From 6e57d829cb6628610e163524f203245b247a2839 Mon Sep 17 00:00:00 2001
From: Aaron Meurer <asmeurer@gmail.com>
Date: Wed, 4 Aug 2021 16:47:05 -0600
Subject: Rename numpy._array_api to numpy.array_api

Instead of the leading underscore, the experimentalness of the module will be
indicated by omitting a warning on import. That we, we do not have to change
the API from underscore to no underscore when the module is no longer
experimental.
---
 numpy/array_api/_array_object.py | 983 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 983 insertions(+)
 create mode 100644 numpy/array_api/_array_object.py

(limited to 'numpy/array_api/_array_object.py')

diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py
new file mode 100644
index 000000000..24957fde6
--- /dev/null
+++ b/numpy/array_api/_array_object.py
@@ -0,0 +1,983 @@
+"""
+Wrapper class around the ndarray object for the array API standard.
+
+The array API standard defines some behaviors differently than ndarray, in
+particular, type promotion rules are different (the standard has no
+value-based casting). The standard also specifies a more limited subset of
+array methods and functionalities than are implemented on ndarray. Since the
+goal of the array_api namespace is to be a minimal implementation of the array
+API standard, we need to define a separate wrapper class for the array_api
+namespace.
+
+The standard compliant class is only a wrapper class. It is *not* a subclass
+of ndarray.
+"""
+
+from __future__ import annotations
+
+import operator
+from enum import IntEnum
+from ._creation_functions import asarray
+from ._dtypes import (_all_dtypes, _boolean_dtypes, _integer_dtypes,
+                      _integer_or_boolean_dtypes, _floating_dtypes, _numeric_dtypes)
+
+from typing import TYPE_CHECKING, Any, Optional, Tuple, Union
+if TYPE_CHECKING:
+    from ._typing import PyCapsule, Device, Dtype
+
+import numpy as np
+
+class Array:
+    """
+    n-d array object for the array API namespace.
+
+    See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for more
+    information.
+
+    This is a wrapper around numpy.ndarray that restricts the usage to only
+    those things that are required by the array API namespace. Note,
+    attributes on this object that start with a single underscore are not part
+    of the API specification and should only be used internally. This object
+    should not be constructed directly. Rather, use one of the creation
+    functions, such as asarray().
+
+    """
+    # Use a custom constructor instead of __init__, as manually initializing
+    # this class is not supported API.
+    @classmethod
+    def _new(cls, x, /):
+        """
+        This is a private method for initializing the array API Array
+        object.
+
+        Functions outside of the array_api submodule should not use this
+        method. Use one of the creation functions instead, such as
+        ``asarray``.
+
+        """
+        obj = super().__new__(cls)
+        # Note: The spec does not have array scalars, only 0-D arrays.
+        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:
+            raise TypeError(f"The array_api namespace does not support the dtype '{x.dtype}'")
+        obj._array = x
+        return obj
+
+    # Prevent Array() from working
+    def __new__(cls, *args, **kwargs):
+        raise TypeError("The array_api Array object should not be instantiated directly. Use an array creation function, such as asarray(), instead.")
+
+    # These functions are not required by the spec, but are implemented for
+    # the sake of usability.
+
+    def __str__(self: Array, /) -> str:
+        """
+        Performs the operation __str__.
+        """
+        return self._array.__str__().replace('array', 'Array')
+
+    def __repr__(self: Array, /) -> str:
+        """
+        Performs the operation __repr__.
+        """
+        return f"Array({np.array2string(self._array, separator=', ')}, dtype={self.dtype.name})"
+
+    # 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
+
+    def _check_allowed_dtypes(self, other, dtype_category, op):
+        """
+        Helper function for operators to only allow specific input dtypes
+
+        Use like
+
+            other = self._check_allowed_dtypes(other, 'numeric', '__add__')
+            if other is NotImplemented:
+                return other
+        """
+        from ._dtypes import _result_type
+
+        _dtypes = {
+            'all': _all_dtypes,
+            'numeric': _numeric_dtypes,
+            'integer': _integer_dtypes,
+            'integer or boolean': _integer_or_boolean_dtypes,
+            'boolean': _boolean_dtypes,
+            'floating-point': _floating_dtypes,
+        }
+
+        if self.dtype not in _dtypes[dtype_category]:
+            raise TypeError(f'Only {dtype_category} dtypes are allowed in {op}')
+        if isinstance(other, (int, float, bool)):
+            other = self._promote_scalar(other)
+        elif isinstance(other, Array):
+            if other.dtype not in _dtypes[dtype_category]:
+                raise TypeError(f'Only {dtype_category} dtypes are allowed in {op}')
+        else:
+            return NotImplemented
+
+        # This will raise TypeError for type combinations that are not allowed
+        # to promote in the spec (even if the NumPy array operator would
+        # promote them).
+        res_dtype = _result_type(self.dtype, other.dtype)
+        if op.startswith('__i'):
+            # Note: NumPy will allow in-place operators in some cases where
+            # the type promoted operator does not match the left-hand side
+            # operand. For example,
+
+            # >>> a = np.array(1, dtype=np.int8)
+            # >>> a += np.array(1, dtype=np.int16)
+
+            # The spec explicitly disallows this.
+            if res_dtype != self.dtype:
+                raise TypeError(f"Cannot perform {op} with dtypes {self.dtype} and {other.dtype}")
+
+        return other
+
+    # Helper function to match the type promotion rules in the spec
+    def _promote_scalar(self, scalar):
+        """
+        Returns a promoted version of a Python scalar appropriate for use with
+        operations on self.
+
+        This may raise an OverflowError in cases where the scalar is an
+        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.
+        """
+        if isinstance(scalar, bool):
+            if self.dtype not in _boolean_dtypes:
+                raise TypeError("Python bool scalars can only be promoted with bool arrays")
+        elif isinstance(scalar, int):
+            if self.dtype in _boolean_dtypes:
+                raise TypeError("Python int scalars cannot be promoted with bool arrays")
+        elif isinstance(scalar, float):
+            if self.dtype not in _floating_dtypes:
+                raise TypeError("Python float scalars can only be promoted with floating-point arrays.")
+        else:
+            raise TypeError("'scalar' must be a Python scalar")
+
+        # Note: the spec only specifies integer-dtype/int promotion
+        # 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))
+
+    @staticmethod
+    def _normalize_two_args(x1, x2):
+        """
+        Normalize inputs to two arg functions to fix type promotion rules
+
+        NumPy deviates from the spec type promotion rules in cases where one
+        argument is 0-dimensional and the other is not. For example:
+
+        >>> import numpy as np
+        >>> a = np.array([1.0], dtype=np.float32)
+        >>> b = np.array(1.0, dtype=np.float64)
+        >>> np.add(a, b) # The spec says this should be float64
+        array([2.], dtype=float32)
+
+        To fix this, we add a dimension to the 0-dimension array before passing it
+        through. This works because a dimension would be added anyway from
+        broadcasting, so the resulting shape is the same, but this prevents NumPy
+        from not promoting the dtype.
+        """
+        # Another option would be to use signature=(x1.dtype, x2.dtype, None),
+        # but that only works for ufuncs, so we would have to call the ufuncs
+        # directly in the operator methods. One should also note that this
+        # sort of trick wouldn't work for functions like searchsorted, which
+        # don't do normal broadcasting, but there aren't any functions like
+        # that in the array API namespace.
+        if x1.ndim == 0 and x2.ndim != 0:
+            # The _array[None] workaround was chosen because it is relatively
+            # performant. broadcast_to(x1._array, x2.shape) is much slower. We
+            # could also manually type promote x2, but that is more complicated
+            # and about the same performance as this.
+            x1 = Array._new(x1._array[None])
+        elif x2.ndim == 0 and x1.ndim != 0:
