from pathlib import Path import torch import comfy.sample as comfy_sample from comfy.model_patcher import ModelPatcher from .ad_settings import AdjustGroup, AnimateDiffSettings, AdjustPE, AdjustWeight from .context import ContextOptions, ContextOptionsGroup, ContextSchedules from .logger import logger from .utils_model import BetaSchedules, get_available_motion_loras, get_available_motion_models, get_motion_lora_path from .utils_motion import ADKeyframeGroup, get_combined_multival from .motion_lora import MotionLoraInfo, MotionLoraList from .motion_module_ad import AllPerBlocks from .model_injection import (ModelPatcherHelper, InjectionParams, MotionModelGroup, get_mm_attachment, load_motion_lora_as_patches, load_motion_module_gen1, load_motion_module_gen2, validate_model_compatibility_gen2, validate_per_block_compatibility) from .sample_settings import SampleSettings, SeedNoiseGeneration from .sampling import outer_sample_wrapper, sliding_calc_cond_batch class AnimateDiffLoaderGen1: @classmethod def INPUT_TYPES(s): return { "required": { "model": ("MODEL",), "model_name": (get_available_motion_models(),), "beta_schedule": (BetaSchedules.ALIAS_LIST, {"default": BetaSchedules.AUTOSELECT}), #"apply_mm_groupnorm_hack": ("BOOLEAN", {"default": True}), }, "optional": { "context_options": ("CONTEXT_OPTIONS",), "motion_lora": ("MOTION_LORA",), "ad_settings": ("AD_SETTINGS",), "ad_keyframes": ("AD_KEYFRAMES",), "sample_settings": ("SAMPLE_SETTINGS",), "scale_multival": ("MULTIVAL",), "effect_multival": ("MULTIVAL",), "per_block": ("PER_BLOCK",), } } RETURN_TYPES = ("MODEL",) CATEGORY = "Animate Diff 🎭🅐🅓/① Gen1 nodes ①" FUNCTION = "load_mm_and_inject_params" def load_mm_and_inject_params(self, model: ModelPatcher, model_name: str, beta_schedule: str,# apply_mm_groupnorm_hack: bool, context_options: ContextOptionsGroup=None, motion_lora: MotionLoraList=None, ad_settings: AnimateDiffSettings=None, sample_settings: SampleSettings=None, scale_multival=None, effect_multival=None, ad_keyframes: ADKeyframeGroup=None, per_block: AllPerBlocks=None, ): # load motion module and motion settings, if included motion_model = load_motion_module_gen2(model_name=model_name, motion_model_settings=ad_settings) # confirm that it is compatible with SD model validate_model_compatibility_gen2(model=model, motion_model=motion_model) # apply motion model to loaded_mm if motion_lora is not None: for lora in motion_lora.loras: load_motion_lora_as_patches(motion_model, lora) attachment = get_mm_attachment(motion_model) attachment.scale_multival = scale_multival attachment.effect_multival = effect_multival if per_block is not None: validate_per_block_compatibility(motion_model=motion_model, all_per_blocks=per_block) attachment.per_block_list = per_block.per_block_list attachment.keyframes = ad_keyframes.clone() if ad_keyframes else ADKeyframeGroup() # create injection params params = InjectionParams(unlimited_area_hack=False) # apply context options if context_options: params.set_context(context_options) # set motion_scale and motion_model_settings if not ad_settings: ad_settings = AnimateDiffSettings() ad_settings.attn_scale = 1.0 params.set_motion_model_settings(ad_settings) # backwards compatibility to support old way of masking scale if params.motion_model_settings.mask_attn_scale is not None: attachment.scale_multival = get_combined_multival(scale_multival, (params.motion_model_settings.mask_attn_scale * params.motion_model_settings.attn_scale)) # need to use a ModelPatcher that supports injection of motion modules into unet model = model.clone() helper = ModelPatcherHelper(model) helper.set_all_properties( outer_sampler_wrapper=outer_sample_wrapper, calc_cond_batch_wrapper=sliding_calc_cond_batch, params=params, sample_settings=sample_settings, motion_models=MotionModelGroup(motion_model), ) sample_settings = helper.get_sample_settings() if sample_settings.custom_cfg is not None: logger.info("[Sample Settings] custom_cfg is set; will override any KSampler cfg values or patches.") if sample_settings.sigma_schedule is not None: logger.info("[Sample