mindspore.numpy.logaddexp
- mindspore.numpy.logaddexp(x1, x2, dtype=None)[source]
Logarithm of the sum of exponentiations of the inputs. Calculates
log(exp(x1) + exp(x2))
.Note
Numpy arguments out, where, casting, order, subok, signature, and extobj are not supported.
- Parameters
x1 (Tensor) – Input array.
x2 (Tensor) – Input array. If
x1.shape != x2.shape
, they must be broadcastable to a common shape (which becomes the shape of the output).dtype (
mindspore.dtype
) – Default:None
. Overrides the dtype of the output Tensor.
- Returns
Tensor or scalar. This is a scalar if both x1 and x2 are scalars.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore.numpy as np >>> x1 = np.array([1, 2, 3]).astype('float16') >>> x2 = np.array(2).astype('float16') >>> output = np.logaddexp(x1, x2) >>> print(output) [2.312 2.693 3.312]