from __future__ import annotations import uuid 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, full_hooks: comfy.hooks.HookGroup): # 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: full_hooks.add(hook) 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: full_hooks.add(hook) return full_hooks 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 = comfy.hooks.HookGroup() 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 = [] for x in hooks.get_type(comfy.hooks.EnumHookType.AddModels): x: comfy.hooks.AddModelsHook hook_models.extend(x.models) 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): real_model: 'BaseModel' = None models, inference_memory = get_additional_models(conds, model.model_dtype()) models += model.get_nested_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 = comfy.hooks.HookGroup() 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.create_target_dict(comfy.hooks.EnumWeightTarget.Model), model_options)