Settings] sigma_schedule is set; will override beta_schedule.") model.add_object_patch("model_sampling", sample_settings.sigma_schedule.clone().model_sampling) else: # save model sampling from BetaSchedule as object patch # if autoselect, get suggested beta_schedule from motion model if beta_schedule == BetaSchedules.AUTOSELECT and helper.get_motion_models(): beta_schedule = helper.get_motion_models()[0].model.get_best_beta_schedule(log=True) new_model_sampling = BetaSchedules.to_model_sampling(beta_schedule, model) if new_model_sampling is not None: model.add_object_patch("model_sampling", new_model_sampling) del motion_model return (model,) class LegacyAnimateDiffLoaderWithContext: @classmethod def INPUT_TYPES(s): return { "required": { "model": ("MODEL",), "model_name": (get_available_motion_models(),), "beta_schedule": (BetaSchedules.ALIAS_LIST, {"default": BetaSchedules.AUTOSELECT}), #"apply_mm_groupnorm_hack": ("BOOLEAN", {"default": True}), }, "optional": { "context_options": ("CONTEXT_OPTIONS",), "motion_lora": ("MOTION_LORA",), "ad_settings": ("AD_SETTINGS",), "sample_settings": ("SAMPLE_SETTINGS",), "motion_scale": ("FLOAT", {"default": 1.0, "min": 0.0, "step": 0.001}), "apply_v2_models_properly": ("BOOLEAN", {"default": True}), "ad_keyframes": ("AD_KEYFRAMES",), } } DEPRECATED = True RETURN_TYPES = ("MODEL",) CATEGORY = "Animate Diff 🎭🅐🅓/① Gen1 nodes ①" FUNCTION = "load_mm_and_inject_params" def load_mm_and_inject_params(self, model: ModelPatcher, model_name: str, beta_schedule: str,# apply_mm_groupnorm_hack: bool, context_options: ContextOptionsGroup=None, motion_lora: MotionLoraList=None, ad_settings: AnimateDiffSettings=None, motion_model_settings: AnimateDiffSettings=None, sample_settings: SampleSettings=None, motion_scale: float=1.0, apply_v2_models_properly: bool=False, ad_keyframes: ADKeyframeGroup=None, ): if ad_settings is not None: motion_model_settings = ad_settings # load motion module motion_model = load_motion_module_gen1(model_name, model, motion_lora=motion_lora, motion_model_settings=motion_model_settings) # set injection params params = InjectionParams( unlimited_area_hack=False, apply_v2_properly=apply_v2_models_properly, ) if context_options: params.set_context(context_options) # set motion_scale and motion_model_settings if not motion_model_settings: motion_model_settings = AnimateDiffSettings() motion_model_settings.attn_scale = motion_scale params.set_motion_model_settings(motion_model_settings) attachment = get_mm_attachment(motion_model) if params.motion_model_settings.mask_attn_scale is not None: attachment.scale_multival = params.motion_model_settings.mask_attn_scale * params.motion_model_settings.attn_scale else: attachment.scale_multival = params.motion_model_settings.attn_scale attachment.keyframes = ad_keyframes.clone() if ad_keyframes else ADKeyframeGroup() # need to use a ModelPatcher that supports injection of motion modules into unet model = model.clone() helper = ModelPatcherHelper(model) helper.set_all_properties( outer_sampler_wrapper=outer_sample_wrapper, calc_cond_batch_wrapper=sliding_calc_cond_batch, params=params, sample_settings=sample_settings, motion_models=MotionModelGroup(motion_model), ) sample_settings = helper.get_sample_settings() if sample_settings.custom_cfg is not None: logger.info("[Sample Settings] custom_cfg is set; will override any KSampler cfg values or patches.") if sample_settings.sigma_schedule is not None: logger.info("[Sample Settings] sigma_schedule is set; will override beta_schedule.") model.add_object_patch("model_sampling", sample_settings.sigma_schedule.clone().model_sampling) else: # save model sampling from BetaSchedule as object patch # if autoselect, get suggested beta_schedule from motion model if beta_schedule == BetaSchedules.AUTOSELECT and helper.get_motion_models(): beta_schedule = helper.get_motion_models()[0].model.get_best_beta_schedule(log=True) new_model_sampling = BetaSchedules.to_model_sampling(beta_schedule, model) if new_model_sampling is not None: model.add_object_patch("model_sampling", new_model_sampling) del motion_model return (model,)