+            x2 = Array._new(x2._array[None])
+        return (x1, x2)
+
+    # Note: A large fraction of allowed indices are disallowed here (see the
+    # docstring below)
+    @staticmethod
+    def _validate_index(key, shape):
+        """
+        Validate an index according to the array API.
+
+        The array API specification only requires a subset of indices that are
+        supported by NumPy. This function will reject any index that is
+        allowed by NumPy but not required by the array API specification. We
+        always raise ``IndexError`` on such indices (the spec does not require
+        any specific behavior on them, but this makes the NumPy array API
+        namespace a minimal implementation of the spec). See
+        https://data-apis.org/array-api/latest/API_specification/indexing.html
+        for the full list of required indexing behavior
+
+        This function either raises IndexError if the index ``key`` is
+        invalid, or a new key to be used in place of ``key`` in indexing. It
+        only raises ``IndexError`` on indices that are not already rejected by
+        NumPy, as NumPy will already raise the appropriate error on such
+        indices. ``shape`` may be None, in which case, only cases that are
+        independent of the array shape are checked.
+
+        The following cases are allowed by NumPy, but not specified by the array
+        API specification:
+
+        - The start and stop of a slice may not be out of bounds. In
+          particular, for a slice ``i:j:k`` on an axis of size ``n``, only the
+          following are allowed:
+
+          - ``i`` or ``j`` omitted (``None``).
+          - ``-n <= i <= max(0, n - 1)``.
+          - For ``k > 0`` or ``k`` omitted (``None``), ``-n <= j <= n``.
+          - For ``k < 0``, ``-n - 1 <= j <= max(0, n - 1)``.
+
+        - Boolean array indices are not allowed as part of a larger tuple
+          index.
+
+        - Integer array indices are not allowed (with the exception of 0-D
+          arrays, which are treated the same as scalars).
+
+        Additionally, it should be noted that indices that would return a
+        scalar in NumPy will return a 0-D array. Array scalars are not allowed
+        in the specification, only 0-D arrays. This is done in the
+        ``Array._new`` constructor, not this function.
+
+        """
+        if isinstance(key, slice):
+            if shape is None:
+                return key
+            if shape == ():
+                return key
+            size = shape[0]
+            # Ensure invalid slice entries are passed through.
+            if key.start is not None:
+                try:
+                    operator.index(key.start)
+                except TypeError:
+                    return key
+                if not (-size <= key.start <= max(0, size - 1)):
+                    raise IndexError("Slices with out-of-bounds start are not allowed in the array API namespace")
+            if key.stop is not None:
+                try:
+                    operator.index(key.stop)
+                except TypeError:
+                    return key
+                step = 1 if key.step is None else key.step
+                if (step > 0 and not (-size <= key.stop <= size)
+                    or step < 0 and not (-size - 1 <= key.stop <= max(0, size - 1))):
+                    raise IndexError("Slices with out-of-bounds stop are not allowed in the array API namespace")
+            return key
+
+        elif isinstance(key, tuple):
+            key = tuple(Array._validate_index(idx, None) for idx in key)
+
+            for idx in key:
+                if isinstance(idx, np.ndarray) and idx.dtype in _boolean_dtypes or isinstance(idx, (bool, np.bool_)):
+                    if len(key) == 1:
+                        return key
+                    raise IndexError("Boolean array indices combined with other indices are not allowed in the array API namespace")
+                if isinstance(idx, tuple):
+                    raise IndexError("Nested tuple indices are not allowed in the array API namespace")
+
+            if shape is None:
+                return key
+            n_ellipsis = key.count(...)
+            if n_ellipsis > 1:
+                return key
+            ellipsis_i = key.index(...) if n_ellipsis else len(key)
+
+            for idx, size in list(zip(key[:ellipsis_i], shape)) + list(zip(key[:ellipsis_i:-1], shape[:ellipsis_i:-1])):
+                Array._validate_index(idx, (size,))
+            return key
+        elif isinstance(key, bool):
+            return key
+        elif isinstance(key, Array):
+            if key.dtype in _integer_dtypes:
+                if key.ndim != 0:
+                    raise IndexError("Non-zero dimensional integer array indices are not allowed in the array API namespace")
+            return key._array
+        elif key is Ellipsis:
+            return key
+        elif key is None:
+            raise IndexError("newaxis indices are not allowed in the array API namespace")
+        try:
+            return operator.index(key)
+        except TypeError:
+            # Note: This also omits boolean arrays that are not already in
+            # Array() form, like a list of booleans.
+            raise IndexError("Only integers, slices (`:`), ellipsis (`...`), and boolean arrays are valid indices in the array API namespace")
+
+    # Everything below this line is required by the spec.
+
+    def __abs__(self: Array, /) -> Array:
+        """
+        Performs the operation __abs__.
+        """
+        if self.dtype not in _numeric_dtypes:
+            raise TypeError('Only numeric dtypes are allowed in __abs__')
+        res = self._array.__abs__()
+        return self.__class__._new(res)
+
+    def __add__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __add__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__add__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__add__(other._array)
+        return self.__class__._new(res)
+
+    def __and__(self: Array, other: Union[int, bool, Array], /) -> Array:
+        """
+        Performs the operation __and__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer or boolean', '__and__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__and__(other._array)
+        return self.__class__._new(res)
+
+    def __array_namespace__(self: Array, /, *, api_version: Optional[str] = None) -> object:
+        if api_version is not None and not api_version.startswith('2021.'):
+            raise ValueError(f"Unrecognized array API version: {api_version!r}")
+        from numpy import array_api
+        return array_api
+
+    def __bool__(self: Array, /) -> bool:
+        """
+        Performs the operation __bool__.
+        """
+        # Note: This is an error here.
+        if self._array.ndim != 0:
+            raise TypeError("bool is only allowed on arrays with 0 dimensions")
+        res = self._array.__bool__()
+        return res
+
+    def __dlpack__(self: Array, /, *, stream: None = None) -> PyCapsule:
+        """
+        Performs the operation __dlpack__.
+        """
+        res = self._array.__dlpack__(stream=stream)
+        return self.__class__._new(res)
+
+    def __dlpack_device__(self: Array, /) -> Tuple[IntEnum, int]:
+        """
+        Performs the operation __dlpack_device__.
+        """
+        # Note: device support is required for this
+        res = self._array.__dlpack_device__()
+        return self.__class__._new(res)
+
+    def __eq__(self: Array, other: Union[int, float, bool, Array], /) -> Array:
+        """
+        Performs the operation __eq__.
+        """
+        # Even though "all" dtypes are allowed, we still require them to be
+        # promotable with each other.
+        other = self._check_allowed_dtypes(other, 'all', '__eq__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__eq__(other._array)
+        return self.__class__._new(res)
+
+    def __float__(self: Array, /) -> float:
+        """
+        Performs the operation __float__.
+        """
+        # Note: This is an error here.
+        if self._array.ndim != 0:
+            raise TypeError("float is only allowed on arrays with 0 dimensions")
+        res = self._array.__float__()
+        return res
+
+    def __floordiv__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __floordiv__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__floordiv__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__floordiv__(other._array)
+        return self.__class__._new(res)
+
+    def __ge__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __ge__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__ge__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__ge__(other._array)
