mindspore.ops.pow

mindspore.ops.pow(input, exponent)[source]

Calculates the exponent power of each element in input.

When exponent is a Tensor, the shapes of input and exponent must be broadcastable.

\[out_{i} = input_{i} ^{ exponent_{i}}\]

Parameters

input (Union[Tensor, Number]) – The first input is a Number or a tensor whose data type is number or bool_.
exponent (Union[Tensor, Number]) –
The second input is a Number or a tensor whose data type is number or bool_.

Returns

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

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> input = Tensor(np.array([1.0, 2.0, 4.0]), mindspore.float32)
>>> exponent = 3.0
>>> output = ops.pow(input, exponent)
>>> print(output)
[ 1.  8. 64.]
>>>
>>> input = Tensor(np.array([1.0, 2.0, 4.0]), mindspore.float32)
>>> exponent = Tensor(np.array([2.0, 4.0, 3.0]), mindspore.float32)
>>> output = ops.pow(input, exponent)
>>> print(output)
[ 1. 16. 64.]