rattus128 b1467da480
execution: fold in dependency aware caching / Fix --cache-none with loops/lazy etc (#10368)
* execution: fold in dependency aware caching

This makes --cache-none compatiable with lazy and expanded
subgraphs.

Currently the --cache-none option is powered by the
DependencyAwareCache. The cache attempts to maintain a parallel
copy of the execution list data structure, however it is only
setup once at the start of execution and does not get meaninigful
updates to the execution list.

This causes multiple problems when --cache-none is used with lazy
and expanded subgraphs as the DAC does not accurately update its
copy of the execution data structure.

DAC has an attempt to handle subgraphs ensure_subcache however
this does not accurately connect to nodes outside the subgraph.
The current semantics of DAC are to free a node ASAP after the
dependent nodes are executed.

This means that if a subgraph refs such a node it will be requed
and re-executed by the execution_list but DAC wont see it in
its to-free lists anymore and leak memory.

Rather than try and cover all the cases where the execution list
changes from inside the cache, move the while problem to the
executor which maintains an always up-to-date copy of the wanted
data-structure.

The executor now has a fast-moving run-local cache of its own.
Each _to node has its own mini cache, and the cache is unconditionally
primed at the time of add_strong_link.

add_strong_link is called for all of static workflows, lazy links
and expanded subgraphs so its the singular source of truth for
output dependendencies.

In the case of a cache-hit, the executor cache will hold the non-none
value (it will respect updates if they happen somehow as well).

In the case of a cache-miss, the executor caches a None and will
wait for a notification to update the value when the node completes.

When a node completes execution, it simply releases its mini-cache
and in turn its strong refs on its direct anscestor outputs, allowing
for ASAP freeing (same as the DependencyAwareCache but a little more
automatic).

This now allows for re-implementation of --cache-none with no cache
at all. The dependency aware cache was also observing the dependency
sematics for the objects and UI cache which is not accurate (this
entire logic was always outputs specific).

This also prepares for more complex caching strategies (such as RAM
pressure based caching), where a cache can implement any freeing
strategy completely independently of the DepedancyAwareness
requirement.

* main: re-implement --cache-none as no cache at all

The execution list now tracks the dependency aware caching more
correctly that the DependancyAwareCache.

Change it to a cache that does nothing.

* test_execution: add --cache-none to the test suite

--cache-none is now expected to work universally. Run it through the
full unit test suite. Propagate the server parameterization for whether
or not the server is capabale of caching, so that the minority of tests
that specifically check for cache hits can if else. Hard assert NOT
caching in the else to give some coverage of --cache-none expected
behaviour to not acutally cache.
2025-10-17 13:55:15 -07:00

