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mindspore.ops.logaddexp

mindspore.ops.logaddexp(input, other)

Computes the logarithm of the sum of exponentiations of the inputs.

$$ou{t}_i=\log (exp(inpu{t}_i)+\exp (othe{r}_i))$$

Parameters

• input (Tensor) – Input Tensor. The dtype of input must be float.

• other (Tensor) – Input Tensor. The dtype of input must be float. If the shape of input is not equal to the shape of other, they must be broadcastable to a common shape (which becomes the shape of the output).

Returns

Tensor.

Raises

• TypeError – If input, other is not a Tensor.

• TypeError – The dtype of input or other is not float.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x1 = Tensor(np.array([1, 2, 3]).astype(np.float16))
>>> x2 = Tensor(np.array(2).astype(np.float16))
>>> output = ops.logaddexp(x1, x2)
>>> print(output)
[2.312 2.693 3.312]