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mindspore.ops.pdist

mindspore.ops.pdist(input, p=2.0)

Calculates the distance between every pair of row vectors in the input using the p-norm. If the input input is a 2D Tensor with shape $(N,M)$, the output must be a 1D Tensor with shape $(N\ast (N-1)/2,)$.

$$y[n]=\sqrt[p]{{\mid x_i-x_j\mid }^p}$$

where $x_i,x_j$ are two different row vectors in the input.

Parameters

• input (Tensor) – Input tensor. dtype: float16, float32 or float64.

• p (float) – The order of norm distance, $p\in [0,\infty )$. Default: 2.0 .

Returns

Tensor, has the same dtype as input.

Raises

• TypeError – If input is not a Tensor.

• TypeError – If dtype of input is not float16, float32 or float64.

• TypeError – If p is not a float.

• ValueError – If p is a negative float.

• ValueError – If dimension of input is less than 2.

Supported Platforms:

GPU CPU

Examples

>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.array([[1.0, 1.0], [2.0, 2.0], [3.0, 3.0]]).astype(np.float32))
>>> y = ops.pdist(x, p=2.0)
>>> print(y)
[1.4142135 2.828427 1.4142135]