Merge branch 'master' into update-python-ver-in-docs

Author: antonwolfy

CHANGELOG.md

@@ -31,6 +31,9 @@ This release achieves 100% compliance with Python Array API specification (revis
 * Changed `"max dimensions"` to `None` in array API capabilities [#2432](https://github.com/IntelPython/dpnp/pull/2432)
 * Updated kernel header `i0.hpp` to expose `cyl_bessel_i0` function depending on build target [#2440](https://github.com/IntelPython/dpnp/pull/2440)
 * Added MKL functions `arg`, `copysign`, `i0`, and `inv` from VM namespace to be used by implementation of the appropriate element-wise functions [#2445](https://github.com/IntelPython/dpnp/pull/2445)
+* Clarified details about conda install instructions in `Quick start quide` and `README` [#2446](https://github.com/IntelPython/dpnp/pull/2446)
+* Bumped oneMKL version up to `0.7` [#2448](https://github.com/IntelPython/dpnp/pull/2448)
+* The parameter `axis` in `dpnp.take_along_axis` function has now a default value of `-1` [#2442](https://github.com/IntelPython/dpnp/pull/2442)
 * Updates the list of required python versions documented in `Quick Start Guide` [#2449](https://github.com/IntelPython/dpnp/pull/2449)
 
 ### Fixed

CMakeLists.txt

@@ -117,16 +117,16 @@ if(_use_onemkl_interfaces)
     endif()
 
     if(DPNP_ONEMKL_INTERFACES_DIR)
-        FetchContent_Declare(onemkl_interfaces_library SOURCE_DIR "${DPNP_ONEMKL_INTERFACES_DIR}")
+        FetchContent_Declare(onemath_library SOURCE_DIR "${DPNP_ONEMKL_INTERFACES_DIR}")
     else()
         FetchContent_Declare(
-                onemkl_interfaces_library
+            onemath_library
                 GIT_REPOSITORY https://github.com/uxlfoundation/oneMath.git
-                GIT_TAG 8f4312ef966420b9b8b4b82b9d5c22e2c91a1fe7  # v0.6
+                GIT_TAG 20ba6fd7ae4af6ed693246cfd22c343e6522edbe  # v0.7
         )
     endif()
 
-    FetchContent_MakeAvailable(onemkl_interfaces_library)
+    FetchContent_MakeAvailable(onemath_library)
     if(TARGET onemath)
         set(MKL_INTERFACES_LIB "onemath" CACHE INTERNAL "OneMath lib target")
     elseif(TARGET onemkl)

dpnp/dpnp_iface_indexing.py

@@ -2205,7 +2205,7 @@ def take(a, indices, /, *, axis=None, out=None, mode="wrap"):
     return dpnp.get_result_array(usm_res, out=out)
 
 
-def take_along_axis(a, indices, axis, mode="wrap"):
+def take_along_axis(a, indices, axis=-1, mode="wrap"):
     """
     Take values from the input array by matching 1d index and data slices.
 
@@ -2227,9 +2227,12 @@ def take_along_axis(a, indices, axis, mode="wrap"):
         dimension of the input array, but dimensions ``Ni`` and ``Nj``
         only need to broadcast against `a`.
     axis : {None, int}
-        The axis to take 1d slices along. If axis is ``None``, the input
-        array is treated as if it had first been flattened to 1d,
-        for consistency with :obj:`dpnp.sort` and :obj:`dpnp.argsort`.
+        The axis to take 1d slices along. If axis is ``None``, the input array
+        is treated as if it had first been flattened to 1d. The default is
+        ``-1``, which takes 1d slices along the last axis. These behaviors are
+        consistent with :obj:`dpnp.sort` and :obj:`dpnp.argsort`.
+
+        Default: ``-1``.
     mode : {"wrap", "clip"}, optional
         Specifies how out-of-bounds indices will be handled. Possible values
         are:
@@ -2274,8 +2277,8 @@ def take_along_axis(a, indices, axis, mode="wrap"):
     array([[10, 20, 30],
            [40, 50, 60]])
 
-    The same works for max and min, if you maintain the trivial dimension
-    with ``keepdims``:
+    The same works for :obj:`dpnp.max` and :obj:`dpnp.min`, if you maintain
+    the trivial dimension with ``keepdims``:
 
     >>> np.max(a, axis=1, keepdims=True)
     array([[30],

dpnp/tests/test_indexing.py

@@ -804,7 +804,7 @@ def test_argequivalent(self, func, argfunc, kwargs):
         # a = dpnp.random.random(size=(3, 4, 5))
         a = dpnp.asarray(numpy.random.random(size=(3, 4, 5)))
 
-        for axis in list(range(a.ndim)) + [None]:
+        for axis in list(range(a.ndim)) + [None, -1]:
             a_func = func(a, axis=axis, **kwargs)
             ai_func = argfunc(a, axis=axis, **kwargs)
             assert_array_equal(