[Neuron] flatten test parameterization for neuron attention kernels

[liangfu]

This PR include two changes:

• Split the test scripts into 1_core and 2-core test folders
• Refactored test_contexted_kv_attention to flatten the nested parameterization (3 loops → 1 list) while expanding coverage variety. The change reduces test combinations from 64 to 10 carefully selected cases, achieving ~80% CI time reduction. The new test suite covers 2x more parameter ranges - from minimal (1-8 heads) through common (16-32 heads) to large scale (48-64 heads), including edge cases with 1-199 batch sizes. Both precision modes are verified across all scales. All test cases pass with both standard and mixed precision modes.

Related PR: #13245 #14085

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[lingfanyu]

LGTM!

[aws-satyajith]

LGTM. Thanks for this change!