from typing import Callable, Union import comfy.hooks import comfy.model_patcher import comfy.patcher_extension import comfy.sample import comfy.samplers from comfy.model_patcher import ModelPatcher from comfy.controlnet import ControlBase from comfy.ldm.modules.attention import BasicTransformerBlock from .control import convert_all_to_advanced, restore_all_controlnet_conns from .control_reference import (ReferenceAdvanced, ReferenceInjections, RefBasicTransformerBlock, RefTimestepEmbedSequential, InjectionBasicTransformerBlockHolder, InjectionTimestepEmbedSequentialHolder, _forward_inject_BasicTransformerBlock, handle_context_ref_setup, handle_reference_injection, REF_CONTROL_LIST_ALL, CONTEXTREF_CLEAN_FUNC) from .dinklink import get_dinklink from .utils import torch_dfs, WrapperConsts def prepare_dinklink_acn_wrapper(): # expose acn_sampler_sample_wrapper d = get_dinklink() link_acn = d.setdefault(WrapperConsts.ACN, {}) link_acn[WrapperConsts.VERSION] = 10000 link_acn[WrapperConsts.ACN_CREATE_SAMPLER_SAMPLE_WRAPPER] = (comfy.patcher_extension.WrappersMP.OUTER_SAMPLE, WrapperConsts.ACN_OUTER_SAMPLE_WRAPPER_KEY, acn_outer_sample_wrapper) def support_sliding_context_windows(conds) -> tuple[bool, list[dict]]: # convert to advanced, with report if anything was actually modified modified, new_conds = convert_all_to_advanced(conds) return modified, new_conds def has_sliding_context_windows(model: ModelPatcher): params = model.get_attachment("ADE_params") if params is None: # backwards compatibility params = getattr(model, "motion_injection_params", None) if params is None: return False context_options = getattr(params, "context_options") return context_options.context_length is not None def get_contextref_obj(model: ModelPatcher): params = model.get_attachment("ADE_params") if params is None: # backwards compatibility params = getattr(model, "motion_injection_params", None) if params is None: return None context_options = getattr(params, "context_options") extras = getattr(context_options, "extras", None) if extras is None: return None return getattr(extras, "context_ref", None) def get_refcn(control: ControlBase, order: int=-1): ref_set: set[ReferenceAdvanced] = set() if control is None: return ref_set if type(control) == ReferenceAdvanced and not control.is_context_ref: control.order = order order -= 1 ref_set.add(control) ref_set.update(get_refcn(control.previous_controlnet, order=order)) return ref_set def should_register_outer_sample_wrapper(hook, model, model_options: dict, target, registered: list): wrappers = comfy.patcher_extension.get_wrappers_with_key(comfy.patcher_extension.WrappersMP.OUTER_SAMPLE, WrapperConsts.ACN_OUTER_SAMPLE_WRAPPER_KEY, model_options, is_model_options=True) return len(wrappers) == 0 def create_wrapper_hooks(): wrappers = {} comfy.patcher_extension.add_wrapper_with_key(comfy.patcher_extension.WrappersMP.OUTER_SAMPLE, WrapperConsts.ACN_OUTER_SAMPLE_WRAPPER_KEY, acn_outer_sample_wrapper, transformer_options=wrappers) hooks = comfy.hooks.HookGroup() hook = comfy.hooks.WrapperHook(wrappers) hook.hook_id = WrapperConsts.ACN_OUTER_SAMPLE_WRAPPER_KEY hook.custom_should_register = should_register_outer_sample_wrapper hooks.add(hook) return hooks def acn_outer_sample_wrapper(executor, *args, **kwargs): controlnets_modified = False guider: comfy.samplers.CFGGuider = executor.class_obj model = guider.model_patcher orig_conds = guider.conds orig_model_options = guider.model_options try: new_model_options = orig_model_options # if context options present, perform some special actions that may be required context_refs = [] if has_sliding_context_windows(guider.model_patcher): new_model_options = comfy.model_patcher.create_model_options_clone(new_model_options) # convert all CNs to Advanced if needed controlnets_modified, conds = support_sliding_context_windows(orig_conds) if controlnets_modified: guider.conds = conds # enable ContextRef, if requested existing_contextref_obj = get_contextref_obj(guider.model_patcher) if existing_contextref_obj is not None: context_refs = handle_context_ref_setup(existing_contextref_obj, new_model_options["transformer_options"], guider.conds) controlnets_modified = True # look for Advanced ControlNets that will require intervention to work ref_set = set() for outer_cond in guider.conds.values(): for cond in outer_cond: if "control" in cond: ref_set.update(get_refcn(cond["control"])) # if no ref cn found, do original function immediately if len(ref_set) == 0 