from __future__ import annotations from typing import Callable class CallbacksMP: ON_CLONE = "on_clone" ON_LOAD = "on_load_after" ON_CLEANUP = "on_cleanup" ON_PRE_RUN = "on_pre_run" ON_PREPARE_STATE = "on_prepare_state" ON_APPLY_HOOKS = "on_apply_hooks" ON_REGISTER_ALL_HOOK_PATCHES = "on_register_all_hook_patches" ON_INJECT_MODEL = "on_inject_model" ON_EJECT_MODEL = "on_eject_model" # callbacks dict is in the format: # {"call_type": {"key": [Callable1, Callable2, ...]} } @classmethod def init_callbacks(cls) -> dict[str, dict[str, list[Callable]]]: return {} def add_callback(call_type: str, callback: Callable, transformer_options: dict, is_model_options=False): add_callback_with_key(call_type, None, callback, transformer_options, is_model_options) def add_callback_with_key(call_type: str, key: str, callback: Callable, transformer_options: dict, is_model_options=False): if is_model_options: transformer_options = transformer_options.get("transformer_options", {}) callbacks: dict[str, dict[str, list]] = transformer_options.get("callbacks", {}) c = callbacks.setdefault(call_type, {}).setdefault(key, []) c.append(callback) def get_all_callbacks(call_type: str, transformer_options: dict, is_model_options=False): if is_model_options: transformer_options = transformer_options.get("transformer_options", {}) c_list = [] callbacks: dict[str, list] = transformer_options.get("callbacks", {}) for c in callbacks.get(call_type, {}).values(): c_list.extend(c) return c_list class WrappersMP: OUTER_SAMPLE = "outer_sample" SAMPLER_SAMPLE = "sampler_sample" CALC_COND_BATCH = "calc_cond_batch" APPLY_MODEL = "apply_model" DIFFUSION_MODEL = "diffusion_model" # wrappers dict is in the format: # {"wrapper_type": {"key": [Callable1, Callable2, ...]} } @classmethod def init_wrappers(cls) -> dict[str, dict[str, list[Callable]]]: return {} def add_wrapper(wrapper_type: str, wrapper: Callable, transformer_options: dict, is_model_options=False): add_wrapper_with_key(wrapper_type, None, wrapper, transformer_options, is_model_options) def add_wrapper_with_key(wrapper_type: str, key: str, wrapper: Callable, transformer_options: dict, is_model_options=False): if is_model_options: transformer_options = transformer_options.get("transformer_options", {}) wrappers: dict[str, dict[str, list]] = transformer_options.get("wrappers", {}) w = wrappers.setdefault(wrapper_type, {}).setdefault(key, []) w.append(wrapper) def get_all_wrappers(wrapper_type: str, transformer_options: dict, is_model_options=False): if is_model_options: transformer_options = transformer_options.get("transformer_options", {}) w_list = [] wrappers: dict[str, list] = transformer_options.get("wrappers", {}) for w in wrappers.get(wrapper_type, {}).values(): w_list.extend(w) return w_list class WrapperExecutor: """Handles call stack of wrappers around a function in an ordered manner.""" def __init__(self, original: Callable, class_obj: object, wrappers: list[Callable], idx: int): # NOTE: class_obj exists so that wrappers surrounding a class method can access # the class instance at runtime via executor.class_obj self.original = original self.class_obj = class_obj self.wrappers = wrappers.copy() self.idx = idx self.is_last = idx == len(wrappers) def __call__(self, *args, **kwargs): """Calls the next wrapper or original function, whichever is appropriate.""" new_executor = self._create_next_executor() return new_executor.execute(*args, **kwargs) def execute(self, *args, **kwargs): """Used to initiate executor internally - DO NOT use this if you received executor in wrapper.""" args = list(args) kwargs = dict(kwargs) if self.is_last: return self.original(*args, **kwargs) return self.wrappers[self.idx](self, *args, **kwargs) def _create_next_executor(self) -> 'WrapperExecutor': new_idx = self.idx + 1 if new_idx > len(self.wrappers): raise Exception(f"Wrapper idx exceeded available wrappers; something went very wrong.") if self.class_obj is None: return WrapperExecutor.new_executor(self.original, self.wrappers, new_idx) return WrapperExecutor.new_class_executor(self.original, self.class_obj, self.wrappers, new_idx) @classmethod def new_executor(cls, original: Callable, wrappers: list[Callable], idx=0): return cls(original, class_obj=None, wrappers=wrappers, idx=idx) @classmethod def new_class_executor(cls, original: Callable, class_obj: object, wrappers: list[Callable], idx=0): return cls(original, class_obj, wrappers, idx=idx) class PatcherInjection: def __init__(self, inject: Callable, eject: Callable): self.inject = inject self.eject = eject def copy_nested_dicts(input_dict: dict): new_dict = input_dict.copy() for key, value in input_dict.items(): if isinstance(value, dict): new_dict[key] = copy_nested_dicts(value) elif isinstance(value, list): new_dict[key] = value.copy() return new_dict def merge_nested_dicts(dict1: dict, dict2: dict, copy_dict1=True): if copy_dict1: merged_dict = copy_nested_dicts(dict1) else: merged_dict = dict1 for key, value in dict2.items(): if isinstance(value, dict): curr_value = merged_dict.setdefault(key, {}) merged_dict[key] = merge_nested_dicts(value, curr_value) elif isinstance(value, list): merged_dict.setdefault(key, []).extend(value) else: merged_dict[key] = value return merged_dict