jax.numpy.maximum#

jax.numpy.maximum=<jnp.ufunc'maximum'>#

Return element-wise maximum of the input arrays.

JAX implementation ofnumpy.maximum.

Parameters:

• x – input array or scalar.

• y – input array or scalar. Bothx andy should either have same shapeor be broadcast compatible.

• args (ArrayLike)

• out (None)

• where (None)

Returns:

An array containing the element-wise maximum ofx andy.

Return type:

Any

Note

For each pair of elements,jnp.maximum returns:

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

• nan if one element isnan.

See also

• jax.numpy.minimum(): Returns element-wise minimum of the inputarrays.

• jax.numpy.fmax(): Returns element-wise maximum of the input arrays,ignoring NaNs.

• jax.numpy.amax(): Returns the maximum of array elements along a givenaxis.

• jax.numpy.nanmax(): Returns the maximum of the array elements alonga given axis, ignoring NaNs.

Examples

Inputs withx.shape==y.shape:

>>>x=jnp.array([1,-5,3,2])>>>y=jnp.array([-2,4,7,-6])>>>jnp.maximum(x,y)Array([1, 4, 7, 2], dtype=int32)

Inputs with broadcast compatibility:

>>>x1=jnp.array([[-2,5,7,4],...[1,-6,3,8]])>>>y1=jnp.array([-5,3,6,9])>>>jnp.maximum(x1,y1)Array([[-2,  5,  7,  9],       [ 1,  3,  6,  9]], dtype=int32)

Inputs havingnan:

>>>nan=jnp.nan>>>x2=jnp.array([nan,-3,9])>>>y2=jnp.array([[4,-2,nan],...[-3,-5,10]])>>>jnp.maximum(x2,y2)Array([[nan, -2., nan],      [nan, -3., 10.]], dtype=float32)