Calculate element-wise base x1 exponential of x2.
JAX implementation of numpy.power.
x1 (ArrayLike) – scalar or array. Specifies the bases.
x2 (ArrayLike) – scalar or array. Specifies the exponent. x1 and x2 should either have same shape or be broadcast compatible.
An array containing the base x1 exponentials of x2 with same dtype as input.
Note
When x2 is a concrete integer scalar, jnp.power lowers to jax.lax.integer_pow().
When x2 is a traced scalar or an array, jnp.power lowers to jax.lax.pow().
jnp.power raises a TypeError for integer type raised to a concrete negative integer power. For a non-concrete power, the operation is invalid and the returned value is implementation-defined.
jnp.power returns nan for negative value raised to the power of non-integer values.
See also
jax.lax.pow(): Computes element-wise power, \(x^y\).
jax.lax.integer_pow(): Computes element-wise power \(x^y\), where \(y\) is a fixed integer.
jax.numpy.float_power(): Computes the first array raised to the power of second array, element-wise, by promoting to the inexact dtype.
jax.numpy.pow(): Computes the first array raised to the power of second array, element-wise.
Examples
Inputs with scalar integers:
>>> jnp.power(4, 3) Array(64, dtype=int32, weak_type=True)
Inputs with same shape:
>>> x1 = jnp.array([2, 4, 5]) >>> x2 = jnp.array([3, 0.5, 2]) >>> jnp.power(x1, x2) Array([ 8., 2., 25.], dtype=float32)
Inputs with broadcast compatibility:
>>> x3 = jnp.array([-2, 3, 1])
>>> x4 = jnp.array([[4, 1, 6],
... [1.3, 3, 5]])
>>> jnp.power(x3, x4)
Array([[16., 3., 1.],
[nan, 27., 1.]], dtype=float32)
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4