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Perlin noise
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@@ -410,9 +410,9 @@ def rand_perlin_2d_octaves(device, shape, res, octaves=1, persistence=0.5):
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amplitude *= persistence
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return noise
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def perlin_noise(noise, device):
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def perlin_noise(noise, device,octaves):
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b, c, w, h = noise.shape()
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perlin = lambda : rand_perlin_2d_octaves(device,(w,h),(4,4),1)
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perlin = lambda : rand_perlin_2d_octaves(device,(w,h),(4,4),octaves)
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noise_perlin_r = torch.rand(noise.shape, device=device) + perlin()
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noise_perlin_g = torch.rand(noise.shape, device=device) + perlin()
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noise_perlin_b = torch.rand(noise.shape, device=device) + perlin()
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@@ -420,7 +420,7 @@ def perlin_noise(noise, device):
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(noise_perlin_r,
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noise_perlin_g,
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noise_perlin_b),
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2)
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1)
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return noise_perlin
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@@ -2127,6 +2127,12 @@ def add_training_arguments(parser: argparse.ArgumentParser, support_dreambooth:
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default=None,
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help="enable multires noise with this number of iterations (if enabled, around 6-10 is recommended) / Multires noiseを有効にしてこのイテレーション数を設定する(有効にする場合は6-10程度を推奨)",
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)
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parser.add_argument(
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"--perlin_noise",
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type=int,
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default=None,
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help="enable perlin noise and set the octaves",
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)
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parser.add_argument(
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"--multires_noise_discount",
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type=float,
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