178 lines
6.0 KiB
Python
178 lines
6.0 KiB
Python
import torch
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class LatentFormat:
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scale_factor = 1.0
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latent_channels = 4
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latent_rgb_factors = None
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latent_rgb_factors_bias = None
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taesd_decoder_name = None
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def process_in(self, latent):
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return latent * self.scale_factor
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def process_out(self, latent):
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return latent / self.scale_factor
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class SD15(LatentFormat):
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def __init__(self, scale_factor=0.18215):
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self.scale_factor = scale_factor
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self.latent_rgb_factors = [
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# R G B
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[ 0.3512, 0.2297, 0.3227],
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[ 0.3250, 0.4974, 0.2350],
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[-0.2829, 0.1762, 0.2721],
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[-0.2120, -0.2616, -0.7177]
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]
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self.taesd_decoder_name = "taesd_decoder"
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class SDXL(LatentFormat):
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scale_factor = 0.13025
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def __init__(self):
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self.latent_rgb_factors = [
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# R G B
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[ 0.3651, 0.4232, 0.4341],
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[-0.2533, -0.0042, 0.1068],
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[ 0.1076, 0.1111, -0.0362],
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[-0.3165, -0.2492, -0.2188]
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]
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self.latent_rgb_factors_bias = [ 0.1084, -0.0175, -0.0011]
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self.taesd_decoder_name = "taesdxl_decoder"
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class SDXL_Playground_2_5(LatentFormat):
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def __init__(self):
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self.scale_factor = 0.5
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self.latents_mean = torch.tensor([-1.6574, 1.886, -1.383, 2.5155]).view(1, 4, 1, 1)
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self.latents_std = torch.tensor([8.4927, 5.9022, 6.5498, 5.2299]).view(1, 4, 1, 1)
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self.latent_rgb_factors = [
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# R G B
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[ 0.3920, 0.4054, 0.4549],
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[-0.2634, -0.0196, 0.0653],
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[ 0.0568, 0.1687, -0.0755],
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[-0.3112, -0.2359, -0.2076]
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]
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self.taesd_decoder_name = "taesdxl_decoder"
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def process_in(self, latent):
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latents_mean = self.latents_mean.to(latent.device, latent.dtype)
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latents_std = self.latents_std.to(latent.device, latent.dtype)
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return (latent - latents_mean) * self.scale_factor / latents_std
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def process_out(self, latent):
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latents_mean = self.latents_mean.to(latent.device, latent.dtype)
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latents_std = self.latents_std.to(latent.device, latent.dtype)
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return latent * latents_std / self.scale_factor + latents_mean
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class SD_X4(LatentFormat):
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def __init__(self):
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self.scale_factor = 0.08333
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self.latent_rgb_factors = [
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[-0.2340, -0.3863, -0.3257],
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[ 0.0994, 0.0885, -0.0908],
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[-0.2833, -0.2349, -0.3741],
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[ 0.2523, -0.0055, -0.1651]
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]
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class SC_Prior(LatentFormat):
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latent_channels = 16
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def __init__(self):
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self.scale_factor = 1.0
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self.latent_rgb_factors = [
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[-0.0326, -0.0204, -0.0127],
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[-0.1592, -0.0427, 0.0216],
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[ 0.0873, 0.0638, -0.0020],
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[-0.0602, 0.0442, 0.1304],
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[ 0.0800, -0.0313, -0.1796],
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[-0.0810, -0.0638, -0.1581],
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[ 0.1791, 0.1180, 0.0967],
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[ 0.0740, 0.1416, 0.0432],
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[-0.1745, -0.1888, -0.1373],
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[ 0.2412, 0.1577, 0.0928],
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[ 0.1908, 0.0998, 0.0682],
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[ 0.0209, 0.0365, -0.0092],
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[ 0.0448, -0.0650, -0.1728],
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[-0.1658, -0.1045, -0.1308],
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[ 0.0542, 0.1545, 0.1325],
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[-0.0352, -0.1672, -0.2541]
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]
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class SC_B(LatentFormat):
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def __init__(self):
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self.scale_factor = 1.0 / 0.43
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self.latent_rgb_factors = [
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[ 0.1121, 0.2006, 0.1023],
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[-0.2093, -0.0222, -0.0195],
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[-0.3087, -0.1535, 0.0366],
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[ 0.0290, -0.1574, -0.4078]
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]
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class SD3(LatentFormat):
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latent_channels = 16
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def __init__(self):
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self.scale_factor = 1.5305
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self.shift_factor = 0.0609
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self.latent_rgb_factors = [
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[-0.0922, -0.0175, 0.0749],
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[ 0.0311, 0.0633, 0.0954],
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[ 0.1994, 0.0927, 0.0458],
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[ 0.0856, 0.0339, 0.0902],
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[ 0.0587, 0.0272, -0.0496],
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[-0.0006, 0.1104, 0.0309],
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[ 0.0978, 0.0306, 0.0427],
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[-0.0042, 0.1038, 0.1358],
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[-0.0194, 0.0020, 0.0669],
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[-0.0488, 0.0130, -0.0268],
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[ 0.0922, 0.0988, 0.0951],
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[-0.0278, 0.0524, -0.0542],
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[ 0.0332, 0.0456, 0.0895],
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[-0.0069, -0.0030, -0.0810],
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[-0.0596, -0.0465, -0.0293],
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[-0.1448, -0.1463, -0.1189]
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]
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self.latent_rgb_factors_bias = [0.2394, 0.2135, 0.1925]
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self.taesd_decoder_name = "taesd3_decoder"
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def process_in(self, latent):
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return (latent - self.shift_factor) * self.scale_factor
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def process_out(self, latent):
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return (latent / self.scale_factor) + self.shift_factor
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class StableAudio1(LatentFormat):
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latent_channels = 64
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class Flux(SD3):
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latent_channels = 16
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def __init__(self):
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self.scale_factor = 0.3611
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self.shift_factor = 0.1159
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self.latent_rgb_factors =[
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[-0.0346, 0.0244, 0.0681],
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[ 0.0034, 0.0210, 0.0687],
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[ 0.0275, -0.0668, -0.0433],
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[-0.0174, 0.0160, 0.0617],
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[ 0.0859, 0.0721, 0.0329],
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[ 0.0004, 0.0383, 0.0115],
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[ 0.0405, 0.0861, 0.0915],
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[-0.0236, -0.0185, -0.0259],
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[-0.0245, 0.0250, 0.1180],
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[ 0.1008, 0.0755, -0.0421],
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[-0.0515, 0.0201, 0.0011],
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[ 0.0428, -0.0012, -0.0036],
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[ 0.0817, 0.0765, 0.0749],
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[-0.1264, -0.0522, -0.1103],
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[-0.0280, -0.0881, -0.0499],
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[-0.1262, -0.0982, -0.0778]
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]
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self.latent_rgb_factors_bias = [-0.0329, -0.0718, -0.0851]
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self.taesd_decoder_name = "taef1_decoder"
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def process_in(self, latent):
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return (latent - self.shift_factor) * self.scale_factor
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def process_out(self, latent):
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return (latent / self.scale_factor) + self.shift_factor
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