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Update tiled_diffusion.py #77

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6 changes: 3 additions & 3 deletions tiled_diffusion.py
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Expand Up @@ -454,9 +454,9 @@ def gaussian_weights(tile_w:int, tile_h:int) -> Tensor:
This generates gaussian weights to smooth the noise of each tile.
This is critical for this method to work.
'''
f = lambda x, midpoint, var=0.01: exp(-(x-midpoint)*(x-midpoint) / (tile_w*tile_w) / (2*var)) / sqrt(2*pi*var)
x_probs = [f(x, (tile_w - 1) / 2) for x in range(tile_w)] # -1 because index goes from 0 to latent_width - 1
y_probs = [f(y, tile_h / 2) for y in range(tile_h)]
f = lambda x, midpoint, tile_dim, var=0.01: exp(-(x-midpoint)*(x-midpoint) / (tile_dim*tile_dim) / (2*var)) / sqrt(2*pi*var)
x_probs = [f(x, (tile_w - 1) / 2,tile_w) for x in range(tile_w)] # -1 because index goes from 0 to latent_width - 1
y_probs = [f(y, tile_h / 2,tile_h) for y in range(tile_h)]

w = np.outer(y_probs, x_probs)
return torch.from_numpy(w).to(devices.device, dtype=torch.float32)
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