jax.numpy.fmax#

jax.numpy.fmax(x1, x2)[source]#

Return element-wise maximum of the input arrays.

JAX implementation of numpy.fmax().

Parameters:

  • x1 (ArrayLike) – input array or scalar

  • x2 (ArrayLike) – input array or scalar. x1 and x1 must either have same shape or be broadcast compatible.

Returns:

An array containing the element-wise maximum of x1 and x2.

Return type:

Array

Note

For each pair of elements, jnp.fmax returns:

  • the larger of the two if both elements are finite numbers.

  • finite number if one element is nan.

  • nan if both elements are nan.

  • inf if one element is inf and the other is finite or nan.

  • -inf if one element is -inf and the other is nan.

Examples

>>> jnp.fmax(3, 7)
Array(7, dtype=int32, weak_type=True)
>>> jnp.fmax(5, jnp.array([1, 7, 9, 4]))
Array([5, 7, 9, 5], dtype=int32)

>>> x1 = jnp.array([1, 3, 7, 8])
>>> x2 = jnp.array([-1, 4, 6, 9])
>>> jnp.fmax(x1, x2)
Array([1, 4, 7, 9], dtype=int32)

>>> x3 = jnp.array([[2, 3, 5, 10],
...                 [11, 9, 7, 5]])
>>> jnp.fmax(x1, x3)
Array([[ 2,  3,  7, 10],
       [11,  9,  7,  8]], dtype=int32)

>>> x4 = jnp.array([jnp.inf, 6, -jnp.inf, nan])
>>> x5 = jnp.array([[3, 5, 7, nan],
...                 [nan, 9, nan, -1]])
>>> jnp.fmax(x4, x5)
Array([[ inf,   6.,   7.,  nan],
       [ inf,   9., -inf,  -1.]], dtype=float32)