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 class Flux(SD3): def __init__(self): self.scale_factor = 0.3611 self.shift_factor = 0.1159 self.latent_rgb_factors =[ [-0.0404, 0.0159, 0.0609], [ 0.0043, 0.0298, 0.0850], [ 0.0328, -0.0749, -0.0503], [-0.0245, 0.0085, 0.0549], [ 0.0966, 0.0894, 0.0530], [ 0.0035, 0.0399, 0.0123], [ 0.0583, 0.1184, 0.1262], [-0.0191, -0.0206, -0.0306], [-0.0324, 0.0055, 0.1001], [ 0.0955, 0.0659, -0.0545], [-0.0504, 0.0231, -0.0013], [ 0.0500, -0.0008, -0.0088], [ 0.0982, 0.0941, 0.0976], [-0.1233, -0.0280, -0.0897], [-0.0005, -0.0530, -0.0020], [-0.1273, -0.0932, -0.0680] ] 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