jax.numpy.log

jax.numpy.log(x, /)

Calculate element-wise natural logarithm of the input.

JAX implementation of numpy.log.

Parameters:

x (ArrayLike) – input array or scalar.

Returns:

An array containing the logarithm of each element in x, promotes to inexact dtype.

Return type:

Array

Numerical Precision:

Maximum error in units in the last place (ULPs):

Platform	bfloat16	float16	float32
CPU	0	1	1
NVIDIA GPU	0	1	1
TPU v2–v5e	1	1	4030
TPU v5p	0	1	62
TPU v6e, 7x	0	1	2

See also

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

• jax.numpy.log2(): Calculates base-2 logarithm of each element of input.

• jax.numpy.log1p(): Calculates element-wise logarithm of one plus input.

Examples

jnp.log and jnp.exp are inverse functions of each other. Applying jnp.log on the result of jnp.exp(x) yields the original input x.

>>> x = jnp.array([2, 3, 4, 5])
>>> jnp.log(jnp.exp(x))
Array([2., 3., 4., 5.], dtype=float32)

Using jnp.log we can demonstrate well-known properties of logarithms, such as \(log(a*b) = log(a)+log(b)\).

>>> x1 = jnp.array([2, 1, 3, 1])
>>> x2 = jnp.array([1, 3, 2, 4])
>>> jnp.allclose(jnp.log(x1*x2), jnp.log(x1)+jnp.log(x2))
Array(True, dtype=bool)