* Update the README.md for the release.
* polish the code
* add the mobile section
* update the example code in the README.md
* correction on pytorch tutorial
* Support the tensor renaming for the embedded graph
* Add ORT verifying step in the conversion.
* make the gpt-e2e work
* Support the loop in mytorch
* gpt2 end-to-end works
* Polish the code and fix the unit test.
* initial checkins
* restructure the implementation.
* refine the Python interface
* Finalize the interface.
* Add the custmop class for the customization.
* Test the eager_op with vector_to_string customop
* Refine the customop conversion interface.
* initial onnx builder
* Runable with incorrect result.
* reformat the onnx_ops calls
* a few of operators working on tracing
* handcraft all op conversion
* Add the unit testing for mytorch
* unit test passed.
* Add some documents...
* Move non-torch API into onnxruntime_customops.utils module.
* Fix the unit test issues.
* Fix some typos.
* Added getting started instructions for Windows
Signed-off-by: Tom Wildenhain <tomwi@microsoft.com>
* Created a tutorial for converting models with custom ops. WIP
* Removed long outputs
* Changed to keras syntax and added setup instructions
Co-authored-by: Wenbing Li <10278425+wenbingl@users.noreply.github.com>
Wenbing Li
TomWildenhain-Microsoft