* Fix for Perlin noise issue for cuda as well.

This commit is contained in:
Peter Baylies 2022-10-07 18:43:55 -04:00 committed by Lincoln Stein
parent 4c026d9d92
commit 27f62999c9

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@ -223,15 +223,15 @@ def rand_perlin_2d(shape, res, device, fade = lambda t: 6*t**5 - 15*t**4 + 10*t*
rand_val = torch.rand(res[0]+1, res[1]+1) rand_val = torch.rand(res[0]+1, res[1]+1)
angles = 2*math.pi*rand_val angles = 2*math.pi*rand_val
gradients = torch.stack((torch.cos(angles), torch.sin(angles)), dim = -1) gradients = torch.stack((torch.cos(angles), torch.sin(angles)), dim = -1).to(device)
tile_grads = lambda slice1, slice2: gradients[slice1[0]:slice1[1], slice2[0]:slice2[1]].repeat_interleave(d[0], 0).repeat_interleave(d[1], 1) tile_grads = lambda slice1, slice2: gradients[slice1[0]:slice1[1], slice2[0]:slice2[1]].repeat_interleave(d[0], 0).repeat_interleave(d[1], 1)
dot = lambda grad, shift: (torch.stack((grid[:shape[0],:shape[1],0] + shift[0], grid[:shape[0],:shape[1], 1] + shift[1] ), dim = -1) * grad[:shape[0], :shape[1]]).sum(dim = -1) dot = lambda grad, shift: (torch.stack((grid[:shape[0],:shape[1],0] + shift[0], grid[:shape[0],:shape[1], 1] + shift[1] ), dim = -1) * grad[:shape[0], :shape[1]]).sum(dim = -1)
n00 = dot(tile_grads([0, -1], [0, -1]), [0, 0]) n00 = dot(tile_grads([0, -1], [0, -1]), [0, 0]).to(device)
n10 = dot(tile_grads([1, None], [0, -1]), [-1, 0]) n10 = dot(tile_grads([1, None], [0, -1]), [-1, 0]).to(device)
n01 = dot(tile_grads([0, -1],[1, None]), [0, -1]) n01 = dot(tile_grads([0, -1],[1, None]), [0, -1]).to(device)
n11 = dot(tile_grads([1, None], [1, None]), [-1,-1]) n11 = dot(tile_grads([1, None], [1, None]), [-1,-1]).to(device)
t = fade(grid[:shape[0], :shape[1]]) t = fade(grid[:shape[0], :shape[1]])
return math.sqrt(2) * torch.lerp(torch.lerp(n00, n10, t[..., 0]), torch.lerp(n01, n11, t[..., 0]), t[..., 1]) return math.sqrt(2) * torch.lerp(torch.lerp(n00, n10, t[..., 0]), torch.lerp(n01, n11, t[..., 0]), t[..., 1]).to(device)