ComfyUI/comfy/sampler_helpers.py

137 lines
5.0 KiB
Python

from __future__ import annotations
import uuid
import torch
import comfy.model_management
import comfy.conds
import comfy.utils
import comfy.hooks
import comfy.patcher_extension
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from comfy.model_patcher import ModelPatcher
from comfy.model_base import BaseModel
from comfy.controlnet import ControlBase
def prepare_mask(noise_mask, shape, device):
return comfy.utils.reshape_mask(noise_mask, shape).to(device)
def get_models_from_cond(cond, model_type):
models = []
for c in cond:
if model_type in c:
if isinstance(c[model_type], list):
models += c[model_type]
else:
models += [c[model_type]]
return models
def get_hooks_from_cond(cond, hooks_dict: dict[comfy.hooks.EnumHookType, dict[comfy.hooks.Hook, None]]):
# get hooks from conds, and collect cnets so they can be checked for extra_hooks
cnets: list[ControlBase] = []
for c in cond:
if 'hooks' in c:
for hook in c['hooks'].hooks:
hook: comfy.hooks.Hook
with_type = hooks_dict.setdefault(hook.hook_type, {})
with_type[hook] = None
if 'control' in c:
cnets.append(c['control'])
def get_extra_hooks_from_cnet(cnet: ControlBase, _list: list):
if cnet.extra_hooks is not None:
_list.append(cnet.extra_hooks)
if cnet.previous_controlnet is None:
return _list
return get_extra_hooks_from_cnet(cnet.previous_controlnet, _list)
hooks_list = []
cnets = set(cnets)
for base_cnet in cnets:
get_extra_hooks_from_cnet(base_cnet, hooks_list)
extra_hooks = comfy.hooks.HookGroup.combine_all_hooks(hooks_list)
if extra_hooks is not None:
for hook in extra_hooks.hooks:
with_type = hooks_dict.setdefault(hook.hook_type, {})
with_type[hook] = None
return hooks_dict
def convert_cond(cond):
out = []
for c in cond:
temp = c[1].copy()
model_conds = temp.get("model_conds", {})
if c[0] is not None:
model_conds["c_crossattn"] = comfy.conds.CONDCrossAttn(c[0]) #TODO: remove
temp["cross_attn"] = c[0]
temp["model_conds"] = model_conds
temp["uuid"] = uuid.uuid4()
out.append(temp)
return out
def get_additional_models(conds, dtype):
"""loads additional models in conditioning"""
cnets: list[ControlBase] = []
gligen = []
add_models = []
hooks: dict[comfy.hooks.EnumHookType, dict[comfy.hooks.Hook, None]] = {}
for k in conds:
cnets += get_models_from_cond(conds[k], "control")
gligen += get_models_from_cond(conds[k], "gligen")
add_models += get_models_from_cond(conds[k], "additional_models")
get_hooks_from_cond(conds[k], hooks)
control_nets = set(cnets)
inference_memory = 0
control_models = []
for m in control_nets:
control_models += m.get_models()
inference_memory += m.inference_memory_requirements(dtype)
gligen = [x[1] for x in gligen]
hook_models = [x.model for x in hooks.get(comfy.hooks.EnumHookType.AddModels, {}).keys()]
models = control_models + gligen + add_models + hook_models
return models, inference_memory
def cleanup_additional_models(models):
"""cleanup additional models that were loaded"""
for m in models:
if hasattr(m, 'cleanup'):
m.cleanup()
def prepare_sampling(model: 'ModelPatcher', noise_shape, conds):
device = model.load_device
real_model: 'BaseModel' = None
models, inference_memory = get_additional_models(conds, model.model_dtype())
models += model.get_all_additional_models() # TODO: does this require inference_memory update?
memory_required = model.memory_required([noise_shape[0] * 2] + list(noise_shape[1:])) + inference_memory
minimum_memory_required = model.memory_required([noise_shape[0]] + list(noise_shape[1:])) + inference_memory
comfy.model_management.load_models_gpu([model] + models, memory_required=memory_required, minimum_memory_required=minimum_memory_required)
real_model = model.model
return real_model, conds, models
def cleanup_models(conds, models):
cleanup_additional_models(models)
control_cleanup = []
for k in conds:
control_cleanup += get_models_from_cond(conds[k], "control")
cleanup_additional_models(set(control_cleanup))
def prepare_model_patcher(model: 'ModelPatcher', conds, model_options: dict):
# check for hooks in conds - if not registered, see if can be applied
hooks = {}
for k in conds:
get_hooks_from_cond(conds[k], hooks)
# add wrappers and callbacks from ModelPatcher to transformer_options
model_options["transformer_options"]["wrappers"] = comfy.patcher_extension.copy_nested_dicts(model.wrappers)
model_options["transformer_options"]["callbacks"] = comfy.patcher_extension.copy_nested_dicts(model.callbacks)
# register hooks on model/model_options
model.register_all_hook_patches(hooks, comfy.hooks.EnumWeightTarget.Model, model_options)