vllm/vllm/attention/selector.py
2025-11-19 16:24:55 +00:00

263 lines
8.0 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import inspect
import os
from collections.abc import Generator
from contextlib import contextmanager
from functools import cache
from typing import cast, get_args
import torch
import vllm.envs as envs
from vllm.attention.backends.abstract import AttentionBackend
from vllm.attention.backends.registry import (
MAMBA_TYPE_TO_BACKEND_MAP,
AttentionBackendEnum,
MambaAttentionBackendEnum,
)
from vllm.config.cache import CacheDType
from vllm.logger import init_logger
from vllm.utils import STR_BACKEND_ENV_VAR
from vllm.utils.import_utils import resolve_obj_by_qualname
logger = init_logger(__name__)
def get_env_variable_attn_backend() -> AttentionBackendEnum | None:
"""
Get the backend override specified by the vLLM attention
backend environment variable, if one is specified.
Returns:
* AttentionBackendEnum value if an override is specified
* None otherwise
"""
backend_name = os.environ.get(STR_BACKEND_ENV_VAR)
return None if backend_name is None else AttentionBackendEnum[backend_name]
# Global state allows a particular choice of backend
# to be forced, overriding the logic which auto-selects
# a backend based on system & workload configuration
# (default behavior if this variable is None)
#
# THIS SELECTION TAKES PRECEDENCE OVER THE
# VLLM_ATTENTION_BACKEND ENVIRONMENT VARIABLE
forced_attn_backend: AttentionBackendEnum | None = None
def global_force_attn_backend(attn_backend: AttentionBackendEnum | None) -> None:
"""
Force all attention operations to use a specified backend.
Passing `None` for the argument re-enables automatic
backend selection.,
Arguments:
* attn_backend: backend selection (None to revert to auto)
"""
global forced_attn_backend
forced_attn_backend = attn_backend
def get_global_forced_attn_backend() -> AttentionBackendEnum | None:
"""
Get the currently-forced choice of attention backend,
or None if auto-selection is currently enabled.
"""
return forced_attn_backend
def get_attn_backend(
head_size: int,
dtype: torch.dtype,
kv_cache_dtype: str | None,
block_size: int | None,
use_mla: bool = False,
has_sink: bool = False,
use_sparse: bool = False,
attn_type: str | None = None,
) -> type[AttentionBackend]:
"""Selects which attention backend to use and lazily imports it."""
if kv_cache_dtype is not None:
valid_cache_dtypes = get_args(CacheDType)
assert kv_cache_dtype in valid_cache_dtypes, (
f"Invalid kv_cache_dtype: {kv_cache_dtype}. "
f"Valid values are: {valid_cache_dtypes}"
)
return _cached_get_attn_backend(
head_size=head_size,
dtype=dtype,
kv_cache_dtype=cast(CacheDType | None, kv_cache_dtype),
block_size=block_size,
use_mla=use_mla,
has_sink=has_sink,
use_sparse=use_sparse,
attn_type=attn_type,
)
@cache
def _cached_get_attn_backend(
head_size: int,
dtype: torch.dtype,
kv_cache_dtype: CacheDType | None,
block_size: int | None,
use_mla: bool = False,
has_sink: bool = False,
use_sparse: bool = False,
attn_type: str | None = None,
) -> type[AttentionBackend]:
# Check whether a particular choice of backend was
# previously forced.
#
# THIS SELECTION OVERRIDES THE VLLM_ATTENTION_BACKEND
# ENVIRONMENT VARIABLE.
selected_backend = None
backend_by_global_setting: AttentionBackendEnum | None = (
get_global_forced_attn_backend()
)
if backend_by_global_setting is not None:
selected_backend = backend_by_global_setting
else:
# Check the environment variable and override if specified
backend_by_env_var: str | None = envs.VLLM_ATTENTION_BACKEND
if backend_by_env_var is not None:
if backend_by_env_var.endswith("_VLLM_V1"):
logger.warning(
"The suffix '_VLLM_V1' in the environment variable "
"%s is no longer necessary as V0 backends have been "
"deprecated. Please remove this suffix from your "
"environment variable setting.",
STR_BACKEND_ENV_VAR,
)
backend_by_env_var = backend_by_env_var.removesuffix("_VLLM_V1")
try:
selected_backend = AttentionBackendEnum[backend_by_env_var]
except KeyError as e:
raise ValueError(
f"Invalid attention backend: '{backend_by_env_var}'. Valid "
f"backends are: {list(AttentionBackendEnum.__members__.keys())}"
) from e
# get device-specific attn_backend
from vllm.platforms import current_platform
sig = inspect.signature(current_platform.get_attn_backend_cls)
if "use_v1" in sig.parameters:
logger.warning_once(
"use_v1 parameter for get_attn_backend_cls is deprecated and will "
"be removed in v0.13.0 or v1.0.0, whichever is soonest. Please "
"remove it from your plugin code."
)
attention_cls = current_platform.get_attn_backend_cls(
selected_backend,
head_size,
dtype,
kv_cache_dtype,
block_size,
True, # use_v1
use_mla,
has_sink,
use_sparse,
attn_type,
)
else:
attention_cls = current_platform.get_attn_backend_cls(
selected_backend,
head_size,
dtype,
kv_cache_dtype,
block_size,
use_mla,
has_sink,
use_sparse,
attn_type,
)
if not attention_cls:
raise ValueError(
f"Invalid attention backend for {current_platform.device_name}"
)
backend = resolve_obj_by_qualname(attention_cls)
# Adjust kv cache layout if the selected backend requires a specific one
required_layout = backend.get_required_kv_cache_layout()
if required_layout is not None:
from vllm.v1.attention.backends.utils import set_kv_cache_layout
set_kv_cache_layout(required_layout)
logger.info(
"Using %s KV cache layout for %s backend.",
required_layout,
backend.get_name(),
)
return backend
def get_mamba_attn_backend(
mamba_type: str,
) -> type[AttentionBackend]:
"""Select which mamba attention backend to use and lazily import it."""
return _cached_get_mamba_attn_backend(mamba_type)
@cache
def _cached_get_mamba_attn_backend(
mamba_type: str,
) -> type[AttentionBackend]:
assert mamba_type and isinstance(mamba_type, str)
selected_backend = None
try:
backend_name = MAMBA_TYPE_TO_BACKEND_MAP[mamba_type]
selected_backend = MambaAttentionBackendEnum[backend_name]
except KeyError as e:
raise ValueError(
f"Invalid mamba attention backend type: '{backend_name}'. Valid "
f"backends are: {list(MambaAttentionBackendEnum.__members__.keys())}"
) from e
mamba_attn_backend = selected_backend.get_class()
return mamba_attn_backend
@contextmanager
def global_force_attn_backend_context_manager(
attn_backend: AttentionBackendEnum,
) -> Generator[None, None, None]:
"""
Globally force a vLLM attention backend override within a
context manager, reverting the global attention backend
override to its prior state upon exiting the context
manager.
Arguments:
* attn_backend: attention backend to force
Returns:
* Generator
"""
# Save the current state of the global backend override (if any)
original_value = get_global_forced_attn_backend()
# Globally force the new backend override
global_force_attn_backend(attn_backend)
# Yield control back to the enclosed code block
try:
yield
finally:
# Revert the original global backend override, if any
global_force_attn_backend(original_value)
_cached_get_attn_backend.cache_clear()