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1
.github/workflows/stable-release.yml
vendored
1
.github/workflows/stable-release.yml
vendored
@ -1,4 +1,3 @@
|
||||
|
||||
name: "Release Stable Version"
|
||||
|
||||
on:
|
||||
|
2
.github/workflows/test-unit.yml
vendored
2
.github/workflows/test-unit.yml
vendored
@ -15,7 +15,7 @@ jobs:
|
||||
continue-on-error: true
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: '3.12'
|
||||
|
@ -36,7 +36,7 @@ ComfyUI lets you design and execute advanced stable diffusion pipelines using a
|
||||
## Get Started
|
||||
|
||||
#### [Desktop Application](https://www.comfy.org/download)
|
||||
- The easiest way to get started.
|
||||
- The easiest way to get started.
|
||||
- Available on Windows & macOS.
|
||||
|
||||
#### [Windows Portable Package](#installing)
|
||||
@ -190,7 +190,7 @@ This is the command to install the nightly with ROCm 6.3 which might have some p
|
||||
### Intel GPUs (Windows and Linux)
|
||||
|
||||
(Option 1) Intel Arc GPU users can install native PyTorch with torch.xpu support using pip (currently available in PyTorch nightly builds). More information can be found [here](https://pytorch.org/docs/main/notes/get_start_xpu.html)
|
||||
|
||||
|
||||
1. To install PyTorch nightly, use the following command:
|
||||
|
||||
```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/xpu```
|
||||
@ -321,7 +321,7 @@ Generate a self-signed certificate (not appropriate for shared/production use) a
|
||||
|
||||
Use `--tls-keyfile key.pem --tls-certfile cert.pem` to enable TLS/SSL, the app will now be accessible with `https://...` instead of `http://...`.
|
||||
|
||||
> Note: Windows users can use [alexisrolland/docker-openssl](https://github.com/alexisrolland/docker-openssl) or one of the [3rd party binary distributions](https://wiki.openssl.org/index.php/Binaries) to run the command example above.
|
||||
> Note: Windows users can use [alexisrolland/docker-openssl](https://github.com/alexisrolland/docker-openssl) or one of the [3rd party binary distributions](https://wiki.openssl.org/index.php/Binaries) to run the command example above.
|
||||
<br/><br/>If you use a container, note that the volume mount `-v` can be a relative path so `... -v ".\:/openssl-certs" ...` would create the key & cert files in the current directory of your command prompt or powershell terminal.
|
||||
|
||||
## Support and dev channel
|
||||
|
@ -101,6 +101,7 @@ parser.add_argument("--preview-size", type=int, default=512, help="Sets the maxi
|
||||
cache_group = parser.add_mutually_exclusive_group()
|
||||
cache_group.add_argument("--cache-classic", action="store_true", help="Use the old style (aggressive) caching.")
|
||||
cache_group.add_argument("--cache-lru", type=int, default=0, help="Use LRU caching with a maximum of N node results cached. May use more RAM/VRAM.")
|
||||
cache_group.add_argument("--cache-none", action="store_true", help="Reduced RAM/VRAM usage at the expense of executing every node for each run.")
|
||||
|
||||
attn_group = parser.add_mutually_exclusive_group()
|
||||
attn_group.add_argument("--use-split-cross-attention", action="store_true", help="Use the split cross attention optimization. Ignored when xformers is used.")
