jax.numpy.equal#
- jax.numpy.equal(x, y, /)[source]#
Returns element-wise truth value of
x == y
.JAX implementation of
numpy.equal
. This function provides the implementation of the==
operator for JAX arrays.- Parameters:
x (ArrayLike) – input array or scalar.
y (ArrayLike) – input array or scalar.
x
andy
should either have same shape or be broadcast compatible.
- Returns:
A boolean array containing
True
where the elements ofx == y
andFalse
otherwise.- Return type:
See also
jax.numpy.not_equal()
: Returns element-wise truth value ofx != y
.jax.numpy.greater_equal()
: Returns element-wise truth value ofx >= y
.jax.numpy.less_equal()
: Returns element-wise truth value ofx <= y
.jax.numpy.greater()
: Returns element-wise truth value ofx > y
.jax.numpy.less()
: Returns element-wise truth value ofx < y
.
Examples
>>> jnp.equal(0., -0.) Array(True, dtype=bool, weak_type=True) >>> jnp.equal(1, 1.) Array(True, dtype=bool, weak_type=True) >>> jnp.equal(5, jnp.array(5)) Array(True, dtype=bool, weak_type=True) >>> jnp.equal(2, -2) Array(False, dtype=bool, weak_type=True) >>> x = jnp.array([[1, 2, 3], ... [4, 5, 6], ... [7, 8, 9]]) >>> y = jnp.array([1, 5, 9]) >>> jnp.equal(x, y) Array([[ True, False, False], [False, True, False], [False, False, True]], dtype=bool) >>> x == y Array([[ True, False, False], [False, True, False], [False, False, True]], dtype=bool)