+        return self.__class__._new(res)
+
+    def __getitem__(self: Array, key: Union[int, slice, ellipsis, Tuple[Union[int, slice, ellipsis], ...], Array], /) -> Array:
+        """
+        Performs the operation __getitem__.
+        """
+        # Note: Only indices required by the spec are allowed. See the
+        # docstring of _validate_index
+        key = self._validate_index(key, self.shape)
+        res = self._array.__getitem__(key)
+        return self._new(res)
+
+    def __gt__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __gt__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__gt__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__gt__(other._array)
+        return self.__class__._new(res)
+
+    def __int__(self: Array, /) -> int:
+        """
+        Performs the operation __int__.
+        """
+        # Note: This is an error here.
+        if self._array.ndim != 0:
+            raise TypeError("int is only allowed on arrays with 0 dimensions")
+        res = self._array.__int__()
+        return res
+
+    def __invert__(self: Array, /) -> Array:
+        """
+        Performs the operation __invert__.
+        """
+        if self.dtype not in _integer_or_boolean_dtypes:
+            raise TypeError('Only integer or boolean dtypes are allowed in __invert__')
+        res = self._array.__invert__()
+        return self.__class__._new(res)
+
+    def __le__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __le__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__le__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__le__(other._array)
+        return self.__class__._new(res)
+
+    # Note: __len__ may end up being removed from the array API spec.
+    def __len__(self, /) -> int:
+        """
+        Performs the operation __len__.
+        """
+        res = self._array.__len__()
+        return self.__class__._new(res)
+
+    def __lshift__(self: Array, other: Union[int, Array], /) -> Array:
+        """
+        Performs the operation __lshift__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer', '__lshift__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__lshift__(other._array)
+        return self.__class__._new(res)
+
+    def __lt__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __lt__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__lt__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__lt__(other._array)
+        return self.__class__._new(res)
+
+    def __matmul__(self: Array, other: Array, /) -> Array:
+        """
+        Performs the operation __matmul__.
+        """
+        # matmul is not defined for scalars, but without this, we may get
+        # the wrong error message from asarray.
+        other = self._check_allowed_dtypes(other, 'numeric', '__matmul__')
+        if other is NotImplemented:
+            return other
+        res = self._array.__matmul__(other._array)
+        return self.__class__._new(res)
+
+    def __mod__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __mod__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__mod__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__mod__(other._array)
+        return self.__class__._new(res)
+
+    def __mul__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __mul__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__mul__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__mul__(other._array)
+        return self.__class__._new(res)
+
+    def __ne__(self: Array, other: Union[int, float, bool, Array], /) -> Array:
+        """
+        Performs the operation __ne__.
+        """
+        other = self._check_allowed_dtypes(other, 'all', '__ne__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__ne__(other._array)
+        return self.__class__._new(res)
+
+    def __neg__(self: Array, /) -> Array:
+        """
+        Performs the operation __neg__.
+        """
+        if self.dtype not in _numeric_dtypes:
+            raise TypeError('Only numeric dtypes are allowed in __neg__')
+        res = self._array.__neg__()
+        return self.__class__._new(res)
+
+    def __or__(self: Array, other: Union[int, bool, Array], /) -> Array:
+        """
+        Performs the operation __or__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer or boolean', '__or__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__or__(other._array)
+        return self.__class__._new(res)
+
+    def __pos__(self: Array, /) -> Array:
+        """
+        Performs the operation __pos__.
+        """
+        if self.dtype not in _numeric_dtypes:
+            raise TypeError('Only numeric dtypes are allowed in __pos__')
+        res = self._array.__pos__()
+        return self.__class__._new(res)
+
+    # PEP 484 requires int to be a subtype of float, but __pow__ should not
+    # accept int.
+    def __pow__(self: Array, other: Union[float, Array], /) -> Array:
+        """
+        Performs the operation __pow__.
+        """
+        from ._elementwise_functions import pow
+
+        other = self._check_allowed_dtypes(other, 'floating-point', '__pow__')
+        if other is NotImplemented:
+            return other
+        # Note: NumPy's __pow__ does not follow type promotion rules for 0-d
+        # arrays, so we use pow() here instead.
+        return pow(self, other)
+
+    def __rshift__(self: Array, other: Union[int, Array], /) -> Array:
+        """
+        Performs the operation __rshift__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer', '__rshift__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__rshift__(other._array)
+        return self.__class__._new(res)
+
+    def __setitem__(self, key: Union[int, slice, ellipsis, Tuple[Union[int, slice, ellipsis], ...], Array], value: Union[int, float, bool, Array], /) -> Array:
+        """
+        Performs the operation __setitem__.
+        """
+        # Note: Only indices required by the spec are allowed. See the
+        # docstring of _validate_index
+        key = self._validate_index(key, self.shape)
+        self._array.__setitem__(key, asarray(value)._array)
+
+    def __sub__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __sub__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__sub__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__sub__(other._array)
+        return self.__class__._new(res)
+
+    # PEP 484 requires int to be a subtype of float, but __truediv__ should
+    # not accept int.
+    def __truediv__(self: Array, other: Union[float, Array], /) -> Array:
+        """
+        Performs the operation __truediv__.
+        """
+        other = self._check_allowed_dtypes(other, 'floating-point', '__truediv__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__truediv__(other._array)
+        return self.__class__._new(res)
+
+    def __xor__(self: Array, other: Union[int, bool, Array], /) -> Array:
+        """
+        Performs the operation __xor__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer or boolean', '__xor__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__xor__(other._array)
+        return self.__class__._new(res)
+
+    def __iadd__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __iadd__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__iadd__')
+        if other is NotImplemented:
+            return other
+        self._array.__iadd__(other._array)
+        return self
+
+    def __radd__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __radd__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__radd__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__radd__(other._array)
+        return self.__class__._new(res)
+
+    def __iand__(self: Array, other: Union[int, bool, Array], /) -> Array:
+        """
+        Performs the operation __iand__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer or boolean', '__iand__')
+        if other is NotImplemented:
+            return other
+        self._array.__iand__(other._array)
+        return self
+
+    def __rand__(self: Array, other: Union[int, bool, Array], /) -> Array:
+        """
+        Performs the operation __rand__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer or boolean', '__rand__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__rand__(other._array)
+        return self.__class__._new(res)
+
+    def __ifloordiv__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __ifloordiv__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__ifloordiv__')
+        if other is NotImplemented:
+            return other
+        self._array.__ifloordiv__(other._array)
+        return self
+
+    def __rfloordiv__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __rfloordiv__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__rfloordiv__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__rfloordiv__(other._array)
