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vLLM/vllm/model_executor/layers/attention_layer_base.py
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Harry MellorandClaude Opus 5 8c1557a79c Add pydocstyle to the ruff rules (#52136)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
Signed-off-by: Harry Mellor <hej.mellor@gmail.com>
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-16 16:44:29 +00:00

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Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Base class for attention-like layers."""
from abc import ABC, abstractmethod
import torch
from vllm.config import VllmConfig
from vllm.v1.attention.backend import AttentionBackend, AttentionImpl
from vllm.v1.kv_cache_interface import KVCacheSpec
class AttentionLayerBase(ABC):
"""Base class for attention-like layers (Attention, Mamba, etc.)
that support the v1 engine.
This provides a common interface for getting attention backends
from different layer types.
"""
impl: "AttentionImpl"
supports_dcp: bool = True
def bind_kv_cache(self, kv_cache: torch.Tensor) -> None:
"""Bind the allocated KV cache tensor to this layer.
The default stores the cache view as-is; subclasses (e.g. Mamba)
override this to unpack the raw buffer into per-state views.
"""
self.kv_cache = kv_cache
@abstractmethod
def get_attn_backend(self) -> type[AttentionBackend]:
"""Get the attention backend class for this layer."""
pass
@abstractmethod
def get_kv_cache_spec(self, vllm_config: VllmConfig) -> KVCacheSpec | None:
"""Get the KV cache spec for this layer.
May be None if the layer does not need KV cache.
"""
pass