The spec has recently been updated to only require multiaxis (i.e., tuple)
indices in the case where every axis is indexed, meaning there are either as
many indices as axes or the index has an ellipsis.

where does value-based promotion for 0-dimensional arrays, so we use the same
trick as in the Array operators to avoid this.

Printing behavior isn't required by the spec. This is just to make things
easier to understand, especially with the array API test suite.

from_dlpack() should be used to create arrays using DLPack.

unique() in the array API was replaced with three separate functions,
unique_all(), unique_inverse(), and unique_values(), in order to avoid
polymorphic return types.

Additionally, it should be noted that these functions to not currently conform
to the spec with respect to NaN behavior. The spec requires multiple NaNs to
be returned, but np.unique() returns a single NaN. Since this is currently an
open issue in NumPy to possibly revert, I have not yet worked around this. See
numpy#20326.

This does nothing in NumPy, and is just present so that the signature is valid
according to the spec.

The "multiaxis indexing must index every axis explicitly or use an ellipsis"
was supposed to include any type of index, not just tuple indices.

Co-authored-by: Bas van Beek <43369155+BvB93@users.noreply.github.com>

The array_api cannot use the NumPy testing functions because array_api arrays
do not mix with NumPy arrays, and also NumPy testing functions may use APIs
that aren't supported in the array API.

…rray-api-updates2