|
||||
|
@ -587,7 +587,7 @@ def get_sorted_list_via_attr(objects: list, attr: str) -> list:
|
||||
sorted_list.extend(object_list)
|
||||
return sorted_list
|
||||
|
||||
def create_transformer_options_from_hooks(model: ModelPatcher, hooks: HookGroup, transformer_options: dict[str]=None):
|
||||
def create_transformer_options_from_hooks(model: ModelPatcher, hooks: HookGroup, transformer_options: dict[str]=None):
|
||||
# if no hooks or is not a ModelPatcher for sampling, return empty dict
|
||||
if hooks is None or model.is_clip:
|
||||
return {}
|
||||
|
@ -618,10 +618,10 @@ class PixArtAlpha(supported_models_base.BASE):
|
||||
}
|
||||
|
||||
sampling_settings = {
|
||||
"beta_schedule" : "sqrt_linear",
|
||||
"linear_start" : 0.0001,
|
||||
"linear_end" : 0.02,
|
||||
"timesteps" : 1000,
|
||||
"beta_schedule": "sqrt_linear",
|
||||
"linear_start": 0.0001,
|
||||
"linear_end": 0.02,
|
||||
"timesteps": 1000,
|
||||
}
|
||||
|
||||
unet_extra_config = {}
|
||||
@ -681,8 +681,8 @@ class HunyuanDiT1(HunyuanDiT):
|
||||
unet_extra_config = {}
|
||||
|
||||
sampling_settings = {
|
||||
"linear_start" : 0.00085,
|
||||
"linear_end" : 0.03,
|
||||
"linear_start": 0.00085,
|
||||
"linear_end": 0.03,
|
||||
}
|
||||
|
||||
class Flux(supported_models_base.BASE):
|
||||
|
@ -449,8 +449,8 @@ PIXART_MAP_BLOCK = {
|
||||
("mlp.fc1.bias", "ff.net.0.proj.bias"),
|
||||
("mlp.fc2.weight", "ff.net.2.weight"),
|
||||
("mlp.fc2.bias", "ff.net.2.bias"),
|
||||
("cross_attn.proj.weight" ,"attn2.to_out.0.weight"),
|
||||
("cross_attn.proj.bias" ,"attn2.to_out.0.bias"),
|
||||
("cross_attn.proj.weight", "attn2.to_out.0.weight"),
|
||||
("cross_attn.proj.bias", "attn2.to_out.0.bias"),
|
||||
}
|
||||
|
||||
def pixart_to_diffusers(mmdit_config, output_prefix=""):
|
||||
|
@ -316,3 +316,156 @@ class LRUCache(BasicCache):
|
||||
self.children[cache_key].append(self.cache_key_set.get_data_key(child_id))
|
||||
return self
|
||||
|
||||
|
||||
class DependencyAwareCache(BasicCache):
|
||||
"""
|
||||
A cache implementation that tracks dependencies between nodes and manages
|
||||
their execution and caching accordingly. It extends the BasicCache class.
|
||||
Nodes are removed from this cache once all of their descendants have been
|
||||
executed.
|
||||
"""
|
||||
|
||||
def __init__(self, key_class):
|
||||
"""
|
||||
Initialize the DependencyAwareCache.
|
||||
|
||||
Args:
|
||||
key_class: The class used for generating cache keys.
|
||||
"""
|
||||
super().__init__(key_class)
|
||||
self.descendants = {} # Maps node_id -> set of descendant node_ids
|
||||
self.ancestors = {} # Maps node_id -> set of ancestor node_ids
|
||||
self.executed_nodes = set() # Tracks nodes that have been executed
|
||||
|
||||
def set_prompt(self, dynprompt, node_ids, is_changed_cache):
|
||||
"""
|
||||
Clear the entire cache and rebuild the dependency graph.
|
||||
|
||||
Args:
|
||||
dynprompt: The dynamic prompt object containing node information.
|
||||
node_ids: List of node IDs to initialize the cache for.
|
||||
is_changed_cache: Flag indicating if the cache has changed.
|
||||
"""
|
||||
# Clear all existing cache data
|
||||
self.cache.clear()
|
||||
self.subcaches.clear()
|
||||
self.descendants.clear()
|
||||
self.ancestors.clear()
|
||||
self.executed_nodes.clear()
|
||||
|
||||
# Call the parent method to initialize the cache with the new prompt
|
||||
super().set_prompt(dynprompt, node_ids, is_changed_cache)
|
||||
|
||||
# Rebuild the dependency graph
|
||||
self._build_dependency_graph(dynprompt, node_ids)
|
||||
|
||||
def _build_dependency_graph(self, dynprompt, node_ids):
|
||||
"""
|
||||
Build the dependency graph for all nodes.
|
||||
|
||||
Args:
|
||||
dynprompt: The dynamic prompt object containing node information.
|
||||
node_ids: List of node IDs to build the graph for.
