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Fix perlin noise generator for diffusers tensors ()

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Tensors with diffusers no longer have to be multiples of 8. This broke Perlin noise generation. We now generate noise for the next largest multiple of 8 and return a cropped result. Fixes .
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Jonathan 2023-02-15 12:37:42 -06:00 committed by GitHub
parent 5d0dcaf81e
commit cab41f0538
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1 changed files with 5 additions and 2 deletions

7
ldm/invoke/generator/base.py

@ -247,11 +247,14 @@ class Generator:
fixdevice = 'cpu' if (self.model.device.type == 'mps') else self.model.device
# limit noise to only the diffusion image channels, not the mask channels
input_channels = min(self.latent_channels, 4)
# round up to the nearest block of 8
temp_width = int((width + 7) / 8) * 8
temp_height = int((height + 7) / 8) * 8
noise = torch.stack([
rand_perlin_2d((height, width),
rand_perlin_2d((temp_height, temp_width),
(8, 8),
device = self.model.device).to(fixdevice) for _ in range(input_channels)], dim=0).to(self.model.device)
return noise
return noise[0:4, 0:height, 0:width]
def new_seed(self):
self.seed = random.randrange(0, np.iinfo(np.uint32).max)