Some fixes for v2022.12

array_api_tests/dtype_helpers.py

@@ -157,19 +157,18 @@ def is_int_dtype(dtype):
     return dtype in all_int_dtypes
 
 
-def is_float_dtype(dtype):
+def is_float_dtype(dtype, *, include_complex=True):
     # None equals NumPy's xp.float64 object, so we specifically check it here.
     # xp.float64 is in fact an alias of np.dtype('float64'), and its equality
     # with None is meant to be deprecated at some point.
     # See https://github.com/numpy/numpy/issues/18434
     if dtype is None:
         return False
     valid_dtypes = real_float_dtypes
-    if api_version > "2021.12":
+    if api_version > "2021.12" and include_complex:
         valid_dtypes += complex_dtypes
     return dtype in valid_dtypes
 
-
 def get_scalar_type(dtype: DataType) -> ScalarType:
     if dtype in all_int_dtypes:
         return int

array_api_tests/pytest_helpers.py

@@ -464,8 +464,8 @@ def assert_array_elements(
                 f"{sh.fmt_idx(out_repr, idx)}={at_out}, should be {at_expected} "
                 f"{f_func}"
             )
-            _assert_float_element(at_out.real, at_expected.real, msg)
-            _assert_float_element(at_out.imag, at_expected.imag, msg)
+            _assert_float_element(xp.real(at_out), xp.real(at_expected), msg)
+            _assert_float_element(xp.imag(at_out), xp.imag(at_expected), msg)
     else:
         assert xp.all(
             out == expected

array_api_tests/test_data_type_functions.py

@@ -162,6 +162,7 @@ def test_finfo(dtype_name):
         assert isinstance(
             value, stype
         ), f"type(out.{attr})={type(value)!r}, but should be {stype.__name__} {f_func}"
+    assert hasattr(out, "dtype"), f"out has no attribute 'dtype' {f_func}"
     # TODO: test values
 
 
@@ -179,6 +180,7 @@ def test_iinfo(dtype_name):
         assert isinstance(
             value, int
         ), f"type(out.{attr})={type(value)!r}, but should be int {f_func}"
+    assert hasattr(out, "dtype"), f"out has no attribute 'dtype' {f_func}"
     # TODO: test values
 
 

array_api_tests/test_indexing_functions.py

@@ -49,7 +49,7 @@ def test_take(x, data):
         f_axis_idx = sh.fmt_idx("x", axis_idx)
         for i in _indices:
             f_take_idx = sh.fmt_idx(f_axis_idx, i)
-            indexed_x = x[axis_idx][i]
+            indexed_x = x[axis_idx][i, ...]
             for at_idx in sh.ndindex(indexed_x.shape):
                 out_idx = next(out_indices)
                 ph.assert_0d_equals(

array_api_tests/test_set_functions.py

@@ -112,7 +112,7 @@ def test_unique_all(x):
 
     if dh.is_float_dtype(out.values.dtype):
         assume(math.prod(x.shape) <= 128)  # may not be representable
-        expected = sum(v for k, v in counts.items() if math.isnan(k))
+        expected = sum(v for k, v in counts.items() if cmath.isnan(k))
         assert nans == expected, f"{nans} NaNs in out, but should be {expected}"
 
 
@@ -137,7 +137,7 @@ def test_unique_counts(x):
     for idx in sh.ndindex(out.values.shape):
         val = scalar_type(out.values[idx])
         count = int(out.counts[idx])
-        if math.isnan(val):
+        if cmath.isnan(val):
             nans += 1
             assert count == 1, (
                 f"out.counts[{idx}]={count} for out.values[{idx}]={val}, "
@@ -159,7 +159,7 @@ def test_unique_counts(x):
             vals_idx[val] = idx
     if dh.is_float_dtype(out.values.dtype):
         assume(math.prod(x.shape) <= 128)  # may not be representable
-        expected = sum(v for k, v in counts.items() if math.isnan(k))
+        expected = sum(v for k, v in counts.items() if cmath.isnan(k))
         assert nans == expected, f"{nans} NaNs in out, but should be {expected}"
 
 
@@ -188,7 +188,7 @@ def test_unique_inverse(x):
     nans = 0
     for idx in sh.ndindex(out.values.shape):
         val = scalar_type(out.values[idx])
-        if math.isnan(val):
+        if cmath.isnan(val):
             nans += 1
         else:
             assert (

array_api_tests/test_statistical_functions.py

@@ -11,7 +11,7 @@
 from . import hypothesis_helpers as hh
 from . import pytest_helpers as ph
 from . import shape_helpers as sh
-from . import xps
+from . import xps, api_version
 from ._array_module import _UndefinedStub
 from .typing import DataType
 
@@ -145,11 +145,19 @@ def test_prod(x, data):
                     _dtype = x.dtype
                 else:
                     _dtype = default_dtype
-        else:
+        elif dh.is_float_dtype(x.dtype, include_complex=False):
             if dh.dtype_nbits[x.dtype] > dh.dtype_nbits[dh.default_float]:
                 _dtype = x.dtype
             else:
                 _dtype = dh.default_float
+        elif api_version > "2021.12":
+            # Complex dtype
+            if dh.dtype_nbits[x.dtype] > dh.dtype_nbits[dh.default_complex]:
+                _dtype = x.dtype
+            else:
+                _dtype = dh.default_complex
+        else:
+            raise RuntimeError("Unexpected dtype. This indicates a bug in the test suite.")
     else:
         _dtype = dtype
     if _dtype is None:
@@ -253,11 +261,19 @@ def test_sum(x, data):
                     _dtype = x.dtype
                 else:
                     _dtype = default_dtype
-        else:
+        elif dh.is_float_dtype(x.dtype, include_complex=False):
             if dh.dtype_nbits[x.dtype] > dh.dtype_nbits[dh.default_float]:
                 _dtype = x.dtype
             else:
                 _dtype = dh.default_float
+        elif api_version > "2021.12":
+            # Complex dtype
+            if dh.dtype_nbits[x.dtype] > dh.dtype_nbits[dh.default_complex]:
+                _dtype = x.dtype
+            else:
+                _dtype = dh.default_complex
+        else:
+            raise RuntimeError("Unexpected dtype. This indicates a bug in the test suite.")
     else:
         _dtype = dtype
     if _dtype is None: