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import torch | |
class LatentFormat: | |
scale_factor = 1.0 | |
latent_channels = 4 | |
latent_rgb_factors = None | |
taesd_decoder_name = None | |
def process_in(self, latent): | |
return latent * self.scale_factor | |
def process_out(self, latent): | |
return latent / self.scale_factor | |
class SD15(LatentFormat): | |
def __init__(self, scale_factor=0.18215): | |
self.scale_factor = scale_factor | |
self.latent_rgb_factors = [ | |
# R G B | |
[ 0.3512, 0.2297, 0.3227], | |
[ 0.3250, 0.4974, 0.2350], | |
[-0.2829, 0.1762, 0.2721], | |
[-0.2120, -0.2616, -0.7177] | |
] | |
self.taesd_decoder_name = "taesd_decoder" | |
class SDXL(LatentFormat): | |
scale_factor = 0.13025 | |
def __init__(self): | |
self.latent_rgb_factors = [ | |
# R G B | |
[ 0.3920, 0.4054, 0.4549], | |
[-0.2634, -0.0196, 0.0653], | |
[ 0.0568, 0.1687, -0.0755], | |
[-0.3112, -0.2359, -0.2076] | |
] | |
self.taesd_decoder_name = "taesdxl_decoder" | |
class SDXL_Playground_2_5(LatentFormat): | |
def __init__(self): | |
self.scale_factor = 0.5 | |
self.latents_mean = torch.tensor([-1.6574, 1.886, -1.383, 2.5155]).view(1, 4, 1, 1) | |
self.latents_std = torch.tensor([8.4927, 5.9022, 6.5498, 5.2299]).view(1, 4, 1, 1) | |
self.latent_rgb_factors = [ | |
# R G B | |
[ 0.3920, 0.4054, 0.4549], | |
[-0.2634, -0.0196, 0.0653], | |
[ 0.0568, 0.1687, -0.0755], | |
[-0.3112, -0.2359, -0.2076] | |
] | |
self.taesd_decoder_name = "taesdxl_decoder" | |
def process_in(self, latent): | |
latents_mean = self.latents_mean.to(latent.device, latent.dtype) | |
latents_std = self.latents_std.to(latent.device, latent.dtype) | |
return (latent - latents_mean) * self.scale_factor / latents_std | |
def process_out(self, latent): | |
latents_mean = self.latents_mean.to(latent.device, latent.dtype) | |
latents_std = self.latents_std.to(latent.device, latent.dtype) | |
return latent * latents_std / self.scale_factor + latents_mean | |
class SD_X4(LatentFormat): | |
def __init__(self): | |
self.scale_factor = 0.08333 | |
self.latent_rgb_factors = [ | |
[-0.2340, -0.3863, -0.3257], | |
[ 0.0994, 0.0885, -0.0908], | |
[-0.2833, -0.2349, -0.3741], | |
[ 0.2523, -0.0055, -0.1651] | |
] | |
class SC_Prior(LatentFormat): | |
latent_channels = 16 | |
def __init__(self): | |
self.scale_factor = 1.0 | |
self.latent_rgb_factors = [ | |
[-0.0326, -0.0204, -0.0127], | |
[-0.1592, -0.0427, 0.0216], | |
[ 0.0873, 0.0638, -0.0020], | |
[-0.0602, 0.0442, 0.1304], | |
[ 0.0800, -0.0313, -0.1796], | |
[-0.0810, -0.0638, -0.1581], | |
[ 0.1791, 0.1180, 0.0967], | |
[ 0.0740, 0.1416, 0.0432], | |
[-0.1745, -0.1888, -0.1373], | |
[ 0.2412, 0.1577, 0.0928], | |
[ 0.1908, 0.0998, 0.0682], | |
[ 0.0209, 0.0365, -0.0092], | |
[ 0.0448, -0.0650, -0.1728], | |
[-0.1658, -0.1045, -0.1308], | |
[ 0.0542, 0.1545, 0.1325], | |
[-0.0352, -0.1672, -0.2541] | |
] | |
class SC_B(LatentFormat): | |
def __init__(self): | |
self.scale_factor = 1.0 / 0.43 | |
self.latent_rgb_factors = [ | |
[ 0.1121, 0.2006, 0.1023], | |
[-0.2093, -0.0222, -0.0195], | |
[-0.3087, -0.1535, 0.0366], | |
[ 0.0290, -0.1574, -0.4078] | |
] | |
class SD3(LatentFormat): | |
latent_channels = 16 | |
def __init__(self): | |
self.scale_factor = 1.5305 | |
self.shift_factor = 0.0609 | |
self.latent_rgb_factors = [ | |
[-0.0645, 0.0177, 0.1052], | |
[ 0.0028, 0.0312, 0.0650], | |
[ 0.1848, 0.0762, 0.0360], | |
[ 0.0944, 0.0360, 0.0889], | |
[ 0.0897, 0.0506, -0.0364], | |
[-0.0020, 0.1203, 0.0284], | |
[ 0.0855, 0.0118, 0.0283], | |
[-0.0539, 0.0658, 0.1047], | |
[-0.0057, 0.0116, 0.0700], | |
[-0.0412, 0.0281, -0.0039], | |
[ 0.1106, 0.1171, 0.1220], | |
[-0.0248, 0.0682, -0.0481], | |
[ 0.0815, 0.0846, 0.1207], | |
[-0.0120, -0.0055, -0.0867], | |
[-0.0749, -0.0634, -0.0456], | |
[-0.1418, -0.1457, -0.1259] | |
] | |
self.taesd_decoder_name = "taesd3_decoder" | |
def process_in(self, latent): | |
return (latent - self.shift_factor) * self.scale_factor | |
def process_out(self, latent): | |
return (latent / self.scale_factor) + self.shift_factor | |
class StableAudio1(LatentFormat): | |
latent_channels = 64 | |