pdist¶

paddle. pdist ( x, p=2.0, name=None ) [source]

Computes the p-norm distance between every pair of row vectors in the input.

Parameters

• x (Tensor) – The input tensor with shape \(N \times M\).

• p (float, optional) – The value for the p-norm distance to calculate between each vector pair. Default: \(2.0\).

• name (str, optional) – For details, please refer to Name. Generally, no setting is required. Default: None.

Returns

Tensor with shape \(N(N-1)/2\) , the dtype is same as input tensor.

Examples

>>> import paddle
>>> paddle.seed(2023)
>>> a = paddle.randn([4, 5])
>>> print(a)
Tensor(shape=[4, 5], dtype=float32, place=Place(cpu), stop_gradient=True,
       [[ 0.06132207,  1.11349595,  0.41906244, -0.24858207, -1.85169315],
        [-1.50370061,  1.73954511,  0.13331604,  1.66359663, -0.55764782],
        [-0.59911072, -0.57773495, -1.03176904, -0.33741450, -0.29695082],
        [-1.50258386,  0.67233968, -1.07747352,  0.80170447, -0.06695852]])
>>> pdist_out=paddle.pdist(a)
>>> print(pdist_out)
Tensor(shape=[6], dtype=float32, place=Place(cpu), stop_gradient=True,
       [2.87295413, 2.79758120, 3.02793980, 3.40844536, 1.89435327, 1.93171620])