+        return self.__class__._new(res)
+
+    def __ilshift__(self: Array, other: Union[int, Array], /) -> Array:
+        """
+        Performs the operation __ilshift__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer', '__ilshift__')
+        if other is NotImplemented:
+            return other
+        self._array.__ilshift__(other._array)
+        return self
+
+    def __rlshift__(self: Array, other: Union[int, Array], /) -> Array:
+        """
+        Performs the operation __rlshift__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer', '__rlshift__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__rlshift__(other._array)
+        return self.__class__._new(res)
+
+    def __imatmul__(self: Array, other: Array, /) -> Array:
+        """
+        Performs the operation __imatmul__.
+        """
+        # Note: NumPy does not implement __imatmul__.
+
+        # matmul is not defined for scalars, but without this, we may get
+        # the wrong error message from asarray.
+        other = self._check_allowed_dtypes(other, 'numeric', '__imatmul__')
+        if other is NotImplemented:
+            return other
+
+        # __imatmul__ can only be allowed when it would not change the shape
+        # of self.
+        other_shape = other.shape
+        if self.shape == () or other_shape == ():
+            raise ValueError("@= requires at least one dimension")
+        if len(other_shape) == 1 or other_shape[-1] != other_shape[-2]:
+            raise ValueError("@= cannot change the shape of the input array")
+        self._array[:] = self._array.__matmul__(other._array)
+        return self
+
+    def __rmatmul__(self: Array, other: Array, /) -> Array:
+        """
+        Performs the operation __rmatmul__.
+        """
+        # matmul is not defined for scalars, but without this, we may get
+        # the wrong error message from asarray.
+        other = self._check_allowed_dtypes(other, 'numeric', '__rmatmul__')
+        if other is NotImplemented:
+            return other
+        res = self._array.__rmatmul__(other._array)
+        return self.__class__._new(res)
+
+    def __imod__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __imod__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__imod__')
+        if other is NotImplemented:
+            return other
+        self._array.__imod__(other._array)
+        return self
+
+    def __rmod__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __rmod__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__rmod__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__rmod__(other._array)
+        return self.__class__._new(res)
+
+    def __imul__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __imul__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__imul__')
+        if other is NotImplemented:
+            return other
+        self._array.__imul__(other._array)
+        return self
+
+    def __rmul__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __rmul__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__rmul__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__rmul__(other._array)
+        return self.__class__._new(res)
+
+    def __ior__(self: Array, other: Union[int, bool, Array], /) -> Array:
+        """
+        Performs the operation __ior__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer or boolean', '__ior__')
+        if other is NotImplemented:
+            return other
+        self._array.__ior__(other._array)
+        return self
+
+    def __ror__(self: Array, other: Union[int, bool, Array], /) -> Array:
+        """
+        Performs the operation __ror__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer or boolean', '__ror__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__ror__(other._array)
+        return self.__class__._new(res)
+
+    def __ipow__(self: Array, other: Union[float, Array], /) -> Array:
+        """
+        Performs the operation __ipow__.
+        """
+        other = self._check_allowed_dtypes(other, 'floating-point', '__ipow__')
+        if other is NotImplemented:
+            return other
+        self._array.__ipow__(other._array)
+        return self
+
+    def __rpow__(self: Array, other: Union[float, Array], /) -> Array:
+        """
+        Performs the operation __rpow__.
+        """
+        from ._elementwise_functions import pow
+
+        other = self._check_allowed_dtypes(other, 'floating-point', '__rpow__')
+        if other is NotImplemented:
+            return other
+        # Note: NumPy's __pow__ does not follow the spec type promotion rules
+        # for 0-d arrays, so we use pow() here instead.
+        return pow(other, self)
+
+    def __irshift__(self: Array, other: Union[int, Array], /) -> Array:
+        """
+        Performs the operation __irshift__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer', '__irshift__')
+        if other is NotImplemented:
+            return other
+        self._array.__irshift__(other._array)
+        return self
+
+    def __rrshift__(self: Array, other: Union[int, Array], /) -> Array:
+        """
+        Performs the operation __rrshift__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer', '__rrshift__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__rrshift__(other._array)
+        return self.__class__._new(res)
+
+    def __isub__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __isub__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__isub__')
+        if other is NotImplemented:
+            return other
+        self._array.__isub__(other._array)
+        return self
+
+    def __rsub__(self: Array, other: Union[int, float, Array], /) -> Array:
+        """
+        Performs the operation __rsub__.
+        """
+        other = self._check_allowed_dtypes(other, 'numeric', '__rsub__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__rsub__(other._array)
+        return self.__class__._new(res)
+
+    def __itruediv__(self: Array, other: Union[float, Array], /) -> Array:
+        """
+        Performs the operation __itruediv__.
+        """
+        other = self._check_allowed_dtypes(other, 'floating-point', '__itruediv__')
+        if other is NotImplemented:
+            return other
+        self._array.__itruediv__(other._array)
+        return self
+
+    def __rtruediv__(self: Array, other: Union[float, Array], /) -> Array:
+        """
+        Performs the operation __rtruediv__.
+        """
+        other = self._check_allowed_dtypes(other, 'floating-point', '__rtruediv__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__rtruediv__(other._array)
+        return self.__class__._new(res)
+
+    def __ixor__(self: Array, other: Union[int, bool, Array], /) -> Array:
+        """
+        Performs the operation __ixor__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer or boolean', '__ixor__')
+        if other is NotImplemented:
+            return other
+        self._array.__ixor__(other._array)
+        return self
+
+    def __rxor__(self: Array, other: Union[int, bool, Array], /) -> Array:
+        """
+        Performs the operation __rxor__.
+        """
+        other = self._check_allowed_dtypes(other, 'integer or boolean', '__rxor__')
+        if other is NotImplemented:
+            return other
+        self, other = self._normalize_two_args(self, other)
+        res = self._array.__rxor__(other._array)
+        return self.__class__._new(res)
+
+    @property
+    def dtype(self) -> Dtype:
+        """
+        Array API compatible wrapper for :py:meth:`np.ndarray.dtype <numpy.ndarray.dtype>`.
+
+        See its docstring for more information.
+        """
+        return self._array.dtype
+
+    @property
+    def device(self) -> Device:
+        return 'cpu'
+
+    @property
+    def ndim(self) -> int:
+        """
+        Array API compatible wrapper for :py:meth:`np.ndarray.ndim <numpy.ndarray.ndim>`.
+
+        See its docstring for more information.
+        """
+        return self._array.ndim
+
+    @property
+    def shape(self) -> Tuple[int, ...]:
+        """
+        Array API compatible wrapper for :py:meth:`np.ndarray.shape <numpy.ndarray.shape>`.
+
+        See its docstring for more information.
+        """
+        return self._array.shape
+
+    @property
+    def size(self) -> int:
+        """
+        Array API compatible wrapper for :py:meth:`np.ndarray.size <numpy.ndarray.size>`.
+
+        See its docstring for more information.
+        """
+        return self._array.size
+
+    @property
+    def T(self) -> Array:
+        """
+        Array API compatible wrapper for :py:meth:`np.ndarray.T <numpy.ndarray.T>`.
+
+        See its docstring for more information.
+        """
+        return self._array.T
-- 
cgit v1.2.1


