Fix array-api-tests job

.github/workflows/array-api-tests.yml

@@ -1,10 +1,12 @@
 name: Array API Tests
 
+on: [push, pull_request]
+
 env:
-  PYTEST_ARGS: "-v -rxXfE --ci"
+  PYTEST_ARGS: "-v -rxXfE --ci --hypothesis-disable-deadline"
 
 jobs:
-  tests:
+  array-api-tests:
     runs-on: ubuntu-latest
     strategy:
       matrix:
@@ -37,13 +39,14 @@ jobs:
         else
           python -m pip install 'numpy>=1.26,<2.0';
         fi
+        python -m pip install ${GITHUB_WORKSPACE}/array-api-strict
+        python -m pip install -r ${GITHUB_WORKSPACE}/array-api-tests/requirements.txt
     - name: Run the array API testsuite
       env:
         ARRAY_API_TESTS_MODULE: array_api_strict
         # This enables the NEP 50 type promotion behavior (without it a lot of
         # tests fail in numpy 1.26 on bad scalar type promotion behavior)
         NPY_PROMOTION_STATE: weak
       run: |
-        export PYTHONPATH="${GITHUB_WORKSPACE}/array-api-compat"
         cd ${GITHUB_WORKSPACE}/array-api-tests
-        pytest array_api_tests/ --xfails-file ${PYTEST_ARGS}
+        pytest array_api_tests/ --skips-file ${GITHUB_WORKSPACE}/array-api-strict/array-api-tests-xfails.txt ${PYTEST_ARGS}

array-api-tests-xfails.txt

@@ -0,0 +1,25 @@
+# copy=False is not yet implemented
+# https://github.com/numpy/numpy/pull/25168
+array_api_tests/test_creation_functions.py::test_asarray_arrays
+
+# Some fft tests are currently wrong
+# (https://github.com/data-apis/array-api-tests/issues/231)
+array_api_tests/test_fft.py::test_fft
+array_api_tests/test_fft.py::test_ifft
+array_api_tests/test_fft.py::test_fftn
+array_api_tests/test_fft.py::test_ifftn
+array_api_tests/test_fft.py::test_rfft
+array_api_tests/test_fft.py::test_irfft
+array_api_tests/test_fft.py::test_rfftn
+array_api_tests/test_fft.py::test_irfftn
+array_api_tests/test_fft.py::test_hfft
+array_api_tests/test_fft.py::test_ihfft
+
+# Known special case issue in NumPy. Not worth working around here
+# https://github.com/numpy/numpy/issues/21213
+array_api_tests/test_special_cases.py::test_iop[__ipow__(x1_i is -infinity and x2_i > 0 and not (x2_i.is_integer() and x2_i % 2 == 1)) -> +infinity]
+array_api_tests/test_special_cases.py::test_iop[__ipow__(x1_i is -0 and x2_i > 0 and not (x2_i.is_integer() and x2_i % 2 == 1)) -> +0]
+
+# The test suite is incorrectly checking sums that have loss of significance
+# (https://github.com/data-apis/array-api-tests/issues/168)
+array_api_tests/test_statistical_functions.py::test_sum

array_api_strict/_array_object.py

@@ -5,8 +5,8 @@
 particular, type promotion rules are different (the standard has no
 value-based casting). The standard also specifies a more limited subset of
 array methods and functionalities than are implemented on ndarray. Since the
-goal of the array_api namespace is to be a minimal implementation of the array
-API standard, we need to define a separate wrapper class for the array_api
+goal of the array_api_strict namespace is to be a minimal implementation of the array
+API standard, we need to define a separate wrapper class for the array_api_strict
 namespace.
 
 The standard compliant class is only a wrapper class. It is *not* a subclass
@@ -73,7 +73,7 @@ def _new(cls, x, /):
         This is a private method for initializing the array API Array
         object.
 
-        Functions outside of the array_api submodule should not use this
+        Functions outside of the array_api_strict module should not use this
         method. Use one of the creation functions instead, such as
         ``asarray``.
 
