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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,)
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