Merge master into impl_of_interp

Author: vlad-perevezentsev

.github/workflows/array-api-skips.txt

@@ -6,9 +6,3 @@ array_api_tests/test_operators_and_elementwise_functions.py::test_clip
 # unexpected result is returned - unmute when dpctl-1986 is resolved
 array_api_tests/test_operators_and_elementwise_functions.py::test_asin
 array_api_tests/test_operators_and_elementwise_functions.py::test_asinh
-
-# advanced indexing relating issues (waiting a fix from dpctl)
-array_api_tests/test_array_object.py::test_getitem_arrays_and_ints_1[1]
-array_api_tests/test_array_object.py::test_getitem_arrays_and_ints_1[None]
-array_api_tests/test_array_object.py::test_getitem_arrays_and_ints_2[1]
-array_api_tests/test_array_object.py::test_getitem_arrays_and_ints_2[None]

.github/workflows/build-sphinx.yml

@@ -42,6 +42,7 @@ jobs:
       oneapi-pkgs-env: ''
       # Enable env when it's required to use only conda packages without OneAPI installation
       # oneapi-pkgs-env: '${{ github.workspace }}/environments/oneapi_pkgs.yml'
+      dpctl-pkg-txt: 'environments/dpctl_pkg.txt'
 
     steps:
       - name: Cancel Previous Runs
@@ -149,7 +150,7 @@ jobs:
       - name: Install dpctl
         if: env.oneapi-pkgs-env == ''
         run: |
-          pip install -i https://pypi.anaconda.org/dppy/label/dev/simple dpctl==0.20.0dev0
+          pip install -r ${{ env.dpctl-pkg-txt }}
 
       - name: Conda info
         run: |

.github/workflows/conda-package.yml

@@ -82,6 +82,9 @@ jobs:
           environment-file: ${{ env.build-conda-pkg-env }}
           activate-environment: ${{ env.build-env-name }}
 
+      - name: List installed packages
+        run: mamba list
+
       - name: Store conda paths as envs
         shell: bash -el {0}
         run: |

.github/workflows/generate_coverage.yaml

@@ -26,6 +26,7 @@ jobs:
       oneapi-pkgs-env: ''
       # Enable env when it's required to use only conda packages without OneAPI installation
       # oneapi-pkgs-env: '${{ github.workspace }}/environments/oneapi_pkgs.yml'
+      dpctl-pkg-txt: 'environments/dpctl_pkg.txt'
 
     steps:
       - name: Cancel Previous Runs
@@ -108,7 +109,7 @@ jobs:
       - name: Install dpctl
         if: env.oneapi-pkgs-env == ''
         run: |
-          pip install -i https://pypi.anaconda.org/dppy/label/dev/simple dpctl==0.20.0dev0
+          pip install -r ${{ env.dpctl-pkg-txt }}
 
       - name: Conda info
         run: |

CHANGELOG.md

@@ -22,6 +22,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 * The vector norms `ord={None, 1, 2, inf}` and the matrix norms `ord={None, 1, 2, inf, "fro", "nuc"}` now consistently return zero for empty arrays, which are arrays with at least one axis of size zero. This change affects `dpnp.linalg.norm`, `dpnp.linalg.vector_norm`, and `dpnp.linalg.matrix_norm`. Previously, dpnp would either raise errors or return zero depending on the parameters provided [#2371](https://github.com/IntelPython/dpnp/pull/2371)
 * Extended `dpnp.fft.fftfreq` and `dpnp.fft.rfftfreq` functions to support `dtype` keyword per Python Array API spec 2024.12 [#2384](https://github.com/IntelPython/dpnp/pull/2384)
 * Updated `dpnp.fix` to return output with the same data-type of input [#2392](https://github.com/IntelPython/dpnp/pull/2392)
+* Updated `dpnp.einsum` to add support for `order=None` [#2411](https://github.com/IntelPython/dpnp/pull/2411)
 
 ### Fixed
 

conda-recipe/meta.yaml

@@ -1,6 +1,6 @@
 {% set max_compiler_and_mkl_version = environ.get("MAX_BUILD_CMPL_MKL_VERSION", "2026.0a0") %}
 {% set required_compiler_and_mkl_version = "2025.0" %}
-{% set required_dpctl_version = "0.19.0*" %}
+{% set required_dpctl_version = "0.20.0*" %}
 
 package:
     name: dpnp

dpnp/dpnp_iface_linearalgebra.py

@@ -215,12 +215,13 @@ def einsum(
         If provided, forces the calculation to use the data type specified.
 