@@ -86,7 +86,7 @@ def _new(cls, x, /):
         _dtype = _DType(x.dtype)
         if _dtype not in _all_dtypes:
             raise TypeError(
-                f"The array_api namespace does not support the dtype '{x.dtype}'"
+                f"The array_api_strict namespace does not support the dtype '{x.dtype}'"
             )
         obj._array = x
         obj._dtype = _dtype
@@ -95,7 +95,7 @@ def _new(cls, x, /):
     # Prevent Array() from working
     def __new__(cls, *args, **kwargs):
         raise TypeError(
-            "The array_api Array object should not be instantiated directly. Use an array creation function, such as asarray(), instead."
+            "The array_api_strict Array object should not be instantiated directly. Use an array creation function, such as asarray(), instead."
         )
 
     # These functions are not required by the spec, but are implemented for
@@ -121,7 +121,7 @@ def __repr__(self: Array, /) -> str:
         return prefix + mid + suffix
 
     # This function is not required by the spec, but we implement it here for
-    # convenience so that np.asarray(np.array_api.Array) will work.
+    # convenience so that np.asarray(array_api_strict.Array) will work.
     def __array__(self, dtype: None | np.dtype[Any] = None) -> npt.NDArray[Any]:
         """
         Warning: this method is NOT part of the array API spec. Implementers
@@ -338,7 +338,7 @@ def _validate_index(self, key):
             if i is not None:
                 nonexpanding_key.append(i)
                 if isinstance(i, np.ndarray):
-                    raise IndexError("Index arrays for np.array_api must be np.array_api arrays")
+                    raise IndexError("Index arrays for array_api_strict must be array_api_strict arrays")
                 if isinstance(i, Array):
                     if i.dtype in _boolean_dtypes:
                         key_has_mask = True
@@ -471,7 +471,7 @@ def __array_namespace__(
         if api_version is not None and not api_version.startswith("2021."):
             raise ValueError(f"Unrecognized array API version: {api_version!r}")
         import array_api_strict
-        return array_api
+        return array_api_strict
 
     def __bool__(self: Array, /) -> bool:
         """
@@ -571,7 +571,7 @@ def __getitem__(
         # docstring of _validate_index
         self._validate_index(key)
         if isinstance(key, Array):
-            # Indexing self._array with array_api arrays can be erroneous
+            # Indexing self._array with array_api_strict arrays can be erroneous
             key = key._array
         res = self._array.__getitem__(key)
         return self._new(res)
@@ -761,7 +761,7 @@ def __setitem__(
         # docstring of _validate_index
         self._validate_index(key)
         if isinstance(key, Array):
-            # Indexing self._array with array_api arrays can be erroneous
+            # Indexing self._array with array_api_strict arrays can be erroneous
             key = key._array
         self._array.__setitem__(key, asarray(value)._array)
 

array_api_strict/_dtypes.py

@@ -11,7 +11,7 @@ def __init__(self, np_dtype):
         self._np_dtype = np_dtype
 
     def __repr__(self):
-        return f"np.array_api.{self._np_dtype.name}"
+        return f"array_api_strict.{self._np_dtype.name}"
 
     def __eq__(self, other):
         # See https://github.com/numpy/numpy/pull/25370/files#r1423259515.

array_api_strict/linalg.py

@@ -305,10 +305,16 @@ def slogdet(x: Array, /) -> SlogdetResult:
 # To workaround this, the below is the code from np.linalg.solve except
 # only calling solve1 in the exactly 1D case.
 def _solve(a, b):
-    from numpy.linalg._linalg import (
+    try:
+        from numpy.linalg._linalg import (
         _makearray, _assert_stacked_2d, _assert_stacked_square,
         _commonType, isComplexType, _raise_linalgerror_singular
-    )
+        )
+    except ImportError:
+        from numpy.linalg.linalg import (
+        _makearray, _assert_stacked_2d, _assert_stacked_square,
+        _commonType, isComplexType, _raise_linalgerror_singular
+        )
     from numpy.linalg import _umath_linalg
 
     a, _ = _makearray(a)