feat: add count_nonzero to specification

spec/draft/API_specification/searching_functions.rst

@@ -22,6 +22,7 @@ Objects in API
 
    argmax
    argmin
+   count_nonzero
    nonzero
    searchsorted
    where

src/array_api_stubs/_draft/searching_functions.py

@@ -1,7 +1,7 @@
-__all__ = ["argmax", "argmin", "nonzero", "searchsorted", "where"]
+__all__ = ["argmax", "argmin", "count_nonzero", "nonzero", "searchsorted", "where"]
 
 
-from ._types import Optional, Tuple, Literal, array
+from ._types import Optional, Tuple, Literal, Union, array
 
 
 def argmax(x: array, /, *, axis: Optional[int] = None, keepdims: bool = False) -> array:
@@ -54,15 +54,41 @@ def argmin(x: array, /, *, axis: Optional[int] = None, keepdims: bool = False) -
     """
 
 
-def nonzero(x: array, /) -> Tuple[array, ...]:
+def count_nonzero(
+    x: array,
+    /,
+    *,
+    axis: Optional[Union[int, Tuple[int, ...]]] = None,
+    keepdims: bool = False,
+) -> array:
     """
-    Returns the indices of the array elements which are non-zero.
+    Counts the number of array elements which are non-zero.
 
-    .. note::
-       If ``x`` has a complex floating-point data type, non-zero elements are those elements having at least one component (real or imaginary) which is non-zero.
+    Parameters
+    ----------
+    x: array
+        input array. Must have a positive rank. If ``x`` is zero-dimensional, the function must raise an exception.
+    axis: Optional[Union[int, Tuple[int, ...]]]
+        axis or axes along which to count non-zero values. By default, the number of non-zero values must be computed over the entire array. If a tuple of integers, the number of non-zero values must be computed over multiple axes. Default: ``None``.
+    keepdims: bool
+        if ``True``, the reduced axes (dimensions) must be included in the result as singleton dimensions, and, accordingly, the result must be compatible with the input array (see :ref:`broadcasting`). Otherwise, if ``False``, the reduced axes (dimensions) must not be included in the result. Default: ``False``.
 
-    .. note::
-       If ``x`` has a boolean data type, non-zero elements are those elements which are equal to ``True``.
+    Returns
+    -------
+    out: array
+        if the number of non-zeros values was computed over the entire array, a zero-dimensional array containing the total number of non-zero values; otherwise, a non-zero-dimensional array containing the counts along the specified axes. The returned array must have the default array index data type.
+
+    Notes
+    -----
+
+    -   If ``x`` has a complex floating-point data type, non-zero elements are those elements having at least one component (real or imaginary) which is non-zero.
+    -   If ``x`` has a boolean data type, non-zero elements are those elements which are equal to ``True``.
+    """
+
+
+def nonzero(x: array, /) -> Tuple[array, ...]:
+    """
+    Returns the indices of the array elements which are non-zero.
 
     .. admonition:: Data-dependent output shape
        :class: admonition important
@@ -76,12 +102,15 @@ def nonzero(x: array, /) -> Tuple[array, ...]:
 
     Returns
     -------
-    out: Typle[array, ...]
+    out: Tuple[array, ...]
         a tuple of ``k`` arrays, one for each dimension of ``x`` and each of size ``n`` (where ``n`` is the total number of non-zero elements), containing the indices of the non-zero elements in that dimension. The indices must be returned in row-major, C-style order. The returned array must have the default array index data type.
 
     Notes
     -----
 
+    -   If ``x`` has a complex floating-point data type, non-zero elements are those elements having at least one component (real or imaginary) which is non-zero.
+    -   If ``x`` has a boolean data type, non-zero elements are those elements which are equal to ``True``.
+
     .. versionchanged:: 2022.12
        Added complex data type support.
     """