Merge pull request #119 from ev-br/result_type_scalars

Allow python scalars in `result_type`: 2024.12 revision

Author: ev-br

array_api_strict/_data_type_functions.py

@@ -197,7 +197,7 @@ def isdtype(
     else:
         raise TypeError(f"'kind' must be a dtype, str, or tuple of dtypes and strs, not {type(kind).__name__}")
 
-def result_type(*arrays_and_dtypes: Union[Array, Dtype]) -> Dtype:
+def result_type(*arrays_and_dtypes: Union[Array, Dtype, int, float, complex, bool]) -> Dtype:
     """
     Array API compatible wrapper for :py:func:`np.result_type <numpy.result_type>`.
 
@@ -208,19 +208,40 @@ def result_type(*arrays_and_dtypes: Union[Array, Dtype]) -> Dtype:
     # too many extra type promotions like int64 + uint64 -> float64, and does
     # value-based casting on scalar arrays.
     A = []
+    scalars = []
     for a in arrays_and_dtypes:
         if isinstance(a, Array):
             a = a.dtype
+        elif isinstance(a, (bool, int, float, complex)):
+            scalars.append(a)
         elif isinstance(a, np.ndarray) or a not in _all_dtypes:
             raise TypeError("result_type() inputs must be array_api arrays or dtypes")
         A.append(a)
 
+    # remove python scalars
+    A = [a for a in A if not isinstance(a, (bool, int, float, complex))]
+
     if len(A) == 0:
         raise ValueError("at least one array or dtype is required")
     elif len(A) == 1:
-        return A[0]
+        result = A[0]
     else:
         t = A[0]
         for t2 in A[1:]:
             t = _result_type(t, t2)
-        return t
+        result = t
+
+    if len(scalars) == 0:
+        return result
+
+    if get_array_api_strict_flags()['api_version'] <= '2023.12':
+        raise TypeError("result_type() inputs must be array_api arrays or dtypes")
+
+    # promote python scalars given the result_type for all arrays/dtypes
+    from ._creation_functions import empty
+    arr = empty(1, dtype=result)
+    for s in scalars:
+        x = arr._promote_scalar(s)
+        result = _result_type(x.dtype, result)
+
+    return result

array_api_strict/tests/test_data_type_functions.py

@@ -6,9 +6,9 @@
 import numpy as np
 
 from .._creation_functions import asarray
-from .._data_type_functions import astype, can_cast, isdtype
+from .._data_type_functions import astype, can_cast, isdtype, result_type
 from .._dtypes import (
-    bool, int8, int16, uint8, float64,
+    bool, int8, int16, uint8, float64, int64
 )
 from .._flags import set_array_api_strict_flags
 
@@ -70,3 +70,22 @@ def astype_device(api_version):
     else:
         pytest.raises(TypeError, lambda: astype(a, int8, device=None))
         pytest.raises(TypeError, lambda: astype(a, int8, device=a.device))
+
+
+@pytest.mark.parametrize("api_version", ['2023.12', '2024.12'])
+def test_result_type_py_scalars(api_version):
+    if api_version <= '2023.12':
+        set_array_api_strict_flags(api_version=api_version)
+
+        with pytest.raises(TypeError):
+            result_type(int16, 3)
+    else:
+        with pytest.warns(UserWarning):
+            set_array_api_strict_flags(api_version=api_version)
+
+            assert result_type(int8, 3) == int8
+            assert result_type(uint8, 3) == uint8
+            assert result_type(float64, 3) == float64
+
+            with pytest.raises(TypeError):
+                result_type(int64, True)

array_api_strict/tests/test_manipulation_functions.py

@@ -11,7 +11,7 @@
 
 
 def test_concat_errors():
-    assert_raises(TypeError, lambda: concat((1, 1), axis=None))
+    assert_raises((TypeError, ValueError), lambda: concat((1, 1), axis=None))
     assert_raises(TypeError, lambda: concat([asarray([1], dtype=int8),
                                              asarray([1], dtype=float64)]))
 

array_api_strict/tests/test_validation.py

@@ -18,7 +18,7 @@ def p(func: Callable, *args, **kwargs):
     [
         p(xp.can_cast, 42, xp.int8),
         p(xp.can_cast, xp.int8, 42),
-        p(xp.result_type, 42),
+        p(xp.result_type, "42"),
     ],
 )
 def test_raises_on_invalid_types(func, args, kwargs):