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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

- Incorrect links, empty cells, or wrong formats.

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mindspore.ops.hypot

mindspore.ops.hypot(input, other)

Computes hypotenuse of input tensors element-wise as legs of a right triangle. The shape of two inputs should be broadcastable, and data type of them should be one of: float32, float64

$$ou{t}_i=\sqrt{inpu{t}_i^2+othe{r}_i^2}$$

Parameters

• input (Tensor) – The first input tensor.

• other (Tensor) – The second input tensor.

Returns

Tensor, the shape is the same as the one after broadcasting, and the data type is one with higher precision in the two inputs.

Raises

• TypeError – If data type input or other is not float32 or float64.

• ValueError – If shape of two inputs are not broadcastable.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> input = Tensor(np.array([3., 5., 7.]))
>>> other = Tensor(np.array([4., 12., 24.]))
>>> y = ops.hypot(input, other)
>>> print(y)
[ 5. 13. 25.]