Calculate element-wise base x
exponential of y
.
JAX implementation of numpy.float_power
.
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.
An array containing the base x
exponentials of y
, promoting to the inexact dtype.
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 broadcast 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)
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