342 lines
10 KiB
Python
342 lines
10 KiB
Python
from __future__ import annotations
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import dataclasses
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import time
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from abc import ABC, abstractmethod
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from typing import (
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TYPE_CHECKING,
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Any,
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NamedTuple,
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Optional,
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Protocol,
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Tuple,
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runtime_checkable,
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)
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import torch
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from sglang.srt.mem_cache.allocator import BaseTokenToKVPoolAllocator
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from sglang.srt.mem_cache.memory_pool import ReqToTokenPool
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from sglang.srt.observability.metrics_collector import RadixCacheMetricsCollector
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if TYPE_CHECKING:
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from sglang.srt.managers.schedule_batch import Req
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from sglang.srt.mem_cache.radix_cache import RadixKey
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from sglang.srt.mem_cache.unified_cache_components.tree_component import (
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ComponentType,
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)
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@runtime_checkable
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class PrefixCacheTrait(Protocol):
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req_to_token_pool: ReqToTokenPool
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token_to_kv_pool_allocator: BaseTokenToKVPoolAllocator
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page_size: int
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disable: bool
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@dataclasses.dataclass
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class MatchPrefixParams:
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"""Unified parameters for match_prefix across different cache types"""
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key: RadixKey
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# Mamba specific
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cow_mamba: bool = False
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req: Optional[Req] = None
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@dataclasses.dataclass
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class InsertParams:
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"""Unified parameters for insert across different cache types"""
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key: Optional[RadixKey] = None
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value: Optional[torch.Tensor] = None
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# Mamba specific
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mamba_value: Optional[torch.Tensor] = None
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# SWA specific
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prev_prefix_len: int = 0
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swa_evicted_seqlen: int = 0
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# General
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chunked: bool = False
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priority: int = 0
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@dataclasses.dataclass
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class InsertResult:
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"""Result of an insert operation"""
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prefix_len: int
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mamba_exist: bool = False
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@dataclasses.dataclass
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class EvictParams:
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"""Unified parameters for evict across different cache types"""
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num_tokens: int = 0
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swa_num_tokens: int = 0
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mamba_num: int = 0
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@dataclasses.dataclass
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class EvictResult:
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"""Result of an evict operation"""
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num_tokens_evicted: int = 0
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swa_num_tokens_evicted: int = 0
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mamba_num_evicted: int = 0
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@dataclasses.dataclass
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class IncLockRefResult:
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"""Result of an inc_lock_ref operation."""
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delta: Optional[int] = None
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swa_uuid_for_lock: Optional[int] = None
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# Component nodes that were tombstones at acquire time. Replaying this set
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# at release prevents a short-lived lock from consuming a later load-back or
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# request lock after that tombstone becomes a valid device value.
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skip_lock_node_ids: dict[ComponentType, set[int]] = dataclasses.field(
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default_factory=dict
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)
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def to_dec_params(self) -> "DecLockRefParams":
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"""Convert to the corresponding DecLockRefParams for dec_lock_ref."""
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return DecLockRefParams(
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swa_uuid_for_lock=self.swa_uuid_for_lock,
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skip_lock_node_ids={
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component_type: set(node_ids)
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for component_type, node_ids in self.skip_lock_node_ids.items()
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},
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)
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@dataclasses.dataclass
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class DecLockRefParams:
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"""Parameters for dec_lock_ref operation."""
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swa_uuid_for_lock: Optional[int] = None
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skip_lock_node_ids: dict[ComponentType, set[int]] = dataclasses.field(
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default_factory=dict
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)
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@dataclasses.dataclass
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class DecLockRefResult:
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"""Result of an dec_lock_ref operation."""
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delta: Optional[int] = None
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@dataclasses.dataclass
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class InitLoadBackParams:
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"""Unified parameters for init_load_back across different cache types."""
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best_match_node: Any
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host_hit_length: int
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mem_quota: Optional[int] = None
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req: Optional[Req] = None
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class MatchResult(NamedTuple):
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"""Result of a prefix match operation.
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Attributes:
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device_indices : Indices of the KV cache on the device matched by common prefix.
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last_device_node: The last TreeNode on the device that was matched.
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last_host_node : The last TreeNode on the host that was matched.
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Note that if HiCache is not enabled,
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this **must** be the same as `last_device_node`.
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Reserved for L3 storage prefetch anchoring; L2 load_back
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uses `best_match_node` instead.
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best_match_node : Deepest node accepted by all component validators
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during match_prefix. Anchor for every L2 host->device
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load_back walk (FULL / SWA / ...). For legacy caches
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that don't run multi-component validation, set this
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equal to `last_host_node`.
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host_hit_length : Length of the host cache hit. For pure-KV caches this is the
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number of evicted KV tokens on CPU. For hybrid Mamba models this
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is max(kv_host_tokens, 1-if-mamba-on-host) so that a mamba-only
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host hit still triggers load-back without adding a separate field.
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0 if HiCache is not enabled.