From 5605d687019dc55e594d4e227747c72bebb71a3c Mon Sep 17 00:00:00 2001
From: Aaron Meurer <asmeurer@gmail.com>
Date: Wed, 4 Aug 2021 19:59:47 -0600
Subject: Remove unused import

---
 numpy/array_api/_array_object.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'numpy/array_api/_array_object.py')

diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py
index 24957fde6..af70058e6 100644
--- a/numpy/array_api/_array_object.py
+++ b/numpy/array_api/_array_object.py
@@ -21,7 +21,7 @@ from ._creation_functions import asarray
 from ._dtypes import (_all_dtypes, _boolean_dtypes, _integer_dtypes,
                       _integer_or_boolean_dtypes, _floating_dtypes, _numeric_dtypes)
 
-from typing import TYPE_CHECKING, Any, Optional, Tuple, Union
+from typing import TYPE_CHECKING, Optional, Tuple, Union
 if TYPE_CHECKING:
     from ._typing import PyCapsule, Device, Dtype
 
-- 
cgit v1.2.1


From bc20d334b575f897157b1cf3eecda77f3e40e049 Mon Sep 17 00:00:00 2001
From: Aaron Meurer <asmeurer@gmail.com>
Date: Wed, 4 Aug 2021 20:01:11 -0600
Subject: Move the array API dtype categories into the top level

They are not an official part of the spec but are useful for various parts of
the implementation.
---
 numpy/array_api/_array_object.py | 17 ++++-------------
 1 file changed, 4 insertions(+), 13 deletions(-)

(limited to 'numpy/array_api/_array_object.py')

diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py
index af70058e6..50906642d 100644
--- a/numpy/array_api/_array_object.py
+++ b/numpy/array_api/_array_object.py
@@ -98,23 +98,14 @@ class Array:
             if other is NotImplemented:
                 return other
         """
-        from ._dtypes import _result_type
-
-        _dtypes = {
-            'all': _all_dtypes,
-            'numeric': _numeric_dtypes,
-            'integer': _integer_dtypes,
-            'integer or boolean': _integer_or_boolean_dtypes,
-            'boolean': _boolean_dtypes,
-            'floating-point': _floating_dtypes,
-        }
-
-        if self.dtype not in _dtypes[dtype_category]:
+        from ._dtypes import _result_type, _dtype_categories
+
+        if self.dtype not in _dtype_categories[dtype_category]:
             raise TypeError(f'Only {dtype_category} dtypes are allowed in {op}')
         if isinstance(other, (int, float, bool)):
             other = self._promote_scalar(other)
         elif isinstance(other, Array):
-            if other.dtype not in _dtypes[dtype_category]:
+            if other.dtype not in _dtype_categories[dtype_category]:
                 raise TypeError(f'Only {dtype_category} dtypes are allowed in {op}')
         else:
             return NotImplemented
-- 
cgit v1.2.1


From 6789a74312cda391b81ca803d38919555213a38f Mon Sep 17 00:00:00 2001
From: Aaron Meurer <asmeurer@gmail.com>
Date: Wed, 4 Aug 2021 20:05:46 -0600
Subject: Move some imports out of functions to the top of the file

Some of the imports in the array API module have to be inside functions to
avoid circular imports, but these ones did not.
---
 numpy/array_api/_array_object.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

(limited to 'numpy/array_api/_array_object.py')

diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py
index 50906642d..364b88f89 100644
--- a/numpy/array_api/_array_object.py
+++ b/numpy/array_api/_array_object.py
@@ -19,7 +19,8 @@ import operator
 from enum import IntEnum
 from ._creation_functions import asarray
 from ._dtypes import (_all_dtypes, _boolean_dtypes, _integer_dtypes,
-                      _integer_or_boolean_dtypes, _floating_dtypes, _numeric_dtypes)
+                      _integer_or_boolean_dtypes, _floating_dtypes,
+                      _numeric_dtypes, _result_type, _dtype_categories)
 
 from typing import TYPE_CHECKING, Optional, Tuple, Union
 if TYPE_CHECKING:
@@ -27,6 +28,8 @@ if TYPE_CHECKING:
 
 import numpy as np
 
+from numpy import array_api
+
 class Array:
     """
     n-d array object for the array API namespace.
@@ -98,7 +101,6 @@ class Array:
             if other is NotImplemented:
                 return other
         """
-        from ._dtypes import _result_type, _dtype_categories
 
         if self.dtype not in _dtype_categories[dtype_category]:
             raise TypeError(f'Only {dtype_category} dtypes are allowed in {op}')
@@ -338,7 +340,6 @@ class Array:
     def __array_namespace__(self: Array, /, *, api_version: Optional[str] = None) -> object:
         if api_version is not None and not api_version.startswith('2021.'):
             raise ValueError(f"Unrecognized array API version: {api_version!r}")
-        from numpy import array_api
         return array_api
 
     def __bool__(self: Array, /) -> bool:
-- 
cgit v1.2.1


From 2fe8643cce651fa2ada5619f85e3cc16524d4076 Mon Sep 17 00:00:00 2001
From: Aaron Meurer <asmeurer@gmail.com>
Date: Fri, 6 Aug 2021 16:48:16 -0600
Subject: Fix the array API __len__ method

---
 numpy/array_api/_array_object.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

(limited to 'numpy/array_api/_array_object.py')

diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py
index 364b88f89..00f50eade 100644
--- a/numpy/array_api/_array_object.py
+++ b/numpy/array_api/_array_object.py
@@ -468,8 +468,7 @@ class Array:
         """
         Performs the operation __len__.
         """
-        res = self._array.__len__()
-        return self.__class__._new(res)
+        return self._array.__len__()
 
     def __lshift__(self: Array, other: Union[int, Array], /) -> Array:
         """
-- 
cgit v1.2.1


From 8f7d00ed447174d9398af3365709222b529c1cad Mon Sep 17 00:00:00 2001
From: Aaron Meurer <asmeurer@gmail.com>
Date: Fri, 6 Aug 2021 18:22:00 -0600
Subject: Run (selective) black on the array_api submodule

I've omitted a few changes from black that messed up the readability of some
complicated if statements that were organized logically line-by-line, and some
changes that use unnecessary operator spacing.
---
 numpy/array_api/_array_object.py | 205 +++++++++++++++++++++++++--------------
 1 file changed, 130 insertions(+), 75 deletions(-)

(limited to 'numpy/array_api/_array_object.py')

diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py
index 00f50eade..0f511a577 100644
--- a/numpy/array_api/_array_object.py
+++ b/numpy/array_api/_array_object.py
@@ -18,11 +18,19 @@ from __future__ import annotations
 import operator
 from enum import IntEnum
 from ._creation_functions import asarray
-from ._dtypes import (_all_dtypes, _boolean_dtypes, _integer_dtypes,
-                      _integer_or_boolean_dtypes, _floating_dtypes,
-                      _numeric_dtypes, _result_type, _dtype_categories)
+from ._dtypes import (
+    _all_dtypes,
+    _boolean_dtypes,
+    _integer_dtypes,
+    _integer_or_boolean_dtypes,
+    _floating_dtypes,
+    _numeric_dtypes,
+    _result_type,
+    _dtype_categories,
+)
 
 from typing import TYPE_CHECKING, Optional, Tuple, Union
+
 if TYPE_CHECKING:
     from ._typing import PyCapsule, Device, Dtype
 
@@ -30,6 +38,7 @@ import numpy as np
 
 from numpy import array_api
 
+
 class Array:
     """
     n-d array object for the array API namespace.
@@ -45,6 +54,7 @@ class Array:
     functions, such as asarray().
 