|
||||
"""
|
||||
self.descendants.clear()
|
||||
self.ancestors.clear()
|
||||
for node_id in node_ids:
|
||||
self.descendants[node_id] = set()
|
||||
self.ancestors[node_id] = set()
|
||||
|
||||
for node_id in node_ids:
|
||||
inputs = dynprompt.get_node(node_id)["inputs"]
|
||||
for input_data in inputs.values():
|
||||
if is_link(input_data): # Check if the input is a link to another node
|
||||
ancestor_id = input_data[0]
|
||||
self.descendants[ancestor_id].add(node_id)
|
||||
self.ancestors[node_id].add(ancestor_id)
|
||||
|
||||
def set(self, node_id, value):
|
||||
"""
|
||||
Mark a node as executed and store its value in the cache.
|
||||
|
||||
Args:
|
||||
node_id: The ID of the node to store.
|
||||
value: The value to store for the node.
|
||||
"""
|
||||
self._set_immediate(node_id, value)
|
||||
self.executed_nodes.add(node_id)
|
||||
self._cleanup_ancestors(node_id)
|
||||
|
||||
def get(self, node_id):
|
||||
"""
|
||||
Retrieve the cached value for a node.
|
||||
|
||||
Args:
|
||||
node_id: The ID of the node to retrieve.
|
||||
|
||||
Returns:
|
||||
The cached value for the node.
|
||||
"""
|
||||
return self._get_immediate(node_id)
|
||||
|
||||
def ensure_subcache_for(self, node_id, children_ids):
|
||||
"""
|
||||
Ensure a subcache exists for a node and update dependencies.
|
||||
|
||||
Args:
|
||||
node_id: The ID of the parent node.
|
||||
children_ids: List of child node IDs to associate with the parent node.
|
||||
|
||||
Returns:
|
||||
The subcache object for the node.
|
||||
"""
|
||||
subcache = super()._ensure_subcache(node_id, children_ids)
|
||||
for child_id in children_ids:
|
||||
self.descendants[node_id].add(child_id)
|
||||
self.ancestors[child_id].add(node_id)
|
||||
return subcache
|
||||
|
||||
def _cleanup_ancestors(self, node_id):
|
||||
"""
|
||||
Check if ancestors of a node can be removed from the cache.
|
||||
|
||||
Args:
|
||||
node_id: The ID of the node whose ancestors are to be checked.
|
||||
"""
|
||||
for ancestor_id in self.ancestors.get(node_id, []):
|
||||
if ancestor_id in self.executed_nodes:
|
||||
# Remove ancestor if all its descendants have been executed
|
||||
if all(descendant in self.executed_nodes for descendant in self.descendants[ancestor_id]):
|
||||
self._remove_node(ancestor_id)
|
||||
|
||||
def _remove_node(self, node_id):
|
||||
"""
|
||||
Remove a node from the cache.
|
||||
|
||||
Args:
|
||||
node_id: The ID of the node to remove.
|
||||
"""
|
||||
cache_key = self.cache_key_set.get_data_key(node_id)
|
||||
if cache_key in self.cache:
|
||||
del self.cache[cache_key]
|
||||
subcache_key = self.cache_key_set.get_subcache_key(node_id)
|
||||
if subcache_key in self.subcaches:
|
||||
del self.subcaches[subcache_key]
|
||||
|
||||
def clean_unused(self):
|
||||
"""
|
||||
Clean up unused nodes. This is a no-op for this cache implementation.
|
||||
"""
|
||||
pass
|
||||
|
||||
def recursive_debug_dump(self):
|
||||
"""
|
||||
Dump the cache and dependency graph for debugging.
|
||||
|
||||
Returns:
|
||||
A list containing the cache state and dependency graph.
