**Description**:
Enforce no repetition of n-grams. Scores are set to `-inf` for tokens that form a repeated n-gram if added to the back of the input_ids.
**Motivation and Context**
Needed by transformer models in sequence generation algorithms (greedy search and beam search). This module has heavy impact on performance, and can be highly parallelized.
* Update the operator documentation generation
- Make layout a little nicer
- Update to latest supported operators including training
- Fix some links that are broken when the docs content is copied to github-pages
- Fix incorrect usage of 'onnx.ai.ml' as the default domain
- ML ops are now separated from the real default domain of 'onnx.ai'
- Include CPU, CUDA and training kernels
- exclude DNNL as it's not an EP we own
* There are separate paths for CUDA and CUDNN as they are not guaranteed to be in the same location on a Windows machine. Use the CUDNN path when looking for the CUDNN library.
* Enable validation of both contrib ops and operator kernels in build
Filter generation so it's deterministic
Add ability for CI to publish the md files as build artifacts if they differ so a developer can download and add to their PR to resolve any diffs.
Remove workarounds for github-pages as that will now link to the github docs which display correctly
* checkin
* add 4dmask support in attention cuda op
* trim
* add comments
* fix build/test error
* review comments and add tests
* sync doc
* review comments
* minor change
Implement various improvements related to reordering a tensor for use by NCHWc operations:
Relax the requirement that the input channel count must be a multiple of the NCHWc block size (either 8 or 16 depending on ISA). The requirement now is that the channel count must be a multiple of 4. The implementation of MlasReorderInputNchw would need further work to support relaxing this further, but I don't have any models where I've observed this to be necessary yet.
Support fusing a Transpose(NHWC->NCHW) into a following ReorderInput. ReorderInput now has a channels_last attribute as was done in the past for ReorderOutput. This helps with models converted from TF where the converter is unable to remove all Transpose operations.
Add threading support to ReorderInput to accelerate performance (ReorderOutput will come later).
* Implement qlinear concat and unit test.
Add quantization tools for QLinearConcat and it quantization tests.
* Add kernel def hash for QLinearConcat.
* Change according to PR. Add qdq transformer support for QLinearConcat.
* Add QDQ Transformer unittest. Fix typo on domain.
* remove dup logic of no use.
* fix x86 build error.
* Update operator docs.
* Intial commit
* Rename DynamicPad to Pad
* More changes
* Add Unique operator
* Revert accidental check-in
* Fix CUDA Pad to align with changes
* More changes
* Fix more CUDA pad source files
* More fixes
* More changes
* More changes
* Avoid vector copy
* Update vector validation logic
* Fix build failures
* Fix build
* Fix build failure
* Fix tensorrt build
* add --gen_doc to ci_build
* make gen-doc conditional to build/test step
* some fix in the git diff check
* some more trick on doc diff
* updated for input/output
* updated the contrib operator doc
* fix on missing input output descriptions
* fixed the problem of missing doc string, due to protobuf optimization
* fix
* revert last change
* moved gen_doc.py to /tools/python
* fixed typo
* added tools for doc gen, added doc
* doc updated
* some fixes
* hooked up with build.py
* hooked up with build.py and fail on nonupdated doc
* update
