202 lines
10 KiB
Python
202 lines
10 KiB
Python
from torch import Tensor
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import torch
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from .control import TimestepKeyframeImport, TimestepKeyframeGroupImport, ControlWeightsImport, get_properly_arranged_t2i_weights, linear_conversion
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from .logger import logger
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WEIGHTS_RETURN_NAMES = ("CN_WEIGHTS", "TK_SHORTCUT")
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class DefaultWeightsImport:
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@classmethod
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def INPUT_TYPES(s):
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return {
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}
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RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
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RETURN_NAMES = WEIGHTS_RETURN_NAMES
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FUNCTION = "load_weights"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights"
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def load_weights(self):
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weights = ControlWeightsImport.default()
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return (weights, TimestepKeyframeGroupImport.default(TimestepKeyframeImport(control_weights=weights)))
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class ScaledSoftMaskedUniversalWeightsImport:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"mask": ("MASK", ),
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"min_base_multiplier": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}, ),
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"max_base_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}, ),
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#"lock_min": ("BOOLEAN", {"default": False}, ),
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#"lock_max": ("BOOLEAN", {"default": False}, ),
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},
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}
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RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
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RETURN_NAMES = WEIGHTS_RETURN_NAMES
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FUNCTION = "load_weights"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights"
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def load_weights(self, mask: Tensor, min_base_multiplier: float, max_base_multiplier: float, lock_min=False, lock_max=False):
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# normalize mask
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mask = mask.clone()
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x_min = 0.0 if lock_min else mask.min()
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x_max = 1.0 if lock_max else mask.max()
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if x_min == x_max:
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mask = torch.ones_like(mask) * max_base_multiplier
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else:
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mask = linear_conversion(mask, x_min, x_max, min_base_multiplier, max_base_multiplier)
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weights = ControlWeightsImport.universal_mask(weight_mask=mask)
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return (weights, TimestepKeyframeGroupImport.default(TimestepKeyframeImport(control_weights=weights)))
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class ScaledSoftUniversalWeightsImport:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"base_multiplier": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 1.0, "step": 0.001}, ),
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"flip_weights": ("BOOLEAN", {"default": False}),
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},
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}
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RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
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RETURN_NAMES = WEIGHTS_RETURN_NAMES
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FUNCTION = "load_weights"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights"
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def load_weights(self, base_multiplier, flip_weights):
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weights = ControlWeightsImport.universal(base_multiplier=base_multiplier, flip_weights=flip_weights)
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return (weights, TimestepKeyframeGroupImport.default(TimestepKeyframeImport(control_weights=weights)))
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class SoftControlNetWeightsImport:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"weight_00": ("FLOAT", {"default": 0.09941396206337118, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_01": ("FLOAT", {"default": 0.12050177219802567, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_02": ("FLOAT", {"default": 0.14606275417942507, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_03": ("FLOAT", {"default": 0.17704576264172736, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_04": ("FLOAT", {"default": 0.214600924414215, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_05": ("FLOAT", {"default": 0.26012233262329093, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_06": ("FLOAT", {"default": 0.3152997971191405, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_07": ("FLOAT", {"default": 0.3821815722656249, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_08": ("FLOAT", {"default": 0.4632503906249999, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_09": ("FLOAT", {"default": 0.561515625, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_10": ("FLOAT", {"default": 0.6806249999999999, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_11": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_12": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"flip_weights": ("BOOLEAN", {"default": False}),
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},
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}
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RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
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RETURN_NAMES = WEIGHTS_RETURN_NAMES
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FUNCTION = "load_weights"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/ControlNet"
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def load_weights(self, weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
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weight_07, weight_08, weight_09, weight_10, weight_11, weight_12, flip_weights):
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weights = [weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
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weight_07, weight_08, weight_09, weight_10, weight_11, weight_12]
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weights = ControlWeightsImport.controlnet(weights, flip_weights=flip_weights)
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return (weights, TimestepKeyframeGroupImport.default(TimestepKeyframeImport(control_weights=weights)))
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class CustomControlNetWeightsImport:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"weight_00": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_01": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_02": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_04": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_05": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_06": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_07": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_08": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_09": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_10": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_11": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_12": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"flip_weights": ("BOOLEAN", {"default": False}),
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}
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}
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RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
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RETURN_NAMES = WEIGHTS_RETURN_NAMES
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FUNCTION = "load_weights"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/ControlNet"
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def load_weights(self, weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
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weight_07, weight_08, weight_09, weight_10, weight_11, weight_12, flip_weights):
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weights = [weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
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weight_07, weight_08, weight_09, weight_10, weight_11, weight_12]
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weights = ControlWeightsImport.controlnet(weights, flip_weights=flip_weights)
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return (weights, TimestepKeyframeGroupImport.default(TimestepKeyframeImport(control_weights=weights)))
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class SoftT2IAdapterWeightsImport:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"weight_00": ("FLOAT", {"default": 0.25, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_01": ("FLOAT", {"default": 0.62, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_02": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"flip_weights": ("BOOLEAN", {"default": False}),
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},
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}
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RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
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RETURN_NAMES = WEIGHTS_RETURN_NAMES
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FUNCTION = "load_weights"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/T2IAdapter"
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def load_weights(self, weight_00, weight_01, weight_02, weight_03, flip_weights):
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weights = [weight_00, weight_01, weight_02, weight_03]
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weights = get_properly_arranged_t2i_weights(weights)
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weights = ControlWeightsImport.t2iadapter(weights, flip_weights=flip_weights)
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return (weights, TimestepKeyframeGroupImport.default(TimestepKeyframeImport(control_weights=weights)))
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class CustomT2IAdapterWeightsImport:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"weight_00": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_01": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_02": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"flip_weights": ("BOOLEAN", {"default": False}),
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},
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}
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RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
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RETURN_NAMES = WEIGHTS_RETURN_NAMES
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FUNCTION = "load_weights"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/T2IAdapter"
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def load_weights(self, weight_00, weight_01, weight_02, weight_03, flip_weights):
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weights = [weight_00, weight_01, weight_02, weight_03]
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weights = get_properly_arranged_t2i_weights(weights)
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weights = ControlWeightsImport.t2iadapter(weights, flip_weights=flip_weights)
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return (weights, TimestepKeyframeGroupImport.default(TimestepKeyframeImport(control_weights=weights)))
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