|
||||
"""
|
||||
result = super().recursive_debug_dump()
|
||||
result.append({
|
||||
"descendants": self.descendants,
|
||||
"ancestors": self.ancestors,
|
||||
"executed_nodes": list(self.executed_nodes),
|
||||
})
|
||||
return result
|
||||
|
@ -9,7 +9,7 @@ class Morphology:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {"image": ("IMAGE",),
|
||||
"operation": (["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"],),
|
||||
"operation": (["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"],),
|
||||
"kernel_size": ("INT", {"default": 3, "min": 3, "max": 999, "step": 1}),
|
||||
}}
|
||||
|
||||
|
53
execution.py
53
execution.py
@ -15,7 +15,7 @@ import nodes
|
||||
import comfy.model_management
|
||||
from comfy_execution.graph import get_input_info, ExecutionList, DynamicPrompt, ExecutionBlocker
|
||||
from comfy_execution.graph_utils import is_link, GraphBuilder
|
||||
from comfy_execution.caching import HierarchicalCache, LRUCache, CacheKeySetInputSignature, CacheKeySetID
|
||||
from comfy_execution.caching import HierarchicalCache, LRUCache, DependencyAwareCache, CacheKeySetInputSignature, CacheKeySetID
|
||||
from comfy_execution.validation import validate_node_input
|
||||
|
||||
class ExecutionResult(Enum):
|
||||
@ -59,20 +59,27 @@ class IsChangedCache:
|
||||
self.is_changed[node_id] = node["is_changed"]
|
||||
return self.is_changed[node_id]
|
||||
|
||||
class CacheSet:
|
||||
def __init__(self, lru_size=None):
|
||||
if lru_size is None or lru_size == 0:
|
||||
self.init_classic_cache()
|
||||
else:
|
||||
self.init_lru_cache(lru_size)
|
||||
self.all = [self.outputs, self.ui, self.objects]
|
||||
|
||||
# Useful for those with ample RAM/VRAM -- allows experimenting without
|
||||
# blowing away the cache every time
|
||||
def init_lru_cache(self, cache_size):
|
||||
self.outputs = LRUCache(CacheKeySetInputSignature, max_size=cache_size)
|
||||
self.ui = LRUCache(CacheKeySetInputSignature, max_size=cache_size)
|
||||
self.objects = HierarchicalCache(CacheKeySetID)
|
||||
class CacheType(Enum):
|
||||
CLASSIC = 0
|
||||
LRU = 1
|
||||
DEPENDENCY_AWARE = 2
|
||||
|
||||
|
||||
class CacheSet:
|
||||
def __init__(self, cache_type=None, cache_size=None):
|
||||
if cache_type == CacheType.DEPENDENCY_AWARE:
|
||||
self.init_dependency_aware_cache()
|
||||
logging.info("Disabling intermediate node cache.")
|
||||
elif cache_type == CacheType.LRU:
|
||||
if cache_size is None:
|
||||
cache_size = 0
|
||||
self.init_lru_cache(cache_size)
|
||||
logging.info("Using LRU cache")
|
||||
else:
|
||||
self.init_classic_cache()
|
||||
|
||||
self.all = [self.outputs, self.ui, self.objects]
|
||||
|
||||
# Performs like the old cache -- dump data ASAP
|
||||
def init_classic_cache(self):
|
||||
@ -80,6 +87,17 @@ class CacheSet:
|
||||
self.ui = HierarchicalCache(CacheKeySetInputSignature)
|
||||
self.objects = HierarchicalCache(CacheKeySetID)
|
||||
|
||||
def init_lru_cache(self, cache_size):
|
||||
self.outputs = LRUCache(CacheKeySetInputSignature, max_size=cache_size)
|
||||
self.ui = LRUCache(CacheKeySetInputSignature, max_size=cache_size)
|
||||
self.objects = HierarchicalCache(CacheKeySetID)
|
||||
|
||||
# only hold cached items while the decendents have not executed
|
||||
def init_dependency_aware_cache(self):
|
||||
self.outputs = DependencyAwareCache(CacheKeySetInputSignature)
|
||||
self.ui = DependencyAwareCache(CacheKeySetInputSignature)
|
||||
self.objects = DependencyAwareCache(CacheKeySetID)
|
