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Hooks Part 2 - TransformerOptionsHook and AdditionalModelsHook (#6377)
* Add 'sigmas' to transformer_options so that downstream code can know about the full scope of current sampling run, fix Hook Keyframes' guarantee_steps=1 inconsistent behavior with sampling split across different Sampling nodes/sampling runs by referencing 'sigmas' * Cleaned up hooks.py, refactored Hook.should_register and add_hook_patches to use target_dict instead of target so that more information can be provided about the current execution environment if needed * Refactor WrapperHook into TransformerOptionsHook, as there is no need to separate out Wrappers/Callbacks/Patches into different hook types (all affect transformer_options) * Refactored HookGroup to also store a dictionary of hooks separated by hook_type, modified necessary code to no longer need to manually separate out hooks by hook_type * In inner_sample, change "sigmas" to "sampler_sigmas" in transformer_options to not conflict with the "sigmas" that will overwrite "sigmas" in _calc_cond_batch * Refactored 'registered' to be HookGroup instead of a list of Hooks, made AddModelsHook operational and compliant with should_register result, moved TransformerOptionsHook handling out of ModelPatcher.register_all_hook_patches, support patches in TransformerOptionsHook properly by casting any patches/wrappers/hooks to proper device at sample time * Made hook clone code sane, made clear ObjectPatchHook and SetInjectionsHook are not yet operational * Fix performance of hooks when hooks are appended via Cond Pair Set Props nodes by properly caching between positive and negative conds, make hook_patches_backup behave as intended (in the case that something pre-registers WeightHooks on the ModelPatcher instead of registering it at sample time) * Filter only registered hooks on self.conds in CFGGuider.sample * Make hook_scope functional for TransformerOptionsHook * removed 4 whitespace lines to satisfy Ruff, * Add a get_injections function to ModelPatcher * Made TransformerOptionsHook contribute to registered hooks properly, added some doc strings and removed a so-far unused variable * Rename AddModelsHooks to AdditionalModelsHook, rename SetInjectionsHook to InjectionsHook (not yet implemented, but at least getting the naming figured out) * Clean up a typehint
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@@ -24,15 +24,13 @@ def get_models_from_cond(cond, model_type):
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models += [c[model_type]]
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return models
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def get_hooks_from_cond(cond, hooks_dict: dict[comfy.hooks.EnumHookType, dict[comfy.hooks.Hook, None]]):
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def get_hooks_from_cond(cond, full_hooks: comfy.hooks.HookGroup):
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# get hooks from conds, and collect cnets so they can be checked for extra_hooks
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cnets: list[ControlBase] = []
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for c in cond:
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if 'hooks' in c:
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for hook in c['hooks'].hooks:
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hook: comfy.hooks.Hook
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with_type = hooks_dict.setdefault(hook.hook_type, {})
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with_type[hook] = None
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full_hooks.add(hook)
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if 'control' in c:
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cnets.append(c['control'])
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@@ -50,10 +48,9 @@ def get_hooks_from_cond(cond, hooks_dict: dict[comfy.hooks.EnumHookType, dict[co
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extra_hooks = comfy.hooks.HookGroup.combine_all_hooks(hooks_list)
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if extra_hooks is not None:
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for hook in extra_hooks.hooks:
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with_type = hooks_dict.setdefault(hook.hook_type, {})
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with_type[hook] = None
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full_hooks.add(hook)
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return hooks_dict
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return full_hooks
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def convert_cond(cond):
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out = []
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@@ -73,13 +70,11 @@ def get_additional_models(conds, dtype):
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cnets: list[ControlBase] = []
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gligen = []
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add_models = []
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hooks: dict[comfy.hooks.EnumHookType, dict[comfy.hooks.Hook, None]] = {}
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for k in conds:
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cnets += get_models_from_cond(conds[k], "control")
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gligen += get_models_from_cond(conds[k], "gligen")
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add_models += get_models_from_cond(conds[k], "additional_models")
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get_hooks_from_cond(conds[k], hooks)
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control_nets = set(cnets)
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@@ -90,11 +85,20 @@ def get_additional_models(conds, dtype):
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inference_memory += m.inference_memory_requirements(dtype)
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gligen = [x[1] for x in gligen]
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hook_models = [x.model for x in hooks.get(comfy.hooks.EnumHookType.AddModels, {}).keys()]
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models = control_models + gligen + add_models + hook_models
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models = control_models + gligen + add_models
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return models, inference_memory