339 lines
12 KiB
Python

import itertools
from typing import Sequence, Mapping, Dict
from comfy_execution.graph import DynamicPrompt
from abc import ABC, abstractmethod
import nodes
from comfy_execution.graph_utils import is_link
NODE_CLASS_CONTAINS_UNIQUE_ID: Dict[str, bool] = {}
def include_unique_id_in_input(class_type: str) -> bool:
if class_type in NODE_CLASS_CONTAINS_UNIQUE_ID:
return NODE_CLASS_CONTAINS_UNIQUE_ID[class_type]
class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
NODE_CLASS_CONTAINS_UNIQUE_ID[class_type] = "UNIQUE_ID" in class_def.INPUT_TYPES().get("hidden", {}).values()
return NODE_CLASS_CONTAINS_UNIQUE_ID[class_type]
class CacheKeySet(ABC):
def __init__(self, dynprompt, node_ids, is_changed_cache):
self.keys = {}
self.subcache_keys = {}
@abstractmethod
async def add_keys(self, node_ids):
raise NotImplementedError()
def all_node_ids(self):
return set(self.keys.keys())
def get_used_keys(self):
return self.keys.values()
def get_used_subcache_keys(self):
return self.subcache_keys.values()
def get_data_key(self, node_id):
return self.keys.get(node_id, None)
def get_subcache_key(self, node_id):
return self.subcache_keys.get(node_id, None)
class Unhashable:
def __init__(self):
self.value = float("NaN")
def to_hashable(obj):
# So that we don't infinitely recurse since frozenset and tuples
# are Sequences.
if isinstance(obj, (int, float, str, bool, type(None))):
return obj
elif isinstance(obj, Mapping):
return frozenset([(to_hashable(k), to_hashable(v)) for k, v in sorted(obj.items())])
elif isinstance(obj, Sequence):
return frozenset(zip(itertools.count(), [to_hashable(i) for i in obj]))
else:
# TODO - Support other objects like tensors?
return Unhashable()
class CacheKeySetID(CacheKeySet):
def __init__(self, dynprompt, node_ids, is_changed_cache):
super().__init__(dynprompt, node_ids, is_changed_cache)
self.dynprompt = dynprompt
async def add_keys(self, node_ids):
for node_id in node_ids:
if node_id in self.keys:
continue
if not self.dynprompt.has_node(node_id):
continue
node = self.dynprompt.get_node(node_id)
self.keys[node_id] = (node_id, node["class_type"])
self.subcache_keys[node_id] = (node_id, node["class_type"])
class CacheKeySetInputSignature(CacheKeySet):
def __init__(self, dynprompt, node_ids, is_changed_cache):
super().__init__(dynprompt, node_ids, is_changed_cache)
self.dynprompt = dynprompt
self.is_changed_cache = is_changed_cache
def include_node_id_in_input(self) -> bool:
return False
async def add_keys(self, node_ids):
for node_id in node_ids:
if node_id in self.keys:
continue
if not self.dynprompt.has_node(node_id):
continue
node = self.dynprompt.get_node(node_id)
self.keys[node_id] = await self.get_node_signature(self.dynprompt, node_id)
self.subcache_keys[node_id] = (node_id, node["class_type"])
async def get_node_signature(self, dynprompt, node_id):
signature = []
ancestors, order_mapping = self.get_ordered_ancestry(dynprompt, node_id)
signature.append(await self.get_immediate_node_signature(dynprompt, node_id, order_mapping))
for ancestor_id in ancestors:
signature.append(await self.get_immediate_node_signature(dynprompt, ancestor_id, order_mapping))
return to_hashable(signature)
async def get_immediate_node_signature(self, dynprompt, node_id, ancestor_order_mapping):
if not dynprompt.has_node(node_id):
# This node doesn't exist -- we can't cache it.
return [float("NaN")]
node = dynprompt.get_node(node_id)
class_type = node["class_type"]
class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
signature = [class_type, await self.is_changed_cache.get(node_id)]
if self.include_node_id_in_input() or (hasattr(class_def, "NOT_IDEMPOTENT") and class_def.NOT_IDEMPOTENT) or include_unique_id_in_input(class_type):
signature.append(node_id)
inputs = node["inputs"]
for key in sorted(inputs.keys()):
if is_link(inputs[key]):
(ancestor_id, ancestor_socket) = inputs[key]
ancestor_index = ancestor_order_mapping[ancestor_id]
signature.append((key,("ANCESTOR", ancestor_index, ancestor_socket)))
else:
signature.append((key, inputs[key]))
return signature
# This function returns a list of all ancestors of the given node. The order of the list is
# deterministic based on which specific inputs the ancestor is connected by.
def get_ordered_ancestry(self, dynprompt, node_id):
ancestors = []
order_mapping = {}
self.get_ordered_ancestry_internal(dynprompt, node_id, ancestors, order_mapping)
return ancestors, order_mapping
def get_ordered_ancestry_internal(self, dynprompt, node_id, ancestors, order_mapping):
if not dynprompt.has_node(node_id):
return
inputs = dynprompt.get_node(node_id)["inputs"]
input_keys = sorted(inputs.keys())
for key in input_keys:
if is_link(inputs[key]):
ancestor_id = inputs[key][0]
if ancestor_id not in order_mapping:
ancestors.append(ancestor_id)
order_mapping[ancestor_id] = len(ancestors) - 1
self.get_ordered_ancestry_internal(dynprompt, ancestor_id, ancestors, order_mapping)
class BasicCache:
def __init__(self, key_class):
self.key_class = key_class
self.initialized = False
self.dynprompt: DynamicPrompt
self.cache_key_set: CacheKeySet
