diff options
Diffstat (limited to 'numpy/array_api')
| -rw-r--r-- | numpy/array_api/__init__.py | 10 | ||||
| -rw-r--r-- | numpy/array_api/_array_object.py | 48 | ||||
| -rw-r--r-- | numpy/array_api/_creation_functions.py | 19 | ||||
| -rw-r--r-- | numpy/array_api/_data_type_functions.py | 7 | ||||
| -rw-r--r-- | numpy/array_api/_searching_functions.py | 1 | ||||
| -rw-r--r-- | numpy/array_api/_set_functions.py | 89 | ||||
| -rw-r--r-- | numpy/array_api/tests/test_array_object.py | 21 | ||||
| -rw-r--r-- | numpy/array_api/tests/test_creation_functions.py | 10 |
8 files changed, 156 insertions, 49 deletions
diff --git a/numpy/array_api/__init__.py b/numpy/array_api/__init__.py index 89f5e9cba..36e3f3ed5 100644 --- a/numpy/array_api/__init__.py +++ b/numpy/array_api/__init__.py @@ -136,7 +136,7 @@ from ._creation_functions import ( empty, empty_like, eye, - _from_dlpack, + from_dlpack, full, full_like, linspace, @@ -155,7 +155,7 @@ __all__ += [ "empty", "empty_like", "eye", - "_from_dlpack", + "from_dlpack", "full", "full_like", "linspace", @@ -169,6 +169,7 @@ __all__ += [ ] from ._data_type_functions import ( + astype, broadcast_arrays, broadcast_to, can_cast, @@ -178,6 +179,7 @@ from ._data_type_functions import ( ) __all__ += [ + "astype", "broadcast_arrays", "broadcast_to", "can_cast", @@ -358,9 +360,9 @@ from ._searching_functions import argmax, argmin, nonzero, where __all__ += ["argmax", "argmin", "nonzero", "where"] -from ._set_functions import unique +from ._set_functions import unique_all, unique_counts, unique_inverse, unique_values -__all__ += ["unique"] +__all__ += ["unique_all", "unique_counts", "unique_inverse", "unique_values"] from ._sorting_functions import argsort, sort diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py index ef66c5efd..dc74bb8c5 100644 --- a/numpy/array_api/_array_object.py +++ b/numpy/array_api/_array_object.py @@ -32,7 +32,7 @@ from ._dtypes import ( from typing import TYPE_CHECKING, Optional, Tuple, Union, Any if TYPE_CHECKING: - from ._typing import PyCapsule, Device, Dtype + from ._typing import Any, PyCapsule, Device, Dtype import numpy as np @@ -99,9 +99,13 @@ class Array: """ Performs the operation __repr__. """ - prefix = "Array(" suffix = f", dtype={self.dtype.name})" - mid = np.array2string(self._array, separator=', ', prefix=prefix, suffix=suffix) + if 0 in self.shape: + prefix = "empty(" + mid = str(self.shape) + else: + prefix = "Array(" + mid = np.array2string(self._array, separator=', ', prefix=prefix, suffix=suffix) return prefix + mid + suffix # These are various helper functions to make the array behavior match the @@ -244,6 +248,10 @@ class Array: The following cases are allowed by NumPy, but not specified by the array API specification: + - Indices to not include an implicit ellipsis at the end. That is, + every axis of an array must be explicitly indexed or an ellipsis + included. + - 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: @@ -270,6 +278,10 @@ class Array: return key if shape == (): return key + if len(shape) > 1: + raise IndexError( + "Multidimensional arrays must include an index for every axis or use an ellipsis" + ) size = shape[0] # Ensure invalid slice entries are passed through. if key.start is not None: @@ -277,7 +289,7 @@ class Array: operator.index(key.start) except TypeError: return key - if not (-size <= key.start <= max(0, size - 1)): + if not (-size <= key.start <= size): raise IndexError( "Slices with out-of-bounds start are not allowed in the array API namespace" ) @@ -322,6 +334,10 @@ class Array: zip(key[:ellipsis_i:-1], shape[:ellipsis_i:-1]) ): Array._validate_index(idx, (size,)) + if n_ellipsis == 0 and len(key) < len(shape): + raise IndexError( + "Multidimensional arrays must include an index for every axis or use an ellipsis" + ) return key elif isinstance(key, bool): return key @@ -339,7 +355,12 @@ class Array: "newaxis indices are not allowed in the array API namespace" ) try: - return operator.index(key) + key = operator.index(key) + if shape is not None and len(shape) > 1: + raise IndexError( + "Multidimensional arrays must include an index for every axis or use an ellipsis" + ) + return key except TypeError: # Note: This also omits boolean arrays that are not already in # Array() form, like a list of booleans. @@ -403,16 +424,14 @@ class Array: """ Performs the operation __dlpack__. """ - res = self._array.