Merge branch 'numpy:main' into armcompiler

3 files changed, 36 insertions, 3 deletions

diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py
index 8794c5ea5..75baf34b0 100644
--- a/numpy/array_api/_array_object.py
+++ b/numpy/array_api/_array_object.py
@@ -33,6 +33,7 @@ from typing import TYPE_CHECKING, Optional, Tuple, Union, Any
 
 if TYPE_CHECKING:
     from ._typing import Any, PyCapsule, Device, Dtype
+    import numpy.typing as npt
 
 import numpy as np
 
@@ -108,6 +109,17 @@ class Array:
             mid = np.array2string(self._array, separator=', ', prefix=prefix, suffix=suffix)
         return prefix + mid + suffix
 
+    # This function is not required by the spec, but we implement it here for
+    # convenience so that np.asarray(np.array_api.Array) will work.
+    def __array__(self, dtype: None | np.dtype[Any] = None) -> npt.NDArray[Any]:
+        """
+        Warning: this method is NOT part of the array API spec. Implementers
+        of other libraries need not include it, and users should not assume it
+        will be present in other implementations.
+
+        """
+        return np.asarray(self._array, dtype=dtype)
+
     # These are various helper functions to make the array behavior match the
     # spec in places where it either deviates from or is more strict than
     # NumPy behavior
@@ -1072,4 +1084,4 @@ class Array:
         # https://data-apis.org/array-api/latest/API_specification/array_object.html#t
         if self.ndim != 2:
             raise ValueError("x.T requires x to have 2 dimensions. Use x.mT to transpose stacks of matrices and permute_dims() to permute dimensions.")
-        return self._array.T
+        return self.__class__._new(self._array.T)
diff --git a/numpy/array_api/_statistical_functions.py b/numpy/array_api/_statistical_functions.py
index 7bee3f4db..5bc831ac2 100644
--- a/numpy/array_api/_statistical_functions.py
+++ b/numpy/array_api/_statistical_functions.py
@@ -65,8 +65,8 @@ def prod(
     # Note: sum() and prod() always upcast float32 to float64 for dtype=None
     # We need to do so here before computing the product to avoid overflow
     if dtype is None and x.dtype == float32:
-        x = asarray(x, dtype=float64)
-    return Array._new(np.prod(x._array, axis=axis, keepdims=keepdims))
+        dtype = float64
+    return Array._new(np.prod(x._array, dtype=dtype, axis=axis, keepdims=keepdims))
 
 
 def std(
diff --git a/numpy/array_api/tests/test_array_object.py b/numpy/array_api/tests/test_array_object.py
index 12479d765..b980bacca 100644
--- a/numpy/array_api/tests/test_array_object.py
+++ b/numpy/array_api/tests/test_array_object.py
@@ -4,6 +4,7 @@ from numpy.testing import assert_raises
 import numpy as np
 
 from .. import ones, asarray, result_type, all, equal
+from .._array_object import Array
 from .._dtypes import (
     _all_dtypes,
     _boolean_dtypes,
@@ -301,3 +302,23 @@ def test_device_property():
 
     assert all(equal(asarray(a, device='cpu'), a))
     assert_raises(ValueError, lambda: asarray(a, device='gpu'))
+
+def test_array_properties():
+    a = ones((1, 2, 3))
+    b = ones((2, 3))
+    assert_raises(ValueError, lambda: a.T)
+
+    assert isinstance(b.T, Array)
+    assert b.T.shape == (3, 2)
+
+    assert isinstance(a.mT, Array)
+    assert a.mT.shape == (1, 3, 2)
+    assert isinstance(b.mT, Array)
+    assert b.mT.shape == (3, 2)
+
+def test___array__():
+    a = ones((2, 3), dtype=int16)
+    assert np.asarray(a) is a._array
+    b = np.asarray(a, dtype=np.float64)
+    assert np.all(np.equal(b, np.ones((2, 3), dtype=np.float64)))
+    assert b.dtype == np.float64