Fast previews for mochi.
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@ -190,7 +190,21 @@ class Mochi(LatentFormat):
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0.9294154431013696, 1.3720942357788521, 0.881393668867029,
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0.9168315692124348, 0.9185249279345552, 0.9274757570805041]).view(1, self.latent_channels, 1, 1, 1)
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self.latent_rgb_factors = None #TODO
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self.latent_rgb_factors =[
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[-0.0069, -0.0045, 0.0018],
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[ 0.0154, -0.0692, -0.0274],
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[ 0.0333, 0.0019, 0.0206],
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[-0.1390, 0.0628, 0.1678],
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[-0.0725, 0.0134, -0.1898],
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[ 0.0074, -0.0270, -0.0209],
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[-0.0176, -0.0277, -0.0221],
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[ 0.5294, 0.5204, 0.3852],
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[-0.0326, -0.0446, -0.0143],
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[-0.0659, 0.0153, -0.0153],
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[ 0.0185, -0.0217, 0.0014],
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[-0.0396, -0.0495, -0.0281]
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]
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self.latent_rgb_factors_bias = [-0.0940, -0.1418, -0.1453]
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self.taesd_decoder_name = None #TODO
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def process_in(self, latent):
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@ -47,7 +47,12 @@ class Latent2RGBPreviewer(LatentPreviewer):
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if self.latent_rgb_factors_bias is not None:
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self.latent_rgb_factors_bias = self.latent_rgb_factors_bias.to(dtype=x0.dtype, device=x0.device)
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latent_image = torch.nn.functional.linear(x0[0].permute(1, 2, 0), self.latent_rgb_factors, bias=self.latent_rgb_factors_bias)
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if x0.ndim == 5:
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x0 = x0[0, :, 0]
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else:
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x0 = x0[0]
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latent_image = torch.nn.functional.linear(x0.movedim(0, -1), self.latent_rgb_factors, bias=self.latent_rgb_factors_bias)
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# latent_image = x0[0].permute(1, 2, 0) @ self.latent_rgb_factors
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return preview_to_image(latent_image)
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