jax.numpy.all#

jax.numpy.all(a, axis=None, out=None, keepdims=False, *, where=None)[source]#

Test whether all array elements along a given axis evaluate to True.

JAX implementation of numpy.all().

Parameters:

  • a (ArrayLike) – Input array.

  • axis (Axis | None) – int or array, default=None. Axis along which to be tested. If None, tests along all the axes.

  • keepdims (bool) – bool, default=False. If true, reduced axes are left in the result with size 1.

  • where (ArrayLike | None | None) – int or array of boolean dtype, default=None. The elements to be used in the test. Array should be broadcast compatible to the input.

  • out (None | None) – Unused by JAX.

Returns:

An array of boolean values.

Return type:

Array

Examples

By default, jnp.all tests for True values along all the axes.

>>> x = jnp.array([[True, True, True, False],
...                [True, False, True, False],
...                [True, True, False, False]])
>>> jnp.all(x)
Array(False, dtype=bool)

If axis=0, tests for True values along axis 0.

>>> jnp.all(x, axis=0)
Array([ True, False, False, False], dtype=bool)

If keepdims=True, ndim of the output will be same of that of the input.

>>> jnp.all(x, axis=0, keepdims=True)
Array([[ True, False, False, False]], dtype=bool)

To include specific elements in testing for True values, you can use a``where``.

>>> where=jnp.array([[1, 0, 1, 0],
...                  [0, 0, 1, 1],
...                  [1, 1, 1, 0]], dtype=bool)
>>> jnp.all(x, axis=0, keepdims=True, where=where)
Array([[ True,  True, False, False]], dtype=bool)