nodes/Haoming02-comfyui-diffusion-cg
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minor value refreshes

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Haoming
2023-12-10 02:53:24 +08:00
parent f1fd309c04
commit ef660dd643
2 changed files with 12 additions and 26 deletions
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normalization.py
+10 -24
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@@ -1,5 +1,11 @@
DYNAMIC_RANGE = [19.75, 14.275, 14.275, 14.275]
DYNAMIC_RANGE_XL = [27.62, 19.96, 19.96]
DYNAMIC_RANGE = [18, 14, 14, 14]
DYNAMIC_RANGE_XL = [20, 16, 16]
def normalize_tensor(x, r):
ratio = r / max(abs(float(x.min())), abs(float(x.max())))
x *= max(ratio, 0.99)
return x
class Normalization:
@classmethod
@@ -14,17 +20,7 @@ class Normalization:
batches = latent['samples'].size(0)
for b in range(batches):
for c in range(4):
delta = latent['samples'][b][c].mean()
latent['samples'][b][c] -= delta
xmin = abs(float(latent['samples'][b][c].min()))
xmax = abs(float(latent['samples'][b][c].max()))
r = DYNAMIC_RANGE[c] / max(xmin, xmax)
ratio = max(0.95, r)
latent['samples'][b][c] *= ratio
latent['samples'][b][c] += delta
latent['samples'][b][c] = normalize_tensor(latent['samples'][b][c], DYNAMIC_RANGE[c])
return (latent,)
@@ -41,16 +37,6 @@ class NormalizationXL:
batches = latent['samples'].size(0)
for b in range(batches):
for c in range(3):
delta = latent['samples'][b][c].mean()
latent['samples'][b][c] -= delta
xmin = abs(float(latent['samples'][b][c].min()))
xmax = abs(float(latent['samples'][b][c].max()))
r = DYNAMIC_RANGE_XL[c] / max(xmin, xmax)
ratio = max(0.95, r)
latent['samples'][b][c] *= ratio
latent['samples'][b][c] += delta
latent['samples'][b][c] = normalize_tensor(latent['samples'][b][c], DYNAMIC_RANGE_XL[c])
return (latent,)