dpnp.tensor.logaddexp¶
- dpnp.tensor.logaddexp¶
Calculates the natural logarithm of the sum of exponentials for each element x1_i of the input array x1 with the respective element x2_i of the input array x2.
This function calculates log(exp(x1) + exp(x2)) more accurately for small values of x.
- Parameters:
x1 (usm_ndarray) -- First input array, expected to have a real-valued floating-point data type.
x2 (usm_ndarray) -- Second input array, also expected to have a real-valued floating-point data type.
out ({None, usm_ndarray}, optional) --
Output array to populate. Array must have the correct shape and the expected data type.
Default:
None.order ({"C", "F", "A", "K"}, optional) --
Memory layout of the new output array, if parameter out is
None.Default:
"K".
- Returns:
out -- An array containing the element-wise results. The data type of the returned array is determined by the Type Promotion Rules.
- Return type: