Add paged attention support

[cyanguwa]

Description

This PR adds paged attention support for FusedAttention, FlashAttention, and UnfusedDotProductAttention.

• KV cache is maintained in 'bshd' format, and it supports FP32/FP16/BF16, not FP8 yet
• Context parallelism is not supported with KV cache
• FusedAttention and UnfusedDotProductAttention support page_size >= 16, and FlashAttention supports page_size >= 256
• All backends support both pure generation and mixed generation/context in the batch
• FlashAttention supports paged attention through flash_attn_varlen_func, not flash_attn_with_kvcache, due to some numerical issues
• UnfusedDotProductAttention supports paged attention by converting paged cache tensors to non-paged, before attention

Type of change

• Documentation change (change only to the documentation, either a fix or a new content)
• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• Infra/Build change
• Code refractor

Changes

Please list the changes introduced in this PR:

• Add paged attention support for FusedAttention, FlashAttention, and UnfusedDotProductAttention

Checklist:

• I have read and followed the contributing guidelines
• The functionality is complete
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes

[cyanguwa]

/te-ci pytorch L0