### Details:
- The macOS x64 and arm workflows are broken.
- One of the issues is that `apt` retries are set unconditionally in
various reusable workflows when `apt` is only available on Linux.
- There was no `Smart_CI` job requirement for the `Samples` job in the
ARM mac workflow leading to it being broken.
- Several tests started failing, they are skipped in this PR with an
appropriate ticket.
### Tickets:
- *132596*
---------
Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com>
**Details:** We are going to test OpenVINO Tokenizers conversion
extensions by FE layer tests. It gives better quality integration
between openvino and openvino-tokenizers. For example, operation on
string tensors such as tf.raw_ops.StringLower, tf.raw_ops.StringSplitV2
will supported via OV tokenizers near feature until we move them into
core part.
**Ticket:** 132667
---------
Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
**Details:** Run layer tests for TF FE by default and
use_legacy_frontend for legacy FE. Developers have to add
`use_new_frontend` for running layer tests for TF FE. This is not
convenient. Instead, let us use `use_legacy_frontend` option for legacy
FE that is rarely run.
**Tickets:** TBD
---------
Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
### Details:
- Improved op support for 2024.0 release
- Includes ops required for enabling customer model lightglue
- Also added ops for lora fine tuning
- Added support for options in aot autograd backend
- Added a new option to specify whether to use aot autograd
functionality
- Added a new option to specify decompositions that need to be added
- Added a new option to specify ops that need to be disabled from
executing on OpenVINO
### Tickets:
- https://jira.devtools.intel.com/browse/CVS-116702
- https://jira.devtools.intel.com/browse/CVS-120276
---------
Co-authored-by: ynimmaga <yamini.nimmagadda@intel.com>
* [PT FE] torch.export support
* Apply code style
* Fix build
* Support torch <2.2
* Support more operations
* Update tests/model_hub_tests/torch_tests/torch_utils.py
* Support for model operations
* Support is_causal as kwarg for SDPA
* Update src/frontends/pytorch/src/op/addcmul.cpp
* Update tests/model_hub_tests/torch_tests/test_timm.py
* Support only decoder passed to convert_model
* Fix tests
* Update src/bindings/python/src/openvino/frontend/pytorch/fx_decoder.py
* Update src/bindings/python/src/openvino/frontend/pytorch/fx_decoder.py
Co-authored-by: Ekaterina Aidova <ekaterina.aidova@intel.com>
* Apply suggestions from code review
* Apply suggestions from code review
* Improve testing with caching model
* Apply suggestions from code review
---------
Co-authored-by: Ekaterina Aidova <ekaterina.aidova@intel.com>
* extract cpu func tests into a reusable workflow
* add needs
* check paths
* correct paths
* rm usage of setupvars
* extract samples
* use yaml string
* split mac workflow
* check variables
* try github workspace
* check full dir
* set variables
* try with sub directory
* Revert "try with sub directory"
This reverts commit d891ee3f28.
* extract c++ tests from linux
* change
* use cxx workflow in mac workflows
* add noninteractive
* extract cpu func tests
* rm unused
* enable mac
* fix reusable workflow name
* correct path for sparse-checkout
* extract python UT
* remove unnecessary asterisk
* remove another unnecessary asterisk
* use reusable action for linux cc
* add check for setupvars existence
* check with manually installed opencl
* add components input to samples workflow; rm pr triggers for mac workflows
* add missing needs
* add missing option for deps install script
* use disables in test themselves instead of ifs in workflows
* use reusable workflow for cxx tests in linux arm
* use python reusable workflow in linux arm
* add missing endif
* use self-hosted for samples, add x86_64 constraint for jax
* check paths
* find gompby partial name
* skip failing tests on arm; correct gomp finding for ovc
* check tests
* add debian packages job; use job_ prefix for reusable workflows with jobs
* extract tf hub model tests
* extract tf model hub perf tests
* extract pytorch models tests
* do not use container on GHA runners
* extract onnx runtime
* add missing deps
* skip test for linux arm
* rm always()s
* fix quotes
* correct paths
* correct ifs, check dir for onnxruntime
* correct path for onnxruntime utils folder; install python3
* use self-hosted as input
* check for self-hosted runner via name, pass version
* skip cpu plugin unittest
* check cxx tests
* rm pr trigger
Andrei Kashchikhin