         Default: ``None``.
-    order : {"C", "F", "A", "K"}, optional
+    order : {None, "C", "F", "A", "K"}, optional
         Controls the memory layout of the output. ``"C"`` means it should be
         C-contiguous. ``"F"`` means it should be F-contiguous, ``"A"`` means
         it should be ``"F"`` if the inputs are all ``"F"``, ``"C"`` otherwise.
         ``"K"`` means it should be as close to the layout as the inputs as
-        is possible, including arbitrarily permuted axes.
+        is possible, including arbitrarily permuted axes. ``order=None`` is
+        equivalent to ``order="K"``.
 
         Default: ``"K"``.
     casting : {"no", "equiv", "safe", "same_kind", "unsafe"}, optional

dpnp/dpnp_iface_mathematical.py

@@ -612,7 +612,7 @@ def around(x, /, decimals=0, out=None):
 Parameters
 ----------
 x : {dpnp.ndarray, usm_ndarray}
-    Input array, expected to have a real-valued data type.
+    Input array, expected to have a boolean or real-valued data type.
 out : {None, dpnp.ndarray, usm_ndarray}, optional
     Output array to populate.
     Array must have the correct shape and the expected data type.
@@ -792,6 +792,7 @@ def clip(a, /, min=None, max=None, *, out=None, order="K", **kwargs):
 
 conj = conjugate
 
+
 _COPYSIGN_DOCSTRING = """
 Composes a floating-point value with the magnitude of `x1_i` and the sign of
 `x2_i` for each element of input arrays `x1` and `x2`.
@@ -1718,7 +1719,7 @@ def ediff1d(ary, to_end=None, to_begin=None):
 Parameters
 ----------
 x : {dpnp.ndarray, usm_ndarray}
-    Input array, expected to have a real-valued data type.
+    Input array, expected to have a boolean or real-valued data type.
 out : {None, dpnp.ndarray, usm_ndarray}, optional
     Output array to populate.
     Array must have the correct shape and the expected data type.
@@ -1879,7 +1880,7 @@ def ediff1d(ary, to_end=None, to_begin=None):
 Parameters
 ----------
 x : {dpnp.ndarray, usm_ndarray}
-    Input array, expected to have a real-valued data type.
+    Input array, expected to have a boolean or real-valued data type.
 out : {None, dpnp.ndarray, usm_ndarray}, optional
     Output array to populate.
     Array must have the correct shape and the expected data type.
@@ -4731,7 +4732,7 @@ def trapezoid(y, x=None, dx=1.0, axis=-1):
 Parameters
 ----------
 x : {dpnp.ndarray, usm_ndarray}
-    Input array, expected to have a real-valued data type.
+    Input array, expected to have a boolean or real-valued data type.
 out : {None, dpnp.ndarray, usm_ndarray}, optional
     Output array to populate.
     Array must have the correct shape and the expected data type.

dpnp/dpnp_utils/dpnp_utils_einsum.py

@@ -1034,7 +1034,7 @@ def dpnp_einsum(
             )
             arrays.append(operands[id])
     result_dtype = dpnp.result_type(*arrays) if dtype is None else dtype
-    if order in "aA":
+    if order is not None and order in "aA":
         order = "F" if all(arr.flags.fnc for arr in arrays) else "C"
 
     input_subscripts = [

dpnp/tests/test_linalg.py

@@ -1647,6 +1647,10 @@ def test_output_order(self):
             assert tmp.flags.c_contiguous is False
             assert tmp.flags.f_contiguous is False
 
+            tmp = dpnp.einsum("...ft,mf->...mt", a, b, order=None, optimize=opt)
+            assert tmp.flags.c_contiguous is False
+            assert tmp.flags.f_contiguous is False
+
             tmp = dpnp.einsum("...ft,mf->...mt", a, b, optimize=opt)
             assert tmp.flags.c_contiguous is False
             assert tmp.flags.f_contiguous is False