and len(context_refs) == 0: return executor(*args, **kwargs) # otherwise, injection time try: # inject # storage for all Reference-related injections reference_injections = ReferenceInjections() # first, handle attn module injection all_modules = torch_dfs(model.model) attn_modules: list[RefBasicTransformerBlock] = [] for module in all_modules: if isinstance(module, BasicTransformerBlock): attn_modules.append(module) attn_modules = [module for module in all_modules if isinstance(module, BasicTransformerBlock)] attn_modules = sorted(attn_modules, key=lambda x: -x.norm1.normalized_shape[0]) for i, module in enumerate(attn_modules): injection_holder = InjectionBasicTransformerBlockHolder(block=module, idx=i) injection_holder.attn_weight = float(i) / float(len(attn_modules)) if hasattr(module, "_forward"): # backward compatibility module._forward = _forward_inject_BasicTransformerBlock.__get__(module, type(module)) else: module.forward = _forward_inject_BasicTransformerBlock.__get__(module, type(module)) module.injection_holder = injection_holder reference_injections.attn_modules.append(module) # figure out which module is middle block if hasattr(model.model.diffusion_model, "middle_block"): mid_modules = torch_dfs(model.model.diffusion_model.middle_block) mid_attn_modules: list[RefBasicTransformerBlock] = [module for module in mid_modules if isinstance(module, BasicTransformerBlock)] for module in mid_attn_modules: module.injection_holder.is_middle = True # next, handle gn module injection (TimestepEmbedSequential) # TODO: figure out the logic behind these hardcoded indexes if type(model.model).__name__ == "SDXL": input_block_indices = [4, 5, 7, 8] output_block_indices = [0, 1, 2, 3, 4, 5] else: input_block_indices = [4, 5, 7, 8, 10, 11] output_block_indices = [0, 1, 2, 3, 4, 5, 6, 7] if hasattr(model.model.diffusion_model, "middle_block"): module = model.model.diffusion_model.middle_block injection_holder = InjectionTimestepEmbedSequentialHolder(block=module, idx=0, is_middle=True) injection_holder.gn_weight = 0.0 module.injection_holder = injection_holder reference_injections.gn_modules.append(module) for w, i in enumerate(input_block_indices): module = model.model.diffusion_model.input_blocks[i] injection_holder = InjectionTimestepEmbedSequentialHolder(block=module, idx=i, is_input=True) injection_holder.gn_weight = 1.0 - float(w) / float(len(input_block_indices)) module.injection_holder = injection_holder reference_injections.gn_modules.append(module) for w, i in enumerate(output_block_indices): module = model.model.diffusion_model.output_blocks[i] injection_holder = InjectionTimestepEmbedSequentialHolder(block=module, idx=i, is_output=True) injection_holder.gn_weight = float(w) / float(len(output_block_indices)) module.injection_holder = injection_holder reference_injections.gn_modules.append(module) # hack gn_module forwards and update weights for i, module in enumerate(reference_injections.gn_modules): module.injection_holder.gn_weight *= 2 # store ordered ref cns in model's transformer options new_model_options = comfy.model_patcher.create_model_options_clone(new_model_options) # handle diffusion_model forward injection handle_reference_injection(new_model_options, reference_injections) ref_list: list[ReferenceAdvanced] = list(ref_set) new_model_options["transformer_options"][REF_CONTROL_LIST_ALL] = sorted(ref_list, key=lambda x: x.order) new_model_options["transformer_options"][CONTEXTREF_CLEAN_FUNC] = reference_injections.clean_contextref_module_mem guider.model_options = new_model_options # continue with original function return executor(*args, **kwargs) finally: # cleanup injections # restore attn modules attn_modules: list[RefBasicTransformerBlock] = reference_injections.attn_modules for module in attn_modules: module.injection_holder.restore(module) module.injection_holder.clean_all() del module.injection_holder del attn_modules # restore gn modules gn_modules: list[RefTimestepEmbedSequential] = reference_injections.gn_modules for module in gn_modules: module.injection_holder.restore(module) module.injection_holder.clean_all() del module.injection_holder del gn_modules # cleanup reference_injections.cleanup() finally: # restore model_options guider.model_options = orig_model_options # restore guider.conds guider.conds = orig_conds # restore controlnets in conds, if needed if controlnets_modified: restore_all_controlnet_conns(guider.conds) del orig_conds del orig_model_options del model del guider