Reinstate explicit bool | complex

Author: crusaderky

array_api_compat/cupy/_aliases.py

@@ -64,9 +64,12 @@
 
 _copy_default = object()
 
+
 # asarray also adds the copy keyword, which is not present in numpy 1.0.
 def asarray(
-    obj: Array | complex | NestedSequence[complex] | SupportsBufferProtocol,
+    obj: (
+        Array | bool | complex | NestedSequence[bool | complex] | SupportsBufferProtocol
+    ),
     /,
     *,
     dtype: Optional[DType] = None,

array_api_compat/dask/array/_aliases.py

@@ -135,7 +135,9 @@ def arange(
 
 # asarray also adds the copy keyword, which is not present in numpy 1.0.
 def asarray(
-    obj: Array | complex | NestedSequence[complex] | SupportsBufferProtocol,
+    obj: (
+        Array | bool | complex | NestedSequence[bool | complex] | SupportsBufferProtocol
+    ),
     /,
     *,
     dtype: Optional[DType] = None,

array_api_compat/numpy/_aliases.py

@@ -9,6 +9,7 @@
 from ._typing import Array, Device, DType
 
 import numpy as np
+
 bool = np.bool_
 
 # Basic renames
@@ -61,19 +62,23 @@
 tensordot = get_xp(np)(_aliases.tensordot)
 sign = get_xp(np)(_aliases.sign)
 
+
 def _supports_buffer_protocol(obj):
     try:
         memoryview(obj)
     except TypeError:
         return False
     return True
 
+
 # asarray also adds the copy keyword, which is not present in numpy 1.0.
 # asarray() is different enough between numpy, cupy, and dask, the logic
 # complicated enough that it's easier to define it separately for each module
 # rather than trying to combine everything into one function in common/
 def asarray(
-    obj: Array | complex | NestedSequence[complex] | SupportsBufferProtocol,
+    obj: (
+        Array | bool | complex | NestedSequence[bool | complex] | SupportsBufferProtocol
+    ),
     /,
     *,
     dtype: Optional[DType] = None,
@@ -119,11 +124,7 @@ def astype(
 
 # count_nonzero returns a python int for axis=None and keepdims=False
 # https://github.com/numpy/numpy/issues/17562
-def count_nonzero(
-    x : Array,
-    axis=None,
-    keepdims=False
-) -> Array:
+def count_nonzero(x: Array, axis=None, keepdims=False) -> Array:
     result = np.count_nonzero(x, axis=axis, keepdims=keepdims)
     if axis is None and not keepdims:
         return np.asarray(result)