ViperEkura
57729fd92d
- Replace is_causal + causal_offset with unified causal_offset (-1 = off, >=0 = first Q pos)
- Causal and mask can now coexist (was mutually exclusive)
- Add stride-based addressing for Q/KV/O (layout-agnostic, zero-copy)
- Add layout param ("bhld"/"blhd") parsed in Python, passed as int to C++
- Support 2D [batch, kv_len] and 3D [batch, q_len, kv_len] mask
- Vectorize paged KV gather in Python fallback (was per-token Python loop)
- Extract shared helpers: compute_num_splits, alloc_split_partials, dispatch_head_dim
- Unify paged_decode entry via attn_pack_paged_params
- Update mma_softmax_tile for 3D mask with per-row qrow indexing
30 lines
1.0 KiB
Python
30 lines
1.0 KiB
Python
"""CUDA attention kernel wrappers with torch fallback.
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Public API:
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- ``attn_decode`` — single-query decode attention
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- ``attn_prefill`` — multi-query prefill attention
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- ``attn_paged_decode`` — paged decode attention (direct page-table access)
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Interface (shared by all wrappers):
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causal_offset: -1 = non-causal; >=0 = absolute position of first Q token
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mask: 2D [batch, kv_len] or 3D [batch, q_len, kv_len] (bool, True = keep)
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scale: 0.0 = auto (1/sqrt(head_dim)); >0 = explicit
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layout: "bhld" (default) or "blhd"
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Causal and mask can coexist — both are applied simultaneously.
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Each wrapper dispatches to its compiled CUDA kernel (``astrai.extension.attn_*``)
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when available, otherwise falls back to ``torch.nn.functional.scaled_dot_product_attention``.
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"""
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from astrai.extension.loader import KERNEL_NAMES, is_available
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from astrai.extension.ops import attn_decode, attn_paged_decode, attn_prefill
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__all__ = [
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"attn_decode",
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"attn_paged_decode",
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"attn_prefill",
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"is_available",
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"KERNEL_NAMES",
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]
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