ENH: Updates to numpy.array_api (#19937)

* Add __index__ to array_api and update __int__, __bool__, and __float__

The spec specifies that they should only work on arrays with corresponding
dtypes. __index__ is new in the spec since the initial PR, and works
identically to np.array.__index__.

* Add the to_device method to the array_api

This method is new since #18585. It does nothing in NumPy since NumPy does not
support non-CPU devices.

* Update transpose methods in the array_api

transpose() was renamed to matrix_transpose() and now operates on stacks of
matrices. A function to permute dimensions will be added once it is finalized
in the spec. The attribute mT was added and the T attribute was updated to
only operate on 2-dimensional arrays as per the spec.

* Restrict input dtypes in the array API statistical functions

* Add the dtype parameter to the array API sum() and prod()

* Add the function permute_dims() to the array_api namespace

permute_dims() is the replacement for transpose(), which was split into
permute_dims() and matrix_transpose().

* Add tril and triu to the array API namespace

* Fix the array_api Array.__repr__ to indent the array properly

* Make the Device type in the array_api just accept the string "cpu"

1 files changed, 29 insertions, 1 deletions

diff --git a/numpy/array_api/_creation_functions.py b/numpy/array_api/_creation_functions.py
index e9c01e7e6..9f8136267 100644
--- a/numpy/array_api/_creation_functions.py
+++ b/numpy/array_api/_creation_functions.py
@@ -22,7 +22,7 @@ def _check_valid_dtype(dtype):
     # Note: Only spelling dtypes as the dtype objects is supported.
 
     # We use this instead of "dtype in _all_dtypes" because the dtype objects
-    # define equality with the sorts of things we want to disallw.
+    # define equality with the sorts of things we want to disallow.
     for d in (None,) + _all_dtypes:
         if dtype is d:
             return
@@ -281,6 +281,34 @@ def ones_like(
     return Array._new(np.ones_like(x._array, dtype=dtype))
 
 
+def tril(x: Array, /, *, k: int = 0) -> Array:
+    """
+    Array API compatible wrapper for :py:func:`np.tril <numpy.tril>`.
+
+    See its docstring for more information.
+    """
+    from ._array_object import Array
+
+    if x.ndim < 2:
+        # Note: Unlike np.tril, x must be at least 2-D
+        raise ValueError("x must be at least 2-dimensional for tril")
+    return Array._new(np.tril(x._array, k=k))
+
+
+def triu(x: Array, /, *, k: int = 0) -> Array:
+    """
+    Array API compatible wrapper for :py:func:`np.triu <numpy.triu>`.
+
+    See its docstring for more information.
+    """
+    from ._array_object import Array
+
+    if x.ndim < 2:
+        # Note: Unlike np.triu, x must be at least 2-D
+        raise ValueError("x must be at least 2-dimensional for triu")
+    return Array._new(np.triu(x._array, k=k))
+
+
 def zeros(
     shape: Union[int, Tuple[int, ...]],
     *,