self.cache = {}
self.subcaches = {}
async def set_prompt(self, dynprompt, node_ids, is_changed_cache):
self.dynprompt = dynprompt
self.cache_key_set = self.key_class(dynprompt, node_ids, is_changed_cache)
await self.cache_key_set.add_keys(node_ids)
self.is_changed_cache = is_changed_cache
self.initialized = True
def all_node_ids(self):
assert self.initialized
node_ids = self.cache_key_set.all_node_ids()
for subcache in self.subcaches.values():
node_ids = node_ids.union(subcache.all_node_ids())
return node_ids
def _clean_cache(self):
preserve_keys = set(self.cache_key_set.get_used_keys())
to_remove = []
for key in self.cache:
if key not in preserve_keys:
to_remove.append(key)
for key in to_remove:
del self.cache[key]
def _clean_subcaches(self):
preserve_subcaches = set(self.cache_key_set.get_used_subcache_keys())
to_remove = []
for key in self.subcaches:
if key not in preserve_subcaches:
to_remove.append(key)
for key in to_remove:
del self.subcaches[key]
def clean_unused(self):
assert self.initialized
self._clean_cache()
self._clean_subcaches()
def _set_immediate(self, node_id, value):
assert self.initialized
cache_key = self.cache_key_set.get_data_key(node_id)
self.cache[cache_key] = value
def _get_immediate(self, node_id):
if not self.initialized:
return None
cache_key = self.cache_key_set.get_data_key(node_id)
if cache_key in self.cache:
return self.cache[cache_key]
else:
return None
async def _ensure_subcache(self, node_id, children_ids):
subcache_key = self.cache_key_set.get_subcache_key(node_id)
subcache = self.subcaches.get(subcache_key, None)
if subcache is None:
subcache = BasicCache(self.key_class)
self.subcaches[subcache_key] = subcache
await subcache.set_prompt(self.dynprompt, children_ids, self.is_changed_cache)
return subcache
def _get_subcache(self, node_id):
assert self.initialized
subcache_key = self.cache_key_set.get_subcache_key(node_id)
if subcache_key in self.subcaches:
return self.subcaches[subcache_key]
else:
return None
def recursive_debug_dump(self):
result = []
for key in self.cache:
result.append({"key": key, "value": self.cache[key]})
for key in self.subcaches:
result.append({"subcache_key": key, "subcache": self.subcaches[key].recursive_debug_dump()})
return result
class HierarchicalCache(BasicCache):
def __init__(self, key_class):
super().__init__(key_class)
def _get_cache_for(self, node_id):
assert self.dynprompt is not None
parent_id = self.dynprompt.get_parent_node_id(node_id)
if parent_id is None:
return self
hierarchy = []
while parent_id is not None:
hierarchy.append(parent_id)
parent_id = self.dynprompt.get_parent_node_id(parent_id)
cache = self
for parent_id in reversed(hierarchy):
cache = cache._get_subcache(parent_id)
if cache is None:
return None
return cache
def get(self, node_id):
cache = self._get_cache_for(node_id)
if cache is None:
return None
return cache._get_immediate(node_id)
def set(self, node_id, value):
cache = self._get_cache_for(node_id)
assert cache is not None
cache._set_immediate(node_id, value)
async def ensure_subcache_for(self, node_id, children_ids):
cache = self._get_cache_for(node_id)
assert cache is not None
return await cache._ensure_subcache(node_id, children_ids)
class NullCache:
async def set_prompt(self, dynprompt, node_ids, is_changed_cache):
pass
def all_node_ids(self):
return []
def clean_unused(self):
pass
def get(self, node_id):
return None
def set(self, node_id, value):
pass
async def ensure_subcache_for(self, node_id, children_ids):
return self
class LRUCache(BasicCache):
def __init__(self, key_class, max_size=100):
super().__init__(key_class)
self.max_size = max_size
self.min_generation = 0
self.generation = 0
self.used_generation = {}
self.children = {}
async def set_prompt(self, dynprompt, node_ids, is_changed_cache):
await super().set_prompt(dynprompt, node_ids, is_changed_cache)
self.generation += 1
for node_id in node_ids:
self._mark_used(node_id)
def clean_unused(self):
while len(self.cache) > self.max_size and self.min_generation < self.generation:
self.min_generation += 1
to_remove = [key for key in self.cache if self.used_generation[key] < self.min_generation]
for key in to_remove:
del self.cache[key]
del self.used_generation[key]
if key in self.children:
del self.children[key]
self._clean_subcaches()
def get(self, node_id):
self._mark_used(node_id)
return self._get_immediate(node_id)
def _mark_used(self, node_id):
cache_key = self.cache_key_set.get_data_key(node_id)
if cache_key is not None:
self.used_generation[cache_key] = self.generation
def set(self, node_id, value):
self._mark_used(node_id)
return self._set_immediate(node_id, value)
async def ensure_subcache_for(self, node_id, children_ids):
# Just uses subcaches for tracking 'live' nodes
await super()._ensure_subcache(node_id, children_ids)
await self.cache_key_set.add_keys(children_ids)
self._mark_used(node_id)
cache_key = self.cache_key_set.get_data_key(node_id)
self.children[cache_key] = []
for child_id in children_ids:
self._mark_used(child_id)
self.children[cache_key].append(self.cache_key_set.get_data_key(child_id))
return self