* priority-based exec order
* disable 1 failing test
* fix UT
* more comments
Co-authored-by: Ethan Tao <ettao@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Implemented following change to avoid the error when using both --use_external_data_form and --precision int8 with GPT2LMHeadModel, which results in
line 161, in save_external_data; open(external_data_file_path, 'ab').close()
FileNotFoundError: [Errno 2] No such file or directory:
This may also be related to the identified bug #6047.
* add config allow_spinning
* add config allow_spinning
* set true as default
* split configures for inter and intra ops
Co-authored-by: Randy Shuai <rashuai@microsoft.com>
* Change msbuild condition for UAP
* update .netcore target as well
* create nuget packages with _native path
* validate path under _native directory for windowsai package
* pep8
* add diagnostic error message
* pep8
* use baseame
* lib\uap10.0
* uap10
* build\\uap10.0
* Manually binplace winmds into appx when PackageReference is used.
* always binplace winmd regardless of packagereference since c# should work with packages.config also
* resolve all paths to full paths to avoid some reference warnings
* move winmds out of lib folder to prevent automatic component registration
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
* Add more asserts on forward outputs
* Found one more failing case
Co-authored-by: Sherlock Huang <bahuang@OrtTrainingDev3.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
In the previous shared providers there aren't many OpKernel classes, and the existing Provider_OpKernel wrapper was fine. With the opposibility of making Cuda a shared provider, having this need to be changed per OpKernel adds a lot of complexity.
It was fairly straightforward to make OpKernel work with shared providers with minimal changes.
In this change, the ONNX_OPERATOR_* macros can also be shared with the shared providers.
Adds support for required types to the op kernel type control infrastructure. Required types are always enabled.
Added int64 as a required type for certain ops.
* update Attention operator spec to support pruned model
* update Attention and QAttention cpu & cuda kernel
* Fix invalid embed layer norm fusion test models.
* Added required_grad attribute to YieldOp
* Chagened YieldOp attribute to hold the indices of the required gradient outputs from the count, and removed the code reordering the outputs.
* Changed backward_output_grad_names to a map from backward output gradient name to the corresponding output index.
* Handle case where bias_name is already quantized
If bias is shared between multiple nodes and we've already quantized it, just return the quantized name from the map
* Remove qType attribute from QuantizedValue and QuantizedInitializer
These are unused (and were incorrectly set in the case of int8 quantization)
* Add Reshape op to quantizer
* Add test for Reshape quant
* Fixed issue in python cmake to update wheel package
* Fixes python cmake issue for OV EP
Added post build step for libonnxruntime_providers_openvino
that copies the updated libonnxruntime_providers_openvino.so file
to /onnxruntime/capi directory every time this target is rebuilt.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Removed post_build step from onnxruntime_python.cmake
Now that we have added the post build step to copy
onnxruntime_providers_openvino.so and providers_shared.so
to /onnxruntime/capi directory in onnxruntime_providers.cmake file.
so removing the duplication of the same from here.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixed python cmake issue for OpenVINO-EP
->Fixed issue for both Linux and windows
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
Co-authored-by: MaajidKhan <n.maajidkhan@gmail.com>
