* change c++14 to c++11
* add ld lib path for centos
* enable csharp tests on macos
* fix C API test on MacOS + fix manylinux dotnet install
* fix manylinux dotnet install
* fix lib link
Rework TensorSeq in a manner consistent with Tensor and SparseTensor
in terms of type system setup.
Reduce templating. Introduce helpers to ensure the same
data type.
Make OrtValue __dtor not virtual.
Introduce ContainerChecker
* enabme telemetry
* enable telemetry
* set enable telemetry as default
* for debugging
* remove log and set disable telemetry as default back
* delete private file while testing
* resolve comment: mainly add license header, rename macro and update docs
* rewording in privacy.md
* add centos tests to linux cpu ci pipeline
* Disable failing test
* use centos6 instead of centos7
* change back to centos7
* add dotnet runtime dependency
* fix dotnet runtime dependencies
* install dotnet sdk instead of runtimes
* add more dotnet dependencies
* temporary skip failing test
* ix lib path
* reenable failing test
Add support of GPT2 model optimization:
* Match subgraph of Gelu Approximation (using Tanh).
* Fuse LayerNormalization if SkipLayerNormalization is not ready.
* Output model even if embedding layer is not fused.
* Improve Reshape Fusion to improve coverage.
* Refine constant input checking, and output fused op counter.
Update script according to latest op improvements:
* Fusion of Add Bias and Gelu.
* Fuse SkipLayerNormalization and Add Bias.
Other:
* Add ReduceSum for mask as intermediate step.
* Refactor verbose setting.
* Constant folding bug fix/improvements
- Handle constant folding for node that is assigned to a non cpu EP
- Check for errors in optimizer execution frame setup
- Improve CUDA partitioning to look for initializers in parent graphs
- Add unit test
Fixes#2474
* [NupharEP] Add parallel schedule to JIT function name
Update Nuphar docker to use Python 3.6 and ubuntu 18.04
* Update notebook
* Avoid JIT cache file name conflict
* [NupharEP] Enable parallel schedule
* Update TVM with the fix to TVM threadpool to use OpenMP if possible
* Add parallel schedule when trying to vectorize
With this change, BERT squad perf on a 4-core (8 HT) CPU goes from 187ms to 150ms
* Address CR, docs and cmake update
* Doc fix
* Fix mkl
* Fix TVM windows build when using mklml
- Add --skip_tests option to build.py based on github feedback
- Add debug output at end of run_subprocess so it's clearer when the output is from a different process running
- Add check for scipy as it's required by gen_test_models.py for the onnx tests
- Use log.warning instead of warnings.warn for consistency. We use the logger almost everywhere and somewhat randomly used warnings.warn in two places.
- Add check for 'wheel' dependency not being found in setup.py and handle more gracefully
- Fix invalid input name in Keras tests
* Cuda Clip() for op set 11.
* make min_val and max_value input CPU memory directly.
* Remove original cu file useless "#pragma once"
* merge duplicate logic into one class.
