Merge branch 'master' of github.com:numpy/numpy into einsum-dot

1 files changed, 13 insertions, 8 deletions

diff --git a/numpy/typing/_array_like.py b/numpy/typing/_array_like.py
index a1a604239..63b67b33a 100644
--- a/numpy/typing/_array_like.py
+++ b/numpy/typing/_array_like.py
@@ -1,7 +1,9 @@
+from __future__ import annotations
+
 import sys
-from typing import Any, overload, Sequence, TYPE_CHECKING, Union
+from typing import Any, overload, Sequence, TYPE_CHECKING, Union, TypeVar
 
-from numpy import ndarray
+from numpy import ndarray, dtype
 from ._scalars import _ScalarLike
 from ._dtype_like import DTypeLike
 
@@ -16,12 +18,15 @@ else:
     else:
         HAVE_PROTOCOL = True
 
+_DType = TypeVar("_DType", bound="dtype[Any]")
+
 if TYPE_CHECKING or HAVE_PROTOCOL:
-    class _SupportsArray(Protocol):
-        @overload
-        def __array__(self, __dtype: DTypeLike = ...) -> ndarray: ...
-        @overload
-        def __array__(self, dtype: DTypeLike = ...) -> ndarray: ...
+    # The `_SupportsArray` protocol only cares about the default dtype
+    # (i.e. `dtype=None`) of the to-be returned array.
+    # Concrete implementations of the protocol are responsible for adding
+    # any and all remaining overloads
+    class _SupportsArray(Protocol[_DType]):
+        def __array__(self, dtype: None = ...) -> ndarray[Any, _DType]: ...
 else:
     _SupportsArray = Any
 
@@ -36,5 +41,5 @@ ArrayLike = Union[
     _ScalarLike,
     Sequence[_ScalarLike],
     Sequence[Sequence[Any]],  # TODO: Wait for support for recursive types
-    _SupportsArray,
+    "_SupportsArray[Any]",
 ]