     """
+
     # Use a custom constructor instead of __init__, as manually initializing
     # this class is not supported API.
     @classmethod
@@ -64,13 +74,17 @@ class Array:
             # Convert the array scalar to a 0-D array
             x = np.asarray(x)
         if x.dtype not in _all_dtypes:
-            raise TypeError(f"The array_api namespace does not support the dtype '{x.dtype}'")
+            raise TypeError(
+                f"The array_api namespace does not support the dtype '{x.dtype}'"
+            )
         obj._array = x
         return obj
 
     # Prevent Array() from working
     def __new__(cls, *args, **kwargs):
-        raise TypeError("The array_api Array object should not be instantiated directly. Use an array creation function, such as asarray(), instead.")
+        raise TypeError(
+            "The array_api Array object should not be instantiated directly. Use an array creation function, such as asarray(), instead."
+        )
 
     # These functions are not required by the spec, but are implemented for
     # the sake of usability.
@@ -79,7 +93,7 @@ class Array:
         """
         Performs the operation __str__.
         """
-        return self._array.__str__().replace('array', 'Array')
+        return self._array.__str__().replace("array", "Array")
 
     def __repr__(self: Array, /) -> str:
         """
@@ -103,12 +117,12 @@ class Array:
         """
 
         if self.dtype not in _dtype_categories[dtype_category]:
-            raise TypeError(f'Only {dtype_category} dtypes are allowed in {op}')
+            raise TypeError(f"Only {dtype_category} dtypes are allowed in {op}")
         if isinstance(other, (int, float, bool)):
             other = self._promote_scalar(other)
         elif isinstance(other, Array):
             if other.dtype not in _dtype_categories[dtype_category]:
-                raise TypeError(f'Only {dtype_category} dtypes are allowed in {op}')
+                raise TypeError(f"Only {dtype_category} dtypes are allowed in {op}")
         else:
             return NotImplemented
 
@@ -116,7 +130,7 @@ class Array:
         # to promote in the spec (even if the NumPy array operator would
         # promote them).
         res_dtype = _result_type(self.dtype, other.dtype)
-        if op.startswith('__i'):
+        if op.startswith("__i"):
             # Note: NumPy will allow in-place operators in some cases where
             # the type promoted operator does not match the left-hand side
             # operand. For example,
@@ -126,7 +140,9 @@ class Array:
 
             # The spec explicitly disallows this.
             if res_dtype != self.dtype:
-                raise TypeError(f"Cannot perform {op} with dtypes {self.dtype} and {other.dtype}")
+                raise TypeError(
+                    f"Cannot perform {op} with dtypes {self.dtype} and {other.dtype}"
+                )
 
         return other
 
@@ -142,13 +158,19 @@ class Array:
         """
         if isinstance(scalar, bool):
             if self.dtype not in _boolean_dtypes:
-                raise TypeError("Python bool scalars can only be promoted with bool arrays")
+                raise TypeError(
+                    "Python bool scalars can only be promoted with bool arrays"
+                )
         elif isinstance(scalar, int):
             if self.dtype in _boolean_dtypes:
-                raise TypeError("Python int scalars cannot be promoted with bool arrays")
+                raise TypeError(
+                    "Python int scalars cannot be promoted with bool arrays"
+                )
         elif isinstance(scalar, float):
             if self.dtype not in _floating_dtypes:
-                raise TypeError("Python float scalars can only be promoted with floating-point arrays.")
+                raise TypeError(
+                    "Python float scalars can only be promoted with floating-point arrays."
+                )
         else:
             raise TypeError("'scalar' must be a Python scalar")
 
@@ -253,7 +275,9 @@ class Array:
                 except TypeError:
                     return key
                 if not (-size <= key.start <= max(0, size - 1)):
-                    raise IndexError("Slices with out-of-bounds start are not allowed in the array API namespace")
+                    raise IndexError(
+                        "Slices with out-of-bounds start are not allowed in the array API namespace"
+                    )
             if key.stop is not None:
                 try:
                     operator.index(key.stop)
@@ -269,12 +293,20 @@ class Array:
             key = tuple(Array._validate_index(idx, None) for idx in key)
 
             for idx in key:
-                if isinstance(idx, np.ndarray) and idx.dtype in _boolean_dtypes or isinstance(idx, (bool, np.bool_)):
+                if (
+                    isinstance(idx, np.ndarray)
+                    and idx.dtype in _boolean_dtypes
+                    or isinstance(idx, (bool, np.bool_))
+                ):
                     if len(key) == 1:
                         return key
-                    raise IndexError("Boolean array indices combined with other indices are not allowed in the array API namespace")
+                    raise IndexError(
+                        "Boolean array indices combined with other indices are not allowed in the array API namespace"
+                    )
                 if isinstance(idx, tuple):
-                    raise IndexError("Nested tuple indices are not allowed in the array API namespace")
+                    raise IndexError(
+                        "Nested tuple indices are not allowed in the array API namespace"
+                    )
 
             if shape is None:
                 return key
@@ -283,7 +315,9 @@ class Array:
                 return key
             ellipsis_i = key.index(...) if n_ellipsis else len(key)
 
-            for idx, size in list(zip(key[:ellipsis_i], shape)) + list(zip(key[:ellipsis_i:-1], shape[:ellipsis_i:-1])):
+            for idx, size in list(zip(key[:ellipsis_i], shape)) + list(
+                zip(key[:ellipsis_i:-1], shape[:ellipsis_i:-1])
+            ):
                 Array._validate_index(idx, (size,))
             return key
         elif isinstance(key, bool):
@@ -291,18 +325,24 @@ class Array:
         elif isinstance(key, Array):
             if key.dtype in _integer_dtypes:
                 if key.ndim != 0:
-                    raise IndexError("Non-zero dimensional integer array indices are not allowed in the array API namespace")
+                    raise IndexError(
+                        "Non-zero dimensional integer array indices are not allowed in the array API namespace"
+                    )
             return key._array
         elif key is Ellipsis:
             return key
         elif key is None:
-            raise IndexError("newaxis indices are not allowed in the array API namespace")
+            raise IndexError(
+                "newaxis indices are not allowed in the array API namespace"
+            )
         try:
             return operator.index(key)
         except TypeError:
             # Note: This also omits boolean arrays that are not already in
             # Array() form, like a list of booleans.
-            raise IndexError("Only integers, slices (`:`), ellipsis (`...`), and boolean arrays are valid indices in the array API namespace")
+            raise IndexError(
+                "Only integers, slices (`:`), ellipsis (`...`), and boolean arrays are valid indices in the array API namespace"
+            )
 
     # Everything below this line is required by the spec.
 
@@ -311,7 +351,7 @@ class Array:
         Performs the operation __abs__.
         """
         if self.dtype not in _numeric_dtypes:
-            raise TypeError('Only numeric dtypes are allowed in __abs__')
+            raise TypeError("Only numeric dtypes are allowed in __abs__")
         res = self._array.__abs__()
         return self.__class__._new(res)
 
@@ -319,7 +359,7 @@ class Array:
         """
         Performs the operation __add__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__add__')
+        other = self._check_allowed_dtypes(other, "numeric", "__add__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -330,15 +370,17 @@ class Array:
         """
         Performs the operation __and__.
         """
-        other = self._check_allowed_dtypes(other, 'integer or boolean', '__and__')
+        other = self._check_allowed_dtypes(other, "integer or boolean", "__and__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
         res = self._array.__and__(other._array)
         return self.__class__._new(res)
 
-    def __array_namespace__(self: Array, /, *, api_version: Optional[str] = None) -> object:
-        if api_version is not None and not api_version.startswith('2021.'):
+    def __array_namespace__(
+        self: Array, /, *, api_version: Optional[str] = None
+    ) -> object:
+        if api_version is not None and not api_version.startswith("2021."):
             raise ValueError(f"Unrecognized array API version: {api_version!r}")
         return array_api
 
