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import torch | |
def kde(x, std=0.1): | |
# use a gaussian kernel to estimate density | |
x = x.half() # Do it in half precision | |
scores = (-torch.cdist(x, x) ** 2 / (2 * std**2)).exp() | |
density = scores.sum(dim=-1) | |
return density | |