Merge pull request #21995 from eirrgang/mei-1468

BUG: Distinguish exact vs. equivalent dtype for C type aliases.

Original NumPy Commit: 65c10c1cfecb2b3ebd0306ed1c63b103158f80d5

Author: mattip

array_api_strict/tests/test_asarray.py

@@ -0,0 +1,64 @@
+import itertools
+
+import numpy as np
+
+
+def test_dtype_identity():
+    """Confirm the intended behavior for ``asarray`` results.
+
+    The result of ``asarray()`` should have the dtype provided through the
+    keyword argument, when used. This forces unique array handles to be
+    produced for unique np.dtype objects, but (for equivalent dtypes), the
+    underlying data (the base object) is shared with the original array object.
+
+    Ref https://github.com/numpy/numpy/issues/1468
+    """
+    int_array = np.array([1, 2, 3], dtype='i')
+    assert np.asarray(int_array) is int_array
+
+    # The character code resolves to the singleton dtype object provided
+    # by the numpy package.
+    assert np.asarray(int_array, dtype='i') is int_array
+
+    # Derive a dtype from n.dtype('i'), but add a metadata object to force
+    # the dtype to be distinct.
+    unequal_type = np.dtype('i', metadata={'spam': True})
+    annotated_int_array = np.asarray(int_array, dtype=unequal_type)
+    assert annotated_int_array is not int_array
+    assert annotated_int_array.base is int_array
+    # Create an equivalent descriptor with a new and distinct dtype instance.
+    equivalent_requirement = np.dtype('i', metadata={'spam': True})
+    annotated_int_array_alt = np.asarray(annotated_int_array,
+                                         dtype=equivalent_requirement)
+    assert unequal_type == equivalent_requirement
+    assert unequal_type is not equivalent_requirement
+    assert annotated_int_array_alt is not annotated_int_array
+    assert annotated_int_array_alt.dtype is equivalent_requirement
+
+    # Check the same logic for a pair of C types whose equivalence may vary
+    # between computing environments.
+    # Find an equivalent pair.
+    integer_type_codes = ('i', 'l', 'q')
+    integer_dtypes = [np.dtype(code) for code in integer_type_codes]
+    typeA = None
+    typeB = None
+    for typeA, typeB in itertools.permutations(integer_dtypes, r=2):
+        if typeA == typeB:
+            assert typeA is not typeB
+            break
+    assert isinstance(typeA, np.dtype) and isinstance(typeB, np.dtype)
+
+    # These ``asarray()`` calls may produce a new view or a copy,
+    # but never the same object.
+    long_int_array = np.asarray(int_array, dtype='l')
+    long_long_int_array = np.asarray(int_array, dtype='q')
+    assert long_int_array is not int_array
+    assert long_long_int_array is not int_array
+    assert np.asarray(long_int_array, dtype='q') is not long_int_array
+    array_a = np.asarray(int_array, dtype=typeA)
+    assert typeA == typeB
+    assert typeA is not typeB
+    assert array_a.dtype is typeA
+    assert array_a is not np.asarray(array_a, dtype=typeB)
+    assert np.asarray(array_a, dtype=typeB).dtype is typeB
+    assert array_a is np.asarray(array_a, dtype=typeB).base