||||
|
||||
def recursive_debug_dump(self):
|
||||
result = {
|
||||
"outputs": self.outputs.recursive_debug_dump(),
|
||||
@ -414,13 +432,14 @@ def execute(server, dynprompt, caches, current_item, extra_data, executed, promp
|
||||
return (ExecutionResult.SUCCESS, None, None)
|
||||
|
||||
class PromptExecutor:
|
||||
def __init__(self, server, lru_size=None):
|
||||
self.lru_size = lru_size
|
||||
def __init__(self, server, cache_type=False, cache_size=None):
|
||||
self.cache_size = cache_size
|
||||
self.cache_type = cache_type
|
||||
self.server = server
|
||||
self.reset()
|
||||
|
||||
def reset(self):
|
||||
self.caches = CacheSet(self.lru_size)
|
||||
self.caches = CacheSet(cache_type=self.cache_type, cache_size=self.cache_size)
|
||||
self.status_messages = []
|
||||
self.success = True
|
||||
|
||||
|
@ -84,7 +84,7 @@ class CacheHelper:
|
||||
cache_helper = CacheHelper()
|
||||
|
||||
extension_mimetypes_cache = {
|
||||
"webp" : "image",
|
||||
"webp": "image",
|
||||
}
|
||||
|
||||
def map_legacy(folder_name: str) -> str:
|
||||
|
8
main.py
8
main.py
@ -156,7 +156,13 @@ def cuda_malloc_warning():
|
||||
|
||||
def prompt_worker(q, server_instance):
|
||||
current_time: float = 0.0
|
||||
e = execution.PromptExecutor(server_instance, lru_size=args.cache_lru)
|
||||
cache_type = execution.CacheType.CLASSIC
|
||||
if args.cache_lru > 0:
|
||||
cache_type = execution.CacheType.LRU
|
||||
elif args.cache_none:
|
||||
cache_type = execution.CacheType.DEPENDENCY_AWARE
|
||||
|
||||
e = execution.PromptExecutor(server_instance, cache_type=cache_type, cache_size=args.cache_lru)
|
||||
last_gc_collect = 0
|
||||
need_gc = False
|
||||
gc_collect_interval = 10.0
|
||||
|
4
nodes.py
4
nodes.py
@ -1989,7 +1989,7 @@ NODE_CLASS_MAPPINGS = {
|
||||
"ImageBatch": ImageBatch,
|
||||
"ImagePadForOutpaint": ImagePadForOutpaint,
|
||||
"EmptyImage": EmptyImage,
|
||||
"ConditioningAverage": ConditioningAverage ,
|
||||
"ConditioningAverage": ConditioningAverage,
|
||||
"ConditioningCombine": ConditioningCombine,
|
||||
"ConditioningConcat": ConditioningConcat,
|
||||
"ConditioningSetArea": ConditioningSetArea,
|
||||
@ -2076,7 +2076,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"LatentUpscaleBy": "Upscale Latent By",
|
||||
"LatentComposite": "Latent Composite",
|
||||
"LatentBlend": "Latent Blend",
|
||||
"LatentFromBatch" : "Latent From Batch",
|
||||
"LatentFromBatch": "Latent From Batch",
|
||||
"RepeatLatentBatch": "Repeat Latent Batch",
|
||||
# Image
|
||||
"SaveImage": "Save Image",
|
||||
|
@ -1,5 +1,5 @@
|
||||
[pytest]
|
||||
markers =
|
||||
markers =
|
||||
inference: mark as inference test (deselect with '-m "not inference"')
|
||||
execution: mark as execution test (deselect with '-m "not execution"')
|
||||
testpaths =
|
||||
|
@ -1,4 +1,4 @@
|
||||
comfyui-frontend-package==1.14.6
|
||||
comfyui-frontend-package==1.15.13
|
||||
torch
|
||||
torchsde
|
||||
torchvision
|
||||
|
@ -48,7 +48,7 @@ async def send_socket_catch_exception(function, message):
|
||||
@web.middleware
|
||||
async def cache_control(request: web.Request, handler):
|
||||
response: web.Response = await handler(request)
|
||||
if request.path.endswith('.js') or request.path.endswith('.css'):
|
||||
if request.path.endswith('.js') or request.path.endswith('.css') or request.path.endswith('index.json'):
|
||||
response.headers.setdefault('Cache-Control', 'no-cache')
|
||||
return response
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user