GitLab

Consolidate the vectorize and preload
Add vectorization to reduction
Co-authored-by: kahmed10 <15948690+kahmed10@users.noreply.github.com>

prioritizing int8 over int8x4 when it is applicable
Amend return to continue in apply loop
Adding error handling in case int8x4 compilation failed
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>

Break up the gpu::code_object  print to show the actual kernels...

gpu::code_object::add_kernel: 0.646121ms, 5%
gpu::code_object::mul_kernel: 0.623822ms, 5%
gpu::code_object::add_mul_erf_add_mul_mul_kernel: 0.498902ms, 4%
gpu::code_object::mul_add_kernel: 0.478352ms, 4%

clang++ complained about not knowing of std::string for a file
Authored-by: Yves Renier <102358016+yves-renier@users.noreply.github.com>

update protobuf version

Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 2.6.4 to 2.7.2.
- [Release notes](https://github.com/tensorflow/tensorflow/releases)
- [Changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md)
- [Commits](https://github.com/tensorflow/tensorflow/compare/v2.6.4...v2.7.2

)

---
updated-dependencies:
- dependency-name: tensorflow
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Chris Austen <causten@users.noreply.github.com>

Following up on issue #1166 and PR #1220. Using the same approach as in #1220 for parallelizing the eval calls, we can significantly reduce the time spent on eliminate_contiguous pass.

Addressing issue #1166 - propagate_constant pass currently uses a recursive approach to find all instructions in a module that can be evaluated to a literal and performs the replacement in the same call.

New approach:

Perform single pass though instructions in the module to determine which instructions can be evaluated
Evaluate selected instructions in parallel
Replace the selected instructions with the corresponding literal

* Upgrade to cppcheck 2.8