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def get_additional_models_from_model_options(model_options: dict[str]=None):
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"""loads additional models from registered AddModels hooks"""
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models = []
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if model_options is not None and "registered_hooks" in model_options:
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registered: comfy.hooks.HookGroup = model_options["registered_hooks"]
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for hook in registered.get_type(comfy.hooks.EnumHookType.AdditionalModels):
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hook: comfy.hooks.AdditionalModelsHook
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models.extend(hook.models)
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return models
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def cleanup_additional_models(models):
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"""cleanup additional models that were loaded"""
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for m in models:
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@@ -102,9 +106,10 @@ def cleanup_additional_models(models):
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m.cleanup()
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def prepare_sampling(model: 'ModelPatcher', noise_shape, conds):
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real_model: 'BaseModel' = None
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def prepare_sampling(model: ModelPatcher, noise_shape, conds, model_options=None):
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real_model: BaseModel = None
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models, inference_memory = get_additional_models(conds, model.model_dtype())
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models += get_additional_models_from_model_options(model_options)
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models += model.get_nested_additional_models() # TODO: does this require inference_memory update?
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memory_required = model.memory_required([noise_shape[0] * 2] + list(noise_shape[1:])) + inference_memory
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minimum_memory_required = model.memory_required([noise_shape[0]] + list(noise_shape[1:])) + inference_memory
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@@ -123,12 +128,35 @@ def cleanup_models(conds, models):
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cleanup_additional_models(set(control_cleanup))
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def prepare_model_patcher(model: 'ModelPatcher', conds, model_options: dict):
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'''
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Registers hooks from conds.
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'''
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# check for hooks in conds - if not registered, see if can be applied
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hooks = {}
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hooks = comfy.hooks.HookGroup()
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for k in conds:
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get_hooks_from_cond(conds[k], hooks)
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# add wrappers and callbacks from ModelPatcher to transformer_options
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model_options["transformer_options"]["wrappers"] = comfy.patcher_extension.copy_nested_dicts(model.wrappers)
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model_options["transformer_options"]["callbacks"] = comfy.patcher_extension.copy_nested_dicts(model.callbacks)
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# register hooks on model/model_options
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model.register_all_hook_patches(hooks, comfy.hooks.EnumWeightTarget.Model, model_options)
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# begin registering hooks
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registered = comfy.hooks.HookGroup()
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target_dict = comfy.hooks.create_target_dict(comfy.hooks.EnumWeightTarget.Model)
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# handle all TransformerOptionsHooks
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for hook in hooks.get_type(comfy.hooks.EnumHookType.TransformerOptions):
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hook: comfy.hooks.TransformerOptionsHook
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hook.add_hook_patches(model, model_options, target_dict, registered)
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# handle all AddModelsHooks
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for hook in hooks.get_type(comfy.hooks.EnumHookType.AdditionalModels):
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hook: comfy.hooks.AdditionalModelsHook
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hook.add_hook_patches(model, model_options, target_dict, registered)
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# handle all WeightHooks by registering on ModelPatcher
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model.register_all_hook_patches(hooks, target_dict, model_options, registered)
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# add registered_hooks onto model_options for further reference
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if len(registered) > 0:
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model_options["registered_hooks"] = registered
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# merge original wrappers and callbacks with hooked wrappers and callbacks
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to_load_options: dict[str] = model_options.setdefault("to_load_options", {})
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for wc_name in ["wrappers", "callbacks"]:
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comfy.patcher_extension.merge_nested_dicts(to_load_options.setdefault(wc_name, {}), model_options["transformer_options"][wc_name],
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copy_dict1=False)
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return to_load_options
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