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Wan 2.2 support. (#9080)
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@@ -457,6 +457,82 @@ class Wan21(LatentFormat):
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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 Wan22(Wan21):
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latent_channels = 48
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latent_dimensions = 3
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latent_rgb_factors = [
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[ 0.0119, 0.0103, 0.0046],
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[-0.1062, -0.0504, 0.0165],
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[ 0.0140, 0.0409, 0.0491],
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[-0.0813, -0.0677, 0.0607],
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[ 0.0656, 0.0851, 0.0808],
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[ 0.0264, 0.0463, 0.0912],
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[ 0.0295, 0.0326, 0.0590],
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[-0.0244, -0.0270, 0.0025],
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[ 0.0443, -0.0102, 0.0288],
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[-0.0465, -0.0090, -0.0205],
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[ 0.0359, 0.0236, 0.0082],
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[-0.0776, 0.0854, 0.1048],
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[ 0.0564, 0.0264, 0.0561],
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[ 0.0006, 0.0594, 0.0418],
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[-0.0319, -0.0542, -0.0637],
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[-0.0268, 0.0024, 0.0260],
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[ 0.0539, 0.0265, 0.0358],
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[-0.0359, -0.0312, -0.0287],
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[-0.0285, -0.1032, -0.1237],
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[ 0.1041, 0.0537, 0.0622],
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[-0.0086, -0.0374, -0.0051],
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[ 0.0390, 0.0670, 0.2863],
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[ 0.0069, 0.0144, 0.0082],
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[ 0.0006, -0.0167, 0.0079],
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[ 0.0313, -0.0574, -0.0232],
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[-0.1454, -0.0902, -0.0481],
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[ 0.0714, 0.0827, 0.0447],
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[-0.0304, -0.0574, -0.0196],
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[ 0.0401, 0.0384, 0.0204],
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[-0.0758, -0.0297, -0.0014],
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[ 0.0568, 0.1307, 0.1372],
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[-0.0055, -0.0310, -0.0380],
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[ 0.0239, -0.0305, 0.0325],
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[-0.0663, -0.0673, -0.0140],
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[-0.0416, -0.0047, -0.0023],
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[ 0.0166, 0.0112, -0.0093],
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[-0.0211, 0.0011, 0.0331],
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[ 0.1833, 0.1466, 0.2250],
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[-0.0368, 0.0370, 0.0295],
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[-0.3441, -0.3543, -0.2008],
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[-0.0479, -0.0489, -0.0420],
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[-0.0660, -0.0153, 0.0800],
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[-0.0101, 0.0068, 0.0156],
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[-0.0690, -0.0452, -0.0927],
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[-0.0145, 0.0041, 0.0015],
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[ 0.0421, 0.0451, 0.0373],
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[ 0.0504, -0.0483, -0.0356],
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[-0.0837, 0.0168, 0.0055]
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]
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latent_rgb_factors_bias = [0.0317, -0.0878, -0.1388]
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def __init__(self):
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self.scale_factor = 1.0
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self.latents_mean = torch.tensor([
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-0.2289, -0.0052, -0.1323, -0.2339, -0.2799, 0.0174, 0.1838, 0.1557,
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-0.1382, 0.0542, 0.2813, 0.0891, 0.1570, -0.0098, 0.0375, -0.1825,
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-0.2246, -0.1207, -0.0698, 0.5109, 0.2665, -0.2108, -0.2158, 0.2502,
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-0.2055, -0.0322, 0.1109, 0.1567, -0.0729, 0.0899, -0.2799, -0.1230,
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-0.0313, -0.1649, 0.0117, 0.0723, -0.2839, -0.2083, -0.0520, 0.3748,
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0.0152, 0.1957, 0.1433, -0.2944, 0.3573, -0.0548, -0.1681, -0.0667,
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]).view(1, self.latent_channels, 1, 1, 1)
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self.latents_std = torch.tensor([
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0.4765, 1.0364, 0.4514, 1.1677, 0.5313, 0.4990, 0.4818, 0.5013,
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0.8158, 1.0344, 0.5894, 1.0901, 0.6885, 0.6165, 0.8454, 0.4978,
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0.5759, 0.3523, 0.7135, 0.6804, 0.5833, 1.4146, 0.8986, 0.5659,
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0.7069, 0.5338, 0.4889, 0.4917, 0.4069, 0.4999, 0.6866, 0.4093,
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0.5709, 0.6065, 0.6415, 0.4944, 0.5726, 1.2042, 0.5458, 1.6887,
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0.3971, 1.0600, 0.3943, 0.5537, 0.5444, 0.4089, 0.7468, 0.7744
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]).view(1, self.latent_channels, 1, 1, 1)
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class Hunyuan3Dv2(LatentFormat):
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latent_channels = 64
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latent_dimensions = 1
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