Speed up cpu-unit CI

[gagika]

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[codecov]

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[github-actions]

🤖 Hi @gagika, I've received your request, and I'm working on it now! You can track my progress in the logs for more details.

[github-actions]

## 📋 Review Summary

This Pull Request successfully introduces several optimizations to speed up the cpu-unit CI. By increasing parallelism, introducing test duration recording for better load balancing, and reducing the complexity of MoE compilation tests, the CI efficiency is significantly improved without compromising the validity of the tests.

🔍 General Feedback

• Excellent CI Optimizations: The use of pytest-split with stored durations on scheduled runs is a very effective way to handle imbalanced test shards.
• Smart Model Overrides: Using override_model_config to reduce the number of layers in compilation tests is a high-impact change that drastically reduces compilation overhead.
• Improved Maintainability: The refactoring of MoE tests into helper methods makes the test suite cleaner and easier to maintain.

[github-actions]

🟢 Recording per-shard durations on scheduled runs is an excellent strategy for optimizing CI load balancing. Merging these artifacts into a central `.test_durations` file will allow `pytest-split` to balance future runs more effectively using the Least Progress Time (LPT) algorithm.

[github-actions]

🟢 Reducing the `compile_topology` and `compile_topology_num_slices` here is appropriate for a unit/compilation test. It speeds up the CI by requiring fewer resources and less time to verify that the pipeline parallelism logic compiles correctly.

[github-actions]

🟢 Using `override_model_config=true` and reducing `base_num_decoder_layers` to 8 is a great optimization for compilation tests. This significantly reduces the graph size and compilation time while still exercising the necessary code paths for MoE models.

[github-actions]

🟡 Skipping `test_diloco_two_slices` helps stabilize the CI, but it would be beneficial to link a tracking issue or add a TODO explaining why this test is being skipped and if it's intended to be re-enabled later.