@@ -373,7 +415,7 @@ class Array:
         """
         # Even though "all" dtypes are allowed, we still require them to be
         # promotable with each other.
-        other = self._check_allowed_dtypes(other, 'all', '__eq__')
+        other = self._check_allowed_dtypes(other, "all", "__eq__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -394,7 +436,7 @@ class Array:
         """
         Performs the operation __floordiv__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__floordiv__')
+        other = self._check_allowed_dtypes(other, "numeric", "__floordiv__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -405,14 +447,20 @@ class Array:
         """
         Performs the operation __ge__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__ge__')
+        other = self._check_allowed_dtypes(other, "numeric", "__ge__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
         res = self._array.__ge__(other._array)
         return self.__class__._new(res)
 
-    def __getitem__(self: Array, key: Union[int, slice, ellipsis, Tuple[Union[int, slice, ellipsis], ...], Array], /) -> Array:
+    def __getitem__(
+        self: Array,
+        key: Union[
+            int, slice, ellipsis, Tuple[Union[int, slice, ellipsis], ...], Array
+        ],
+        /,
+    ) -> Array:
         """
         Performs the operation __getitem__.
         """
@@ -426,7 +474,7 @@ class Array:
         """
         Performs the operation __gt__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__gt__')
+        other = self._check_allowed_dtypes(other, "numeric", "__gt__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -448,7 +496,7 @@ class Array:
         Performs the operation __invert__.
         """
         if self.dtype not in _integer_or_boolean_dtypes:
-            raise TypeError('Only integer or boolean dtypes are allowed in __invert__')
+            raise TypeError("Only integer or boolean dtypes are allowed in __invert__")
         res = self._array.__invert__()
         return self.__class__._new(res)
 
@@ -456,7 +504,7 @@ class Array:
         """
         Performs the operation __le__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__le__')
+        other = self._check_allowed_dtypes(other, "numeric", "__le__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -474,7 +522,7 @@ class Array:
         """
         Performs the operation __lshift__.
         """
-        other = self._check_allowed_dtypes(other, 'integer', '__lshift__')
+        other = self._check_allowed_dtypes(other, "integer", "__lshift__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -485,7 +533,7 @@ class Array:
         """
         Performs the operation __lt__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__lt__')
+        other = self._check_allowed_dtypes(other, "numeric", "__lt__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -498,7 +546,7 @@ class Array:
         """
         # matmul is not defined for scalars, but without this, we may get
         # the wrong error message from asarray.
-        other = self._check_allowed_dtypes(other, 'numeric', '__matmul__')
+        other = self._check_allowed_dtypes(other, "numeric", "__matmul__")
         if other is NotImplemented:
             return other
         res = self._array.__matmul__(other._array)
@@ -508,7 +556,7 @@ class Array:
         """
         Performs the operation __mod__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__mod__')
+        other = self._check_allowed_dtypes(other, "numeric", "__mod__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -519,7 +567,7 @@ class Array:
         """
         Performs the operation __mul__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__mul__')
+        other = self._check_allowed_dtypes(other, "numeric", "__mul__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -530,7 +578,7 @@ class Array:
         """
         Performs the operation __ne__.
         """
-        other = self._check_allowed_dtypes(other, 'all', '__ne__')
+        other = self._check_allowed_dtypes(other, "all", "__ne__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -542,7 +590,7 @@ class Array:
         Performs the operation __neg__.
         """
         if self.dtype not in _numeric_dtypes:
-            raise TypeError('Only numeric dtypes are allowed in __neg__')
+            raise TypeError("Only numeric dtypes are allowed in __neg__")
         res = self._array.__neg__()
         return self.__class__._new(res)
 
@@ -550,7 +598,7 @@ class Array:
         """
         Performs the operation __or__.
         """
-        other = self._check_allowed_dtypes(other, 'integer or boolean', '__or__')
+        other = self._check_allowed_dtypes(other, "integer or boolean", "__or__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -562,7 +610,7 @@ class Array:
         Performs the operation __pos__.
         """
         if self.dtype not in _numeric_dtypes:
-            raise TypeError('Only numeric dtypes are allowed in __pos__')
+            raise TypeError("Only numeric dtypes are allowed in __pos__")
         res = self._array.__pos__()
         return self.__class__._new(res)
 
@@ -574,7 +622,7 @@ class Array:
         """
         from ._elementwise_functions import pow
 
-        other = self._check_allowed_dtypes(other, 'floating-point', '__pow__')
+        other = self._check_allowed_dtypes(other, "floating-point", "__pow__")
         if other is NotImplemented:
             return other
         # Note: NumPy's __pow__ does not follow type promotion rules for 0-d
@@ -585,14 +633,21 @@ class Array:
         """
         Performs the operation __rshift__.
         """
-        other = self._check_allowed_dtypes(other, 'integer', '__rshift__')
+        other = self._check_allowed_dtypes(other, "integer", "__rshift__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
         res = self._array.__rshift__(other._array)
         return self.__class__._new(res)
 
-    def __setitem__(self, key: Union[int, slice, ellipsis, Tuple[Union[int, slice, ellipsis], ...], Array], value: Union[int, float, bool, Array], /) -> Array:
+    def __setitem__(
+        self,
+        key: Union[
+            int, slice, ellipsis, Tuple[Union[int, slice, ellipsis], ...], Array
+        ],
+        value: Union[int, float, bool, Array],
+        /,
+    ) -> Array:
         """
         Performs the operation __setitem__.
         """
@@ -605,7 +660,7 @@ class Array:
         """
         Performs the operation __sub__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__sub__')
+        other = self._check_allowed_dtypes(other, "numeric", "__sub__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -618,7 +673,7 @@ class Array:
         """
         Performs the operation __truediv__.
         """
-        other = self._check_allowed_dtypes(other, 'floating-point', '__truediv__')
+        other = self._check_allowed_dtypes(other, "floating-point", "__truediv__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -629,7 +684,7 @@ class Array:
         """
         Performs the operation __xor__.
         """
-        other = self._check_allowed_dtypes(other, 'integer or boolean', '__xor__')
+        other = self._check_allowed_dtypes(other, "integer or boolean", "__xor__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -640,7 +695,7 @@ class Array:
         """
         Performs the operation __iadd__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__iadd__')
+        other = self._check_allowed_dtypes(other, "numeric", "__iadd__")
         if other is NotImplemented:
             return other
         self._array.__iadd__(other._array)
@@ -650,7 +705,7 @@ class Array:
         """
         Performs the operation __radd__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__radd__')
+        other = self._check_allowed_dtypes(other, "numeric", "__radd__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -661,7 +716,7 @@ class Array:
         """
         Performs the operation __iand__.
         """
-        other = self._check_allowed_dtypes(other, 'integer or boolean', '__iand__')
+        other = self._check_allowed_dtypes(other, "integer or boolean", "__iand__")
         if other is NotImplemented:
             return other
         self._array.__iand__(other._array)
@@ -671,7 +726,7 @@ class Array:
         """
         Performs the operation __rand__.
         """
-        other = self._check_allowed_dtypes(other, 'integer or boolean', '__rand__')
+        other = self._check_allowed_dtypes(other, "integer or boolean", "__rand__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -682,7 +737,7 @@ class Array:
         """
         Performs the operation __ifloordiv__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__ifloordiv__')
+        other = self._check_allowed_dtypes(other, "numeric", "__ifloordiv__")
         if other is NotImplemented:
             return other
         self._array.__ifloordiv__(other._array)
@@ -692,7 +747,7 @@ class Array:
         """
         Performs the operation __rfloordiv__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__rfloordiv__')
+        other = self._check_allowed_dtypes(other, "numeric", "__rfloordiv__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -703,7 +758,7 @@ class Array:
         """
         Performs the operation __ilshift__.
         """
-        other = self._check_allowed_dtypes(other, 'integer', '__ilshift__')
+        other = self._check_allowed_dtypes(other, "integer", "__ilshift__")
         if other is NotImplemented:
             return other
         self._array.__ilshift__(other._array)
@@ -713,7 +768,7 @@ class Array:
         """
         Performs the operation __rlshift__.
         """
-        other = self._check_allowed_dtypes(other, 'integer', '__rlshift__')
+        other = self._check_allowed_dtypes(other, "integer", "__rlshift__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -728,7 +783,7 @@ class Array:
 