dpnp/tests/test_mathematical.py

@@ -2315,20 +2315,11 @@ def test_out(self, func, dt_in, dt_out):
         if dt_in != dt_out:
             if numpy.can_cast(dt_in, dt_out, casting="same_kind"):
                 # NumPy allows "same_kind" casting, dpnp does not
-                if func != "fix" and dt_in == dpnp.bool and dt_out == dpnp.int8:
-                    # TODO: get rid of w/a when dpctl#2030 is fixed
-                    pass
-                else:
-                    assert_raises(ValueError, getattr(dpnp, func), ia, out=iout)
+                assert_raises(ValueError, getattr(dpnp, func), ia, out=iout)
             else:
                 assert_raises(ValueError, getattr(dpnp, func), ia, out=iout)
                 assert_raises(TypeError, getattr(numpy, func), a, out=out)
         else:
-            if func != "fix" and dt_in == dpnp.bool:
-                # TODO: get rid of w/a when dpctl#2030 is fixed
-                out = out.astype(numpy.int8)
-                iout = iout.astype(dpnp.int8)
-
             expected = getattr(numpy, func)(a, out=out)
             result = getattr(dpnp, func)(ia, out=iout)
             assert result is iout
@@ -2354,11 +2345,6 @@ def test_out_usm_ndarray(self, func, dt):
         out = numpy.empty(a.shape, dtype=dt)
         ia, usm_out = dpnp.array(a), dpt.asarray(out)
 
-        if func != "fix" and dt == dpnp.bool:
-            # TODO: get rid of w/a when dpctl#2030 is fixed
-            out = out.astype(numpy.int8)
-            usm_out = dpt.asarray(usm_out, dtype=dpnp.int8)
-
         expected = getattr(numpy, func)(a, out=out)
         result = getattr(dpnp, func)(ia, out=usm_out)
         assert result.get_array() is usm_out

dpnp/tests/test_umath.py

@@ -108,8 +108,6 @@ def test_umaths(test_cases):
         and is_gpu_device()
     ):
         pytest.skip("dpctl-1652")
-    elif umath in ["ceil", "floor", "trunc"] and args[0].dtype == dpnp.bool:
-        pytest.skip("dpctl-2030")
     elif (
         umath == "tan"
         and dpnp.issubdtype(args[0].dtype, dpnp.complexfloating)

dpnp/tests/third_party/cupy/core_tests/test_ndarray_adv_indexing.py

@@ -609,14 +609,22 @@ def test_invalid_adv_getitem(self):
     },
     {"shape": (2, 3, 4), "indexes": (slice(None), []), "value": 1},
     {"shape": (2, 3, 4), "indexes": ([], []), "value": 1},
-    # {'shape': (2, 3, 4), 'indexes': numpy.array([], dtype=numpy.bool_),
-    #  'value': 1},  #dpctl-1913
-    # {'shape': (2, 3, 4),
-    #  'indexes': (slice(None), numpy.array([], dtype=numpy.bool_)),
-    #  'value': 1},  #dpctl-1913
-    # {'shape': (2, 3, 4), 'indexes': numpy.array([[], []], dtype=numpy.bool_),
-    #  'value': numpy.random.uniform(size=(4,))},  #dpctl-1913
-    # {'shape': (2, 3, 4), 'indexes': numpy.empty((0, 0, 4), bool), 'value': 1},  #dpctl-1913
+    {
+        "shape": (2, 3, 4),
+        "indexes": numpy.array([], dtype=numpy.bool_),
+        "value": 1,
+    },
+    {
+        "shape": (2, 3, 4),
+        "indexes": (slice(None), numpy.array([], dtype=numpy.bool_)),
+        "value": 1,
+    },
+    {
+        "shape": (2, 3, 4),
+        "indexes": numpy.array([[], []], dtype=numpy.bool_),
+        "value": numpy.random.uniform(size=(4,)),
+    },
+    {"shape": (2, 3, 4), "indexes": numpy.empty((0, 0, 4), bool), "value": 1},
     # multiple masks
     {"shape": (2, 3, 4), "indexes": (True, [True, False]), "value": 1},
     {"shape": (2, 3, 4), "indexes": (False, [True, False]), "value": 1},

environments/build_conda_pkg.yml

@@ -3,4 +3,4 @@ channels:
   - conda-forge
 dependencies:
   - python=3.12 # conda-build does not support python 3.13
-  - conda-build=25.3.1
+  - conda-build=25.3.2

environments/dpctl_pkg.txt

@@ -0,0 +1,2 @@
+--index-url https://pypi.anaconda.org/dppy/label/dev/simple
+dpctl>=0.20.0dev0

setup.py

@@ -84,5 +84,5 @@ def _get_cmdclass():
     },
     include_package_data=False,
     python_requires=">=3.9,<3.14",
-    install_requires=["dpctl >= 0.19.0dev0", "numpy"],
+    install_requires=["dpctl >= 0.20.0dev0", "numpy"],
 )