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Add cheap latent preview for flux 2. (#10907)

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Thank you to the person who calculated them. You saved me a percent of my
time.
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comfyanonymous 2025-11-26 01:00:43 -08:00 committed by GitHub
parent 8402c8700a
commit f16219e3aa
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2 changed files with 45 additions and 2 deletions
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40
comfy/latent_formats.py
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@ -6,6 +6,7 @@ class LatentFormat:
latent_dimensions = 2
latent_rgb_factors = None
latent_rgb_factors_bias = None
latent_rgb_factors_reshape = None
taesd_decoder_name = None
def process_in(self, latent):
@ -181,6 +182,45 @@ class Flux(SD3):
class Flux2(LatentFormat):
latent_channels = 128
def __init__(self):
self.latent_rgb_factors =[
[0.0058, 0.0113, 0.0073],
[0.0495, 0.0443, 0.0836],
[-0.0099, 0.0096, 0.0644],
[0.2144, 0.3009, 0.3652],
[0.0166, -0.0039, -0.0054],
[0.0157, 0.0103, -0.0160],
[-0.0398, 0.0902, -0.0235],
[-0.0052, 0.0095, 0.0109],
[-0.3527, -0.2712, -0.1666],
[-0.0301, -0.0356, -0.0180],
[-0.0107, 0.0078, 0.0013],
[0.0746, 0.0090, -0.0941],
[0.0156, 0.0169, 0.0070],
[-0.0034, -0.0040, -0.0114],
[0.0032, 0.0181, 0.0080],
[-0.0939, -0.0008, 0.0186],
[0.0018, 0.0043, 0.0104],
[0.0284, 0.0056, -0.0127],
[-0.0024, -0.0022, -0.0030],
[0.1207, -0.0026, 0.0065],
[0.0128, 0.0101, 0.0142],
[0.0137, -0.0072, -0.0007],
[0.0095, 0.0092, -0.0059],
[0.0000, -0.0077, -0.0049],
[-0.0465, -0.0204, -0.0312],
[0.0095, 0.0012, -0.0066],
[0.0290, -0.0034, 0.0025],
[0.0220, 0.0169, -0.0048],
[-0.0332, -0.0457, -0.0468],
[-0.0085, 0.0389, 0.0609],
[-0.0076, 0.0003, -0.0043],
[-0.0111, -0.0460, -0.0614],
]
self.latent_rgb_factors_bias = [-0.0329, -0.0718, -0.0851]
self.latent_rgb_factors_reshape = lambda t: t.reshape(t.shape[0], 32, 2, 2, t.shape[-2], t.shape[-1]).permute(0, 1, 4, 2, 5, 3).reshape(t.shape[0], 32, t.shape[-2] * 2, t.shape[-1] * 2)
def process_in(self, latent):
return latent

7
latent_preview.py
View File

@ -37,13 +37,16 @@ class TAESDPreviewerImpl(LatentPreviewer):
class Latent2RGBPreviewer(LatentPreviewer):
def __init__(self, latent_rgb_factors, latent_rgb_factors_bias=None):
def __init__(self, latent_rgb_factors, latent_rgb_factors_bias=None, latent_rgb_factors_reshape=None):
self.latent_rgb_factors = torch.tensor(latent_rgb_factors, device="cpu").transpose(0, 1)
self.latent_rgb_factors_bias = None
if latent_rgb_factors_bias is not None:
self.latent_rgb_factors_bias = torch.tensor(latent_rgb_factors_bias, device="cpu")
self.latent_rgb_factors_reshape = latent_rgb_factors_reshape
def decode_latent_to_preview(self, x0):
if self.latent_rgb_factors_reshape is not None:
x0 = self.latent_rgb_factors_reshape(x0)
self.latent_rgb_factors = self.latent_rgb_factors.to(dtype=x0.dtype, device=x0.device)
if self.latent_rgb_factors_bias is not None:
self.latent_rgb_factors_bias = self.latent_rgb_factors_bias.to(dtype=x0.dtype, device=x0.device)
@ -85,7 +88,7 @@ def get_previewer(device, latent_format):
if previewer is None:
if latent_format.latent_rgb_factors is not None:
previewer = Latent2RGBPreviewer(latent_format.latent_rgb_factors, latent_format.latent_rgb_factors_bias)
previewer = Latent2RGBPreviewer(latent_format.latent_rgb_factors, latent_format.latent_rgb_factors_bias, latent_format.latent_rgb_factors_reshape)
return previewer
def prepare_callback(model, steps, x0_output_dict=None):