dpnp.less_equal
- dpnp.less_equal(x1, x2, out=None, where=True, order='K', dtype=None, subok=True, **kwargs)
Computes the less-than or equal-to test results for each element x1_i of the input array x1 with the respective element x2_i of the input array x2.
For full documentation refer to
numpy.less_equal
.- Parameters:
x1 ({dpnp.ndarray, usm_ndarray, scalar}) -- First input array, expected to have numeric data type. Both inputs x1 and x2 can not be scalars at the same time.
x2 ({dpnp.ndarray, usm_ndarray, scalar}) -- Second input array, also expected to have numeric data type. Both inputs x1 and x2 can not be scalars at the same time.
out ({None, dpnp.ndarray, usm_ndarray}, optional) -- Output array to populate. Array must have the correct shape and the expected data type. Default:
None
.order ({"C", "F", "A", "K"}, optional) -- Memory layout of the newly output array, if parameter out is
None
. Default:"K"
.
- Returns:
out -- An array containing the result of element-wise less-than or equal-to comparison. The returned array has a data type of bool.
- Return type:
dpnp.ndarray
Limitations
Parameters where and subok are supported with their default values. Otherwise
NotImplementedError
exception will be raised.See also
dpnp.greater
Return the truth value of (x1 > x2) element-wise.
dpnp.less
Return the truth value of (x1 < x2) element-wise.
dpnp.greater_equal
Return the truth value of (x1 >= x2) element-wise.
dpnp.equal
Return (x1 == x2) element-wise.
dpnp.not_equal
Return (x1 != x2) element-wise.
Examples
>>> import dpnp as np >>> x1 = np.array([4, 2, 1]) >>> x2 = np.array([2, 2, 2] >>> np.less_equal(x1, x2) array([False, True, True])
The
<=
operator can be used as a shorthand forless_equal
ondpnp.ndarray
.>>> a = np.array([4, 2, 1]) >>> b = np.array([2, 2, 2]) >>> a <= b array([False, True, True])