         # matmul is not defined for scalars, but without this, we may get
         # the wrong error message from asarray.
-        other = self._check_allowed_dtypes(other, 'numeric', '__imatmul__')
+        other = self._check_allowed_dtypes(other, "numeric", "__imatmul__")
         if other is NotImplemented:
             return other
 
@@ -748,7 +803,7 @@ class Array:
         """
         # matmul is not defined for scalars, but without this, we may get
         # the wrong error message from asarray.
-        other = self._check_allowed_dtypes(other, 'numeric', '__rmatmul__')
+        other = self._check_allowed_dtypes(other, "numeric", "__rmatmul__")
         if other is NotImplemented:
             return other
         res = self._array.__rmatmul__(other._array)
@@ -758,7 +813,7 @@ class Array:
         """
         Performs the operation __imod__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__imod__')
+        other = self._check_allowed_dtypes(other, "numeric", "__imod__")
         if other is NotImplemented:
             return other
         self._array.__imod__(other._array)
@@ -768,7 +823,7 @@ class Array:
         """
         Performs the operation __rmod__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__rmod__')
+        other = self._check_allowed_dtypes(other, "numeric", "__rmod__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -779,7 +834,7 @@ class Array:
         """
         Performs the operation __imul__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__imul__')
+        other = self._check_allowed_dtypes(other, "numeric", "__imul__")
         if other is NotImplemented:
             return other
         self._array.__imul__(other._array)
@@ -789,7 +844,7 @@ class Array:
         """
         Performs the operation __rmul__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__rmul__')
+        other = self._check_allowed_dtypes(other, "numeric", "__rmul__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -800,7 +855,7 @@ class Array:
         """
         Performs the operation __ior__.
         """
-        other = self._check_allowed_dtypes(other, 'integer or boolean', '__ior__')
+        other = self._check_allowed_dtypes(other, "integer or boolean", "__ior__")
         if other is NotImplemented:
             return other
         self._array.__ior__(other._array)
@@ -810,7 +865,7 @@ class Array:
         """
         Performs the operation __ror__.
         """
-        other = self._check_allowed_dtypes(other, 'integer or boolean', '__ror__')
+        other = self._check_allowed_dtypes(other, "integer or boolean", "__ror__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -821,7 +876,7 @@ class Array:
         """
         Performs the operation __ipow__.
         """
-        other = self._check_allowed_dtypes(other, 'floating-point', '__ipow__')
+        other = self._check_allowed_dtypes(other, "floating-point", "__ipow__")
         if other is NotImplemented:
             return other
         self._array.__ipow__(other._array)
@@ -833,7 +888,7 @@ class Array:
         """
         from ._elementwise_functions import pow
 
-        other = self._check_allowed_dtypes(other, 'floating-point', '__rpow__')
+        other = self._check_allowed_dtypes(other, "floating-point", "__rpow__")
         if other is NotImplemented:
             return other
         # Note: NumPy's __pow__ does not follow the spec type promotion rules
@@ -844,7 +899,7 @@ class Array:
         """
         Performs the operation __irshift__.
         """
-        other = self._check_allowed_dtypes(other, 'integer', '__irshift__')
+        other = self._check_allowed_dtypes(other, "integer", "__irshift__")
         if other is NotImplemented:
             return other
         self._array.__irshift__(other._array)
@@ -854,7 +909,7 @@ class Array:
         """
         Performs the operation __rrshift__.
         """
-        other = self._check_allowed_dtypes(other, 'integer', '__rrshift__')
+        other = self._check_allowed_dtypes(other, "integer", "__rrshift__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -865,7 +920,7 @@ class Array:
         """
         Performs the operation __isub__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__isub__')
+        other = self._check_allowed_dtypes(other, "numeric", "__isub__")
         if other is NotImplemented:
             return other
         self._array.__isub__(other._array)
@@ -875,7 +930,7 @@ class Array:
         """
         Performs the operation __rsub__.
         """
-        other = self._check_allowed_dtypes(other, 'numeric', '__rsub__')
+        other = self._check_allowed_dtypes(other, "numeric", "__rsub__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -886,7 +941,7 @@ class Array:
         """
         Performs the operation __itruediv__.
         """
-        other = self._check_allowed_dtypes(other, 'floating-point', '__itruediv__')
+        other = self._check_allowed_dtypes(other, "floating-point", "__itruediv__")
         if other is NotImplemented:
             return other
         self._array.__itruediv__(other._array)
@@ -896,7 +951,7 @@ class Array:
         """
         Performs the operation __rtruediv__.
         """
-        other = self._check_allowed_dtypes(other, 'floating-point', '__rtruediv__')
+        other = self._check_allowed_dtypes(other, "floating-point", "__rtruediv__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -907,7 +962,7 @@ class Array:
         """
         Performs the operation __ixor__.
         """
-        other = self._check_allowed_dtypes(other, 'integer or boolean', '__ixor__')
+        other = self._check_allowed_dtypes(other, "integer or boolean", "__ixor__")
         if other is NotImplemented:
             return other
         self._array.__ixor__(other._array)
@@ -917,7 +972,7 @@ class Array:
         """
         Performs the operation __rxor__.
         """
-        other = self._check_allowed_dtypes(other, 'integer or boolean', '__rxor__')
+        other = self._check_allowed_dtypes(other, "integer or boolean", "__rxor__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -935,7 +990,7 @@ class Array:
 
     @property
     def device(self) -> Device:
-        return 'cpu'
+        return "cpu"
 
     @property
     def ndim(self) -> int:
-- 
cgit v1.2.1


From d5956c170b07cf26b05c921d810dc387d7e819da Mon Sep 17 00:00:00 2001
From: Aaron Meurer <asmeurer@gmail.com>
Date: Thu, 12 Aug 2021 15:22:58 -0600
Subject: Fix the return annotation for numpy.array_api.Array.__setitem__

---
 numpy/array_api/_array_object.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'numpy/array_api/_array_object.py')

diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py
index 0f511a577..2d746e78b 100644
--- a/numpy/array_api/_array_object.py
+++ b/numpy/array_api/_array_object.py
@@ -647,7 +647,7 @@ class Array:
         ],
         value: Union[int, float, bool, Array],
         /,
-    ) -> Array:
+    ) -> None:
         """
         Performs the operation __setitem__.
         """
-- 
cgit v1.2.1