__dlpack__(stream=stream) - return self.__class__._new(res) + return self._array.__dlpack__(stream=stream) 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) + return self._array.__dlpack_device__() def __eq__(self: Array, other: Union[int, float, bool, Array], /) -> Array: """ @@ -527,13 +546,6 @@ class Array: 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__. - """ - return self._array.__len__() - def __lshift__(self: Array, other: Union[int, Array], /) -> Array: """ Performs the operation __lshift__. @@ -995,7 +1007,9 @@ class Array: res = self._array.__rxor__(other._array) return self.__class__._new(res) - def to_device(self: Array, device: Device, /) -> 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': return self raise ValueError(f"Unsupported device {device!r}") diff --git a/numpy/array_api/_creation_functions.py b/numpy/array_api/_creation_functions.py index c3644ac2c..23beec444 100644 --- a/numpy/array_api/_creation_functions.py +++ b/numpy/array_api/_creation_functions.py @@ -9,7 +9,6 @@ if TYPE_CHECKING: Device, Dtype, NestedSequence, - SupportsDLPack, SupportsBufferProtocol, ) from collections.abc import Sequence @@ -36,7 +35,6 @@ def asarray( int, float, NestedSequence[bool | int | float], - SupportsDLPack, SupportsBufferProtocol, ], /, @@ -60,7 +58,9 @@ def asarray( if copy is False: # Note: copy=False is not yet implemented in np.asarray raise NotImplementedError("copy=False is not yet implemented") - if isinstance(obj, Array) and (dtype is None or obj.dtype == dtype): + if isinstance(obj, Array): + if dtype is not None and obj.dtype != dtype: + copy = True if copy is True: return Array._new(np.array(obj._array, copy=True, dtype=dtype)) return obj @@ -151,9 +151,10 @@ def eye( return Array._new(np.eye(n_rows, M=n_cols, k=k, dtype=dtype)) -def _from_dlpack(x: object, /) -> Array: - # Note: dlpack support is not yet implemented on Array - raise NotImplementedError("DLPack support is not yet implemented") +def from_dlpack(x: object, /) -> Array: + from ._array_object import Array + + return Array._new(np._from_dlpack(x)) def full( @@ -240,6 +241,12 @@ def meshgrid(*arrays: Array, indexing: str = "xy") -> List[Array]: """ from ._array_object import Array + # Note: unlike np.meshgrid, only inputs with all the same dtype are + # allowed + + if len({a.dtype for a in arrays}) > 1: + raise ValueError("meshgrid inputs must all have the same dtype") + return [ Array._new(array) for array in np.meshgrid(*[a._array for a in arrays], indexing=indexing) diff --git a/numpy/array_api/_data_type_functions.py b/numpy/array_api/_data_type_functions.py index 7ccbe9469..e4d6db61b 100644 --- a/numpy/array_api/_data_type_functions.py +++ b/numpy/array_api/_data_type_functions.py @@ -13,6 +13,13 @@ if TYPE_CHECKING: import numpy as np +# Note: astype is a function, not an array method as in NumPy. +def astype(x: Array, dtype: Dtype, /, *, copy: bool = True) -> Array: + if not copy and dtype == x.dtype: + return x + return Array._new(x._array.astype(dtype=dtype, copy=copy)) + + def broadcast_arrays(*arrays: Array) -> List[Array]: """ Array API compatible wrapper for :py:func:`np.broadcast_arrays <numpy.broadcast_arrays>`. diff --git a/numpy/array_api/_searching_functions.py b/numpy/array_api/_searching_functions.py index 3dcef61c3..40f5a4d2e 100644 --- a/numpy/array_api/_searching_functions.py +++ b/numpy/array_api/_searching_functions.py @@ -43,4 +43,5 @@ def where(condition: Array, x1: Array, x2: Array, /) -> Array: """ # Call result type here just to raise on disallowed type combinations _result_type(x1.dtype, x2.dtype) + x1, x2 = Array._normalize_two_args(x1, x2) return Array._new(np.where(condition._array, x1._array, x2._array)) diff --git a/numpy/array_api/_set_functions.py b/numpy/array_api/_set_functions.py index 357f238f5..05ee7e555 100644 --- a/numpy/array_api/_set_functions.py +++ b/numpy/array_api/_set_functions.py @@ -2,19 +2,82 @@ from __future__ import annotations from ._array_object import Array -from typing import Tuple, Union +from typing import NamedTuple import numpy as np +# Note: np.unique() is split into four functions in the array API: +# unique_all, unique_counts, unique_inverse, and unique_values (this is done +# to remove polymorphic return types). -def