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mamba_branching_seqlen: The mamba radix cache branching point, which is the longest
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page-aligned position that could've been cache hit if there
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exists a mamba state.
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"""
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device_indices: torch.Tensor
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last_device_node: Any
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last_host_node: Any
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best_match_node: Any
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host_hit_length: int = 0
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mamba_branching_seqlen: Optional[int] = None
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cache_protected_len: Optional[int] = None
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def zero_match_result(tree_cache, match_result: "MatchResult") -> "MatchResult":
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if tree_cache.is_chunk_cache():
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# Chunk caches' match_prefix already returns a miss; no root_node to walk back to.
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return match_result
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root = tree_cache.root_node
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return match_result._replace(
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# [:0] keeps dtype and device of the original tensor (e.g. CUDA int64)
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# without allocating a fresh empty tensor.
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device_indices=match_result.device_indices[:0],
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last_device_node=root,
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last_host_node=root,
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best_match_node=root,
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host_hit_length=0,
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)
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class BasePrefixCache(ABC, PrefixCacheTrait):
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"""Cache can be indexed by either rid or key."""
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metrics_collector: Optional[RadixCacheMetricsCollector] = (
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None # metrics collector for the cache
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)
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def init_metrics_collector(self):
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from sglang.srt.server_args import get_global_server_args
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server_args = get_global_server_args()
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labels = {"cache_type": self.__class__.__name__}
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if server_args.extra_metric_labels:
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labels.update(server_args.extra_metric_labels)
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self.metrics_collector = RadixCacheMetricsCollector(labels=labels)
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def update_eviction_metrics(self, num_evicted: int, start_time: float):
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if self.metrics_collector is not None and num_evicted > 0:
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self.metrics_collector.observe_eviction_duration(
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time.perf_counter() - start_time
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)
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self.metrics_collector.increment_eviction_num_tokens(num_evicted)
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@abstractmethod
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def reset(self):
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pass
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@abstractmethod
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def match_prefix(self, params: MatchPrefixParams) -> MatchResult:
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pass
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@abstractmethod
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def cache_finished_req(self, req: Req, is_insert: bool = True, **kwargs):
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pass
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@abstractmethod
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def cache_unfinished_req(self, req: Req, **kwargs):
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pass
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@abstractmethod
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def evict(self, params: EvictParams) -> EvictResult:
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pass
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@abstractmethod
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def inc_lock_ref(self, node: Any) -> IncLockRefResult:
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pass
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@abstractmethod
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def dec_lock_ref(
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self, node: Any, params: Optional[DecLockRefParams] = None
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) -> DecLockRefResult:
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pass
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def evictable_size(self):
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return 0
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def full_evictable_size(self):
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return 0
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def swa_evictable_size(self):
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return 0
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def protected_size(self):
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return 0
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def full_protected_size(self):
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return 0
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def swa_protected_size(self):
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return 0
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def total_size(self):
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raise NotImplementedError()
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def pretty_print(self):
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raise NotImplementedError()
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def init_load_back(
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self,
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params: InitLoadBackParams,
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) -> Tuple[torch.Tensor, Any]:
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"""
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Preparing KV cache loading from host to device.
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"""
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raise NotImplementedError()
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def ready_to_load_host_cache(self) -> Any:
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"""
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Notify the cache controller to start the KV cache loading
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"""
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raise NotImplementedError()
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def flush_write_through_acks(self) -> None:
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"""Release lock_ref on radix-tree nodes whose write-through has completed.
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Lightweight operation that only processes finished write acks.
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No-op for caches without hierarchical write-through support.
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"""
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pass
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def check_hicache_events(self) -> Any:
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"""
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Check HiCache related activities to update radix tree and synchronize across TP workers if needed
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"""
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raise NotImplementedError()
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def take_events(self):
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return []
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def supports_swa(self) -> bool:
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return False
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def supports_mamba(self) -> bool:
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return False
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def supports_streaming_session(self) -> bool:
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return False
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def release_session(self, session_id: str) -> None:
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pass
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def session_held_tokens(self, active_pool_idxs: Optional[set] = None) -> int:
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return 0
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def session_held_full_tokens(self, active_pool_idxs: Optional[set] = None) -> int:
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return 0
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def session_held_swa_tokens(self, active_pool_idxs: Optional[set] = None) -> int:
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return 0
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def session_held_req_count(self, active_pool_idxs: Optional[set] = None) -> int:
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return 0
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def session_held_mamba_slots(self, active_pool_idxs: Optional[set] = None) -> int:
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return 0
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def is_chunk_cache(self) -> bool:
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return False
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def is_tree_cache(self) -> bool:
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return not self.is_chunk_cache()
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def available_and_evictable_str(self) -> str:
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available_size = self.token_to_kv_pool_allocator.available_size()
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evictable_size = self.evictable_size()
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return f"Available tokens: {available_size + evictable_size} ({available_size=} + {evictable_size=})\n"
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