jax.numpy.float_power

jax.numpy.float_power(x, y, /)

Calculate element-wise base x exponential of y.

JAX implementation of numpy.float_power.

Parameters:

• x (ArrayLike) – scalar or array. Specifies the bases.

• y (ArrayLike) – scalar or array. Specifies the exponents. x and y should either have same shape or be broadcast compatible.

Returns:

An array containing the base x exponentials of y, promoting to the inexact dtype.

Return type:

Array

See also

• jax.numpy.exp(): Calculates element-wise exponential of the input.

• jax.numpy.exp2(): Calculates base-2 exponential of each element of the input.

Examples

Inputs with same shape:

>>> x = jnp.array([3, 1, -5])
>>> y = jnp.array([2, 4, -1])
>>> jnp.float_power(x, y)
Array([ 9. ,  1. , -0.2], dtype=float32)

Inputs with broacast compatibility:

>>> x1 = jnp.array([[2, -4, 1],
...                 [-1, 2, 3]])
>>> y1 = jnp.array([-2, 1, 4])
>>> jnp.float_power(x1, y1)
Array([[ 0.25, -4.  ,  1.  ],
       [ 1.  ,  2.  , 81.  ]], dtype=float32)

jnp.float_power produces nan for negative values raised to a non-integer values.

>>> jnp.float_power(-3, 1.7)
Array(nan, dtype=float32, weak_type=True)