unique( - x: Array, - /, - *, - return_counts: bool = False, - return_index: bool = False, - return_inverse: bool = False, -) -> Union[Array, Tuple[Array, ...]]: +# Note: The various unique() functions are supposed to return multiple NaNs. +# This does not match the NumPy behavior, however, this is currently left as a +# TODO in this implementation as this behavior may be reverted in np.unique(). +# See https://github.com/numpy/numpy/issues/20326. + +# Note: The functions here return a namedtuple (np.unique() returns a normal +# tuple). + +class UniqueAllResult(NamedTuple): + values: Array + indices: Array + inverse_indices: Array + counts: Array + + +class UniqueCountsResult(NamedTuple): + values: Array + counts: Array + + +class UniqueInverseResult(NamedTuple): + values: Array + inverse_indices: Array + + +def unique_all(x: Array, /) -> UniqueAllResult: + """ + Array API compatible wrapper for :py:func:`np.unique <numpy.unique>`. + + See its docstring for more information. + """ + res = np.unique( + x._array, + return_counts=True, + return_index=True, + return_inverse=True, + ) + + return UniqueAllResult(*[Array._new(i) for i in res]) + + +def unique_counts(x: Array, /) -> UniqueCountsResult: + res = np.unique( + x._array, + return_counts=True, + return_index=False, + return_inverse=False, + ) + + return UniqueCountsResult(*[Array._new(i) for i in res]) + + +def unique_inverse(x: Array, /) -> UniqueInverseResult: + """ + Array API compatible wrapper for :py:func:`np.unique <numpy.unique>`. + + See its docstring for more information. + """ + res = np.unique( + x._array, + return_counts=False, + return_index=False, + return_inverse=True, + ) + return UniqueInverseResult(*[Array._new(i) for i in res]) + + +def unique_values(x: Array, /) -> Array: """ Array API compatible wrapper for :py:func:`np.unique <numpy.unique>`. @@ -22,10 +85,8 @@ def unique( """ res = np.unique( x._array, - return_counts=return_counts, - return_index=return_index, - return_inverse=return_inverse, + return_counts=False, + return_index=False, + return_inverse=False, ) - if isinstance(res, tuple): - return tuple(Array._new(i) for i in res) return Array._new(res) diff --git a/numpy/array_api/tests/test_array_object.py b/numpy/array_api/tests/test_array_object.py index fb42cf621..12479d765 100644 --- a/numpy/array_api/tests/test_array_object.py +++ b/numpy/array_api/tests/test_array_object.py @@ -3,7 +3,7 @@ import operator from numpy.testing import assert_raises import numpy as np -from .. import ones, asarray, result_type +from .. import ones, asarray, result_type, all, equal from .._dtypes import ( _all_dtypes, _boolean_dtypes, @@ -39,18 +39,18 @@ def test_validate_index(): assert_raises(IndexError, lambda: a[:-4]) assert_raises(IndexError, lambda: a[:3:-1]) assert_raises(IndexError, lambda: a[:-5:-1]) - assert_raises(IndexError, lambda: a[3:]) + assert_raises(IndexError, lambda: a[4:]) assert_raises(IndexError, lambda: a[-4:]) - assert_raises(IndexError, lambda: a[3::-1]) + assert_raises(IndexError, lambda: a[4::-1]) assert_raises(IndexError, lambda: a[-4::-1]) assert_raises(IndexError, lambda: a[...,:5]) assert_raises(IndexError, lambda: a[...,:-5]) - assert_raises(IndexError, lambda: a[...,:4:-1]) + assert_raises(IndexError, lambda: a[...,:5:-1]) assert_raises(IndexError, lambda: a[...,:-6:-1]) - assert_raises(IndexError, lambda: a[...,4:]) + assert_raises(IndexError, lambda: a[...,5:]) assert_raises(IndexError, lambda: a[...,-5:]) - assert_raises(IndexError, lambda: a[...,4::-1]) + assert_raises(IndexError, lambda: a[...,5::-1]) assert_raises(IndexError, lambda: a[...,-5::-1]) # Boolean indices cannot be part of a larger tuple index @@ -74,6 +74,11 @@ def test_validate_index(): assert_raises(IndexError, lambda: a[None, ...]) assert_raises(IndexError, lambda: a[..., None]) + # Multiaxis indices must contain exactly as many indices as dimensions + assert_raises(IndexError, lambda: a[()]) + assert_raises(IndexError, lambda: a[0,]) + assert_raises(IndexError, lambda: a[0]) + assert_raises(IndexError, lambda: a[:]) def test_operators(): # For every operator, we test that it works for the required type @@ -291,8 +296,8 @@ def test_device_property(): a = ones((3, 4)) assert a.device == 'cpu' - assert np.array_equal(a.to_device('cpu'), a) + assert all(equal(a.to_device('cpu'), a)) