean up TVM EP cmake
* add pybind auto enabling for TVM EP
* fix blank spaces
* code review fixes
* replace print with comment
* add list of EP without TVM EP
* enable onnx tests
* disable contrib ops and ml ops
* reuse Dockerfile.ubuntu
* Move install_tvm_test_dependencies.sh out of Docker context dir, update build definition.
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
Implement bilinear interpolation for Upsample (Resize) 4-D input with the
outermost and innermost scale (usually channel of NHWC) as 1.
Besides, I revert the HandleResize back to the original implementation for
TransposeOptimizerTests.TestResize* tests.
Disable warning about padding for abseil-cpp flat_hash_map.
Disable some warnings from compiling the test proto. This also required removing a line in CMakeList.txt where we move a level 4 warning to level 3. That ends up later on the command line and overrides the `/wd4800`. Couldn't find a way to handle that nicely. As we compile with `/W4` the value of moving 4800 to level 3 in dev mode is unclear so simplest was to remove that. Open to suggestions if there's a better way.
* Add initial helper for optimizing a QDQ format model for usage with ORT.
If a DQ node has multiple consumers it will end up in multiple QDQ node units. This is complicated to handle as each qdq unit could end up being handled by different execution providers. By duplicating the DQ node we simplify this logic.
Generally the duplicate nodes will disappear when the qdq node unit is converted to a single node with a quantized operator. If there are qdq node units that are not able to be converted to use a quantized operator the ORT cleanup (pending) to drop remaining Q->DQ pairs between fp32 nodes can remove any remaining DQ nodes.
* Fix pep8 warning
Co-authored-by: Guoyu Wang <wanggy@outlook.com>
* 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
Extend opset 13 support for:
- Split-13
- Squeeze-13
- Unsqueeze-13
- Reshape-13
- QuantizeLinear-13
- DequantizeLinear-13
- ReduceSum-13
- Resize-13
Also:
- Rename the file where all the opset versions are stored from "OperatorRegistration.h" to "OperatorVersions.h", which will make it much less confusing in the future when looking given there's another file called "OperatorRegistration.h" that corresponds to "OperatorRegistration.cpp".
- Detemplatize many of the OperatorHelper.h constructors, which duplicate multiple instantiations due to the operator helper classes not sharing a common base class, by wrapping them with an adapter. Ideally there would be a common COM base interface that both IMLOperatorKernelCreationContext and IMLOperatorShapeInferenceContext implementation objects would implement, which a wrapper in MLOperatorAuthorHelper.h could QI for.
- Fix style formatting issues in OperatorHelper.h (sorry for the noise).
```
Summary: Total=4679, Passed=4355, Failed=0, Blocked=0, Not Run=0, Skipped=324
```
Corresponding WindowsAI PR:
https://microsoft.visualstudio.com/WindowsAI/_git/WindowsAI/pullrequest/6973645
Related work items: #36672908, #36672926
* apply the same policy for onnxruntime-common as web and node
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* remove old comment
* add restrictions for hybrid cpus
* add unit test to mock hybrid cpu
* attach hybrid flag
* add mocking interface to CpuInfo
* make is_hybrid
* make mock function const
* add force_hybrid for thread pool
* remove header
* Enable Attention op for ROCM EP.
As a note, potential hipify improvements: (1) handle math
contants (attention_softmax.h), (2) correctly generate transpose
options for the GEMM helpers, consider counterpart/dummy API for
CublasMathModeSetter (attention_impl.cu, attention_impl.cu). After
these improvements, we don't need to manually keep copies of the
above mentioned files any more.
* Clean up debugging code.
