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chore: import upstream snapshot with attribution
2026-07-13 12:32:31 +08:00

225 lines
9.0 KiB
Python

# Copyright (c) 2026 LightSeek Foundation
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
"""Vision-embedding cache for the EPD encode stage.
The encode server runs the vision tower only; a cache lets duplicate images
(same ``MultimodalDataItem.hash``) reuse a previously computed embedding instead
of re-running the tower.
Two interchangeable implementations share a ``get`` / ``put`` surface:
:class:`EmbeddingCache` (single-tier, bytes-bounded LRU) and
:class:`TieredEmbeddingCache` (L1 GPU VRAM + L2 host DRAM). Both are
framework-agnostic and unit-testable without a GPU -- the caller supplies byte
sizes and the device<->host copies are injectable.
"""
from __future__ import annotations
import collections
from collections.abc import Callable, Hashable
class EmbeddingCache:
"""Bytes-bounded LRU cache of vision-tower outputs, keyed by content hash.
Values are opaque (typically a ``torch.Tensor``); the caller supplies the
byte size so this stays framework-agnostic and testable without a GPU.
``on_evict`` is an optional ``(key, value, nbytes)`` callback fired only for
an entry dropped by capacity overflow (not an update to an existing key,
which is an in-place replace, nor an explicit :meth:`pop`). It lets a second
tier capture LRU victims and demote them (see :class:`TieredEmbeddingCache`).
"""
def __init__(
self,
capacity_bytes: int,
on_evict: Callable[[Hashable, object, int], None] | None = None,
):
if capacity_bytes < 0:
raise ValueError(f"capacity_bytes must be >= 0, got {capacity_bytes}")
self.capacity_bytes = capacity_bytes
self._on_evict = on_evict
# key -> (value, nbytes); ordered by recency (oldest first).
self._store: collections.OrderedDict[Hashable, tuple[object, int]] = (
collections.OrderedDict()
)
self._cur_bytes = 0
self.hits = 0
self.misses = 0
def get(self, key: Hashable) -> object | None:
entry = self._store.get(key)
if entry is None:
self.misses += 1
return None
self._store.move_to_end(key)
self.hits += 1
return entry[0]
def put(self, key: Hashable, value: object, nbytes: int) -> None:
if nbytes < 0:
raise ValueError(f"nbytes must be >= 0, got {nbytes}")
# An item larger than the whole cache can never be retained; skip it
# rather than evicting everything for a value dropped immediately after.
if nbytes > self.capacity_bytes:
return
existing = self._store.pop(key, None)
if existing is not None:
self._cur_bytes -= existing[1]
self._store[key] = (value, nbytes)
self._cur_bytes += nbytes
self._evict()
def pop(self, key: Hashable) -> tuple[object, int] | None:
"""Remove ``key`` and return its ``(value, nbytes)``, or ``None`` if
absent. A structural removal: it neither counts as a hit/miss nor fires
``on_evict`` (the caller is taking ownership of the value, e.g. to
promote it to another tier)."""
existing = self._store.pop(key, None)
if existing is None:
return None
self._cur_bytes -= existing[1]
return existing
def _evict(self) -> None:
while self._cur_bytes > self.capacity_bytes and self._store:
key, (value, nbytes) = self._store.popitem(last=False)
self._cur_bytes -= nbytes
if self._on_evict is not None:
self._on_evict(key, value, nbytes)
def __contains__(self, key: Hashable) -> bool:
return key in self._store
def __len__(self) -> int:
return len(self._store)
@property
def current_bytes(self) -> int:
return self._cur_bytes
def _embedding_to_host(value: object) -> object:
"""Default L1->L2 demote: copy a vision embedding from GPU to host memory.
A cache value is a ``(main, deepstack)`` tuple (deepstack half may be
``None`` for non-deepstack models) or a bare tensor.
"""
if isinstance(value, tuple):
return tuple(None if t is None else t.cpu() for t in value)
return value.cpu()
def _embedding_to_device(value: object, device) -> object:
"""Default L2->L1 promote: copy a host-resident embedding back to ``device``
so the executor can stage it into the GPU send ring."""
if isinstance(value, tuple):
return tuple(None if t is None else t.to(device) for t in value)
return value.to(device)
class TieredEmbeddingCache:
"""Two-tier vision-embedding cache: L1 in GPU VRAM, L2 in host DRAM.
Exposes the same ``get`` / ``put`` surface as :class:`EmbeddingCache`, so the
encode worker uses either interchangeably. L2 catches L1's LRU victims in
cheaper host DRAM: a hit there skips the (much more expensive) ViT and only
pays a host->device copy.
Tiers are kept *exclusive* -- a key lives in exactly one. An L1 eviction
demotes the victim to L2 (device->host copy); an L2 hit promotes the entry
back to L1 (host->device copy) and removes it from L2; ``put`` always lands
in L1 and drops any stale L2 duplicate. No distributed L3: image-hash routing
pins each image to one worker, so a per-worker local cache captures the reuse.
The device<->host copies are injectable (``to_host`` / ``to_device``) so the
tiering logic is unit-testable without a GPU; the defaults copy real tensors
to/from ``device``.
"""
def __init__(
self,
l1_capacity_bytes: int,
l2_capacity_bytes: int,
*,
device: object = None,
to_host: Callable[[object], object] | None = None,
to_device: Callable[[object], object] | None = None,
):
# L1 demotes its evictions into L2 via the on_evict hook; L2 is the
# bottom tier (no hook), so its evictions are true drops -- no recursion.
self.l1 = EmbeddingCache(l1_capacity_bytes, on_evict=self._demote)
self.l2 = EmbeddingCache(l2_capacity_bytes)
self._device = device
self._to_host = to_host or _embedding_to_host
self._to_device = to_device or (lambda v: _embedding_to_device(v, self._device))
self.l1_hits = 0
self.l2_hits = 0
self.misses = 0
self.promotions = 0
self.demotions = 0
def get(self, key: Hashable) -> object | None:
value = self.l1.get(key)
if value is not None:
self.l1_hits += 1
return value
promoted = self.l2.pop(key)
if promoted is None:
self.misses += 1
return None
host_value, nbytes = promoted
device_value = self._to_device(host_value)
self.l2_hits += 1
self.promotions += 1
# Re-home as MRU in L1. May evict colder L1 entries, which demote to L2;
# the just-promoted key is MRU so it is never the victim.
self.l1.put(key, device_value, nbytes)
return device_value
def put(self, key: Hashable, value: object, nbytes: int) -> None:
# L1 is the write tier. Drop any stale L2 copy first so the tiers stay
# exclusive (e.g. a key demoted earlier and now re-encoded on a miss).
self.l2.pop(key)
self.l1.put(key, value, nbytes)
def _demote(self, key: Hashable, value: object, nbytes: int) -> None:
"""L1 eviction hook: stash the victim in host DRAM instead of dropping
it. host nbytes == device nbytes (same dtype/numel). A victim larger than
all of L2 is silently dropped by ``L2.put`` (same as having no L2)."""
# Skip the wasted device->host copy for a victim L2 would just drop.
if nbytes > self.l2.capacity_bytes:
return
self.l2.put(key, self._to_host(value), nbytes)
if key in self.l2:
self.demotions += 1
@property
def hits(self) -> int:
return self.l1_hits + self.l2_hits
def __contains__(self, key: Hashable) -> bool:
return key in self.l1 or key in self.l2
def __len__(self) -> int:
return len(self.l1) + len(self.l2)