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torch.nn.functional.pdist
torch.nn.functional.pdist(input, p=2) → Tensor
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Computes the p-norm distance between every pair of row vectors in the input. This is identical to the upper triangular portion, excluding the diagonal, of
torch.norm(input[:, None] - input, dim=2, p=p)
. This function will be faster if the rows are contiguous.If input has shape then the output will have shape .
This function is equivalent to
scipy.spatial.distance.pdist(input, 'minkowski', p=p)
if . When it is equivalent toscipy.spatial.distance.pdist(input, 'hamming') * M
. When , the closest scipy function isscipy.spatial.distance.pdist(xn, lambda x, y: np.abs(x - y).max())
.- Parameters
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- input – input tensor of shape .
- p – p value for the p-norm distance to calculate between each vector pair .
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https://pytorch.org/docs/2.1/generated/torch.nn.functional.pdist.html