implement dpnp.median

dpnp/dpnp_iface.py

@@ -61,7 +61,6 @@
     "as_usm_ndarray",
     "check_limitations",
     "check_supported_arrays_type",
-    "convert_single_elem_array_to_scalar",
     "default_float_type",
     "from_dlpack",
     "get_dpnp_descriptor",
@@ -407,15 +406,6 @@ def check_supported_arrays_type(*arrays, scalar_type=False, all_scalars=False):
     return True
 
 
-def convert_single_elem_array_to_scalar(obj, keepdims=False):
-    """Convert array with single element to scalar."""
-
-    if (obj.ndim > 0) and (obj.size == 1) and (keepdims is False):
-        return obj.dtype.type(obj[0])
-
-    return obj
-
-
 def default_float_type(device=None, sycl_queue=None):
     """
     Return a floating type used by default in DPNP depending on device

dpnp/dpnp_iface_sorting.py

@@ -70,10 +70,6 @@ def _wrap_sort_argsort(
         raise NotImplementedError(
             "kind keyword argument can only be None or 'stable'."
         )
-    if stable is None or not stable:
-        raise NotImplementedError(
-            "stable keyword argument is only supported with its default value."
-        )
 
     usm_a = dpnp.get_usm_ndarray(a)
     if axis is None:
@@ -101,6 +97,12 @@ def argsort(a, axis=-1, kind=None, order=None, *, stable=True):
     kind : {None, "stable"}, optional
         Sorting algorithm. Default is ``None``, which is equivalent to
          ``"stable"``. Unlike NumPy, no other option is accepted here.
+    stable : {None, bool}, optional
+        Sort stability. If ``True``, the returned array will maintain
+        the relative order of ``a`` values which compare as equal.
+        The same behavior applies when set to ``False`` or ``None``.
+        Internally, this option selects ``kind="stable"``.
+        Default: ``None``.
 
     Returns
     -------
@@ -118,9 +120,10 @@ def argsort(a, axis=-1, kind=None, order=None, *, stable=True):
 
     Limitations
     -----------
-    Parameters `order` and `stable` are only supported with their default
-    values. Parameter `kind` can only be ``None`` or ``"stable"`` which are
-    equivalent. Otherwise ``NotImplementedError`` exception will be raised.
+    Parameters `order` is only supported with its default value.
+    Parameter `kind` can only be ``None`` or ``"stable"`` which are equivalent.
+    Otherwise ``NotImplementedError`` exception will be raised.
+
     See Also
     --------
     :obj:`dpnp.ndarray.argsort` : Equivalent method.
@@ -216,6 +219,12 @@ def sort(a, axis=-1, kind=None, order=None, *, stable=True):
     kind : {None, "stable"}, optional
         Sorting algorithm. Default is ``None``, which is equivalent to
         ``"stable"``. Unlike NumPy, no other option is accepted here.
+    stable : {None, bool}, optional
+        Sort stability. If ``True``, the returned array will maintain
+        the relative order of ``a`` values which compare as equal.
+        The same behavior applies when set to ``False`` or ``None``.
+        Internally, this option selects ``kind="stable"``.
+        Default: ``None``.
 
     Returns
     -------
@@ -229,9 +238,9 @@ def sort(a, axis=-1, kind=None, order=None, *, stable=True):
 
     Limitations
     -----------
-    Parameters `order` and `stable` are only supported with their default
-    values. Parameter `kind` can only be ``None`` or ``"stable"`` which are
-    equivalent. Otherwise ``NotImplementedError`` exception will be raised.
+    Parameters `order` is only supported with its default value.
+    Parameter `kind` can only be ``None`` or ``"stable"`` which are equivalent.
+    Otherwise ``NotImplementedError`` exception will be raised.
 
     See Also
     --------

dpnp/dpnp_iface_statistics.py

@@ -668,8 +668,8 @@ def median(a, axis=None, out=None, overwrite_input=False, keepdims=False):
     overwrite_input : bool, optional
        If ``True``, then allow use of memory of input array `a` for
        calculations. The input array will be modified by the call to
-       ``median``. This will save memory when you do not need to preserve
-       the contents of the input array. Treat the input as undefined,
+      :obj:`dpnp.median`. This will save memory when you do not need to
+       preserve the contents of the input array. Treat the input as undefined,
        but it will probably be fully or partially sorted.
        Default: ``False``.
     keepdims : {None, bool}, optional
@@ -711,18 +711,21 @@ def median(a, axis=None, out=None, overwrite_input=False, keepdims=False):
            [ 3,  2,  1]])
     >>> np.median(a)
     array(3.5)
+
     >>> np.median(a, axis=0)
     array([6.5, 4.5, 2.5])
     >>> np.median(a, axis=1)
     array([7.,  2.])
     >>> np.median(a, axis=(0, 1))
     array(3.5)
+
     >>> m = np.median(a, axis=0)
     >>> out = np.zeros_like(m)
     >>> np.median(a, axis=0, out=m)
     array([6.5,  4.5,  2.5])
     >>> m
     array([6.5,  4.5,  2.5])
+
     >>> b = a.copy()
     >>> np.median(b, axis=1, overwrite_input=True)
     array([7.,  2.])

tests/test_mathematical.py

@@ -2470,7 +2470,7 @@ def test_out(self, func_params, dtype):
         # numpy.ceil, numpy.floor, numpy.trunc always return float dtype for
         # NumPy < 2.0.0 while output has the dtype of input for NumPy >= 2.0.0
         # (dpnp follows the latter behavior except for boolean dtype where it
-        # return int8)
+        # returns int8)
         if (
             numpy.lib.NumpyVersion(numpy.__version__) < "2.0.0"
             or dtype == numpy.bool