numpy · rgommers · Jan 21, 2024 · Dec 11, 2023 · Dec 11, 2023 · Dec 11, 2023
diff --git a/doc/release/upcoming_changes/25370.compatibility.rst b/doc/release/upcoming_changes/25370.compatibility.rst
@@ -0,0 +1,14 @@
+Make ``numpy.array_api`` more portable
+--------------------------------------
+
+``numpy.array_api`` no longer uses ``"cpu"`` as its "device", but rather a
+separate ``CPU_DEVICE`` object (which is not accessible in the namespace).
+This is because "cpu" is not part of the array API standard.
+
+``numpy.array_api`` now uses separate wrapped objects for dtypes. Previously
+it reused the ``numpy`` dtype objects. This makes it clear which behaviors on
+dtypes are part of the array API standard (effectively, the standard only
+requires ``==``  on dtype objects).
+
+``numpy.array_api.nonzero`` now errors on zero-dimensional arrays, as required
+by the array API standard.
diff --git a/doc/source/reference/array_api.rst b/doc/source/reference/array_api.rst
@@ -632,6 +632,20 @@ Manipulation functions differences
      - **Compatible**
      - See https://github.com/numpy/numpy/issues/9818.
 
+Searching functions differences
+-------------------------------
+
+.. list-table::
+   :header-rows: 1
+
+   * - Feature
+     - Type
+     - Notes
+   * - ``nonzero`` disallows 0-dimensional inputs
+     - **Breaking**
+     - This behavior is already deprecated for ``np.nonzero``. See
+       https://github.com/numpy/numpy/pull/13708.
+
 Set functions differences
 -------------------------
 
@@ -655,8 +669,8 @@ Set functions differences
 
 .. _array_api-set-functions-differences:
 
-Set functions differences
--------------------------
+Sorting functions differences
+-----------------------------
 
 .. list-table::
    :header-rows: 1
@@ -708,6 +722,16 @@ Other differences
      - **Strictness**
      - For example, ``numpy.array_api.asarray([0], dtype='int32')`` is not
        allowed.
+   * - Dtype objects are wrapped so that they only implement the required
+       ``__eq__`` method, which only compares against dtype objects.
+     - **Strictness**
+     - For example, ``float32 == 'float32'`` is not allowed.
+   * - ``arr.device`` always returns a ``CPU_DEVICE`` object (which is not
+       part of the namespace). This is the only valid non-default value for
+       ``device`` keyword arguments to creation functions like ``asarray()``.
+     - **Compatible**
+     - CPU is the only device supported by NumPy. The standard does not
+       require device objects to be accessible other than via ``arr.device``.
    * - ``asarray`` is not implicitly called in any function.
      - **Strictness**
      - The exception is Python operators, which accept Python scalars in

diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py
@@ -19,6 +19,7 @@
 from enum import IntEnum
 from ._creation_functions import asarray
 from ._dtypes import (
+    _DType,
     _all_dtypes,
     _boolean_dtypes,
     _integer_dtypes,
@@ -39,6 +40,13 @@
 
 import numpy as np
 
+# Placeholder object to represent the "cpu" device (the only device NumPy
+# supports).
+class _cpu_device:
+    def __repr__(self):
+        return "CPU_DEVICE"
+
+CPU_DEVICE = _cpu_device()
 
 class Array:
     """
@@ -75,11 +83,13 @@ def _new(cls, x, /):
         if isinstance(x, np.generic):
             # Convert the array scalar to a 0-D array
             x = np.asarray(x)
-        if x.dtype not in _all_dtypes:
+        _dtype = _DType(x.dtype)
+        if _dtype not in _all_dtypes:
             raise TypeError(
                 f"The array_api namespace does not support the dtype '{x.dtype}'"
             )
         obj._array = x
+        obj._dtype = _dtype
         return obj
 
     # Prevent Array() from working
@@ -101,7 +111,7 @@ def __repr__(self: Array, /) -> str:
         """
         Performs the operation __repr__.
         """
-        suffix = f", dtype={self.dtype.name})"
+        suffix = f", dtype={self.dtype})"
         if 0 in self.shape:
             prefix = "empty("
             mid = str(self.shape)
@@ -176,6 +186,8 @@ def _promote_scalar(self, scalar):
         integer that is too large to fit in a NumPy integer dtype, or
         TypeError when the scalar type is incompatible with the dtype of self.
         """
+        from ._data_type_functions import iinfo
+
         # Note: Only Python scalar types that match the array dtype are
         # allowed.
         if isinstance(scalar, bool):
@@ -189,7 +201,7 @@ def _promote_scalar(self, scalar):
                     "Python int scalars cannot be promoted with bool arrays"
                 )
             if self.dtype in _integer_dtypes:
-                info = np.iinfo(self.dtype)
+                info = iinfo(self.dtype)
                if not (info.min <= scalar <= info.max):
                     raise OverflowError(
                         "Python int scalars must be within the bounds of the dtype for integer arrays"
@@ -215,7 +227,7 @@ def _promote_scalar(self, scalar):
         # behavior for integers within the bounds of the integer dtype.
         # Outside of those bounds we use the default NumPy behavior (either
         # cast or raise OverflowError).
-        return Array._new(np.array(scalar, self.dtype))
+        return Array._new(np.array(scalar, dtype=self.dtype._np_dtype))
 
     @staticmethod
     def _normalize_two_args(x1, x2) -> Tuple[Array, Array]:
@@ -325,7 +337,9 @@ def _validate_index(self, key):
         for i in _key:
             if i is not None:
                 nonexpanding_key.append(i)
-                if isinstance(i, Array) or isinstance(i, np.ndarray):
+                if isinstance(i, np.ndarray):
+                    raise IndexError("Index arrays for np.array_api must be np.array_api arrays")
+                if isinstance(i, Array):
                     if i.dtype in _boolean_dtypes:
                         key_has_mask = True
                     single_axes.append(i)
@@ -1067,7 +1081,7 @@ def __rxor__(self: Array, other: Union[int, bool, Array], /) -> Array:
     def to_device(self: Array, device: Device, /, stream: None = None) -> Array:
         if stream is not None:
             raise ValueError("The stream argument to to_device() is not supported")
-        if device == 'cpu':
+        if device == CPU_DEVICE:
             return self
         raise ValueError(f"Unsupported device {device!r}")
 
@@ -1078,11 +1092,11 @@ def dtype(self) -> Dtype:
 
         See its docstring for more information.
         """
-        return self._array.dtype
+        return self._dtype
 
     @property
     def device(self) -> Device:
-        return "cpu"
+        return CPU_DEVICE
 
     # Note: mT is new in array API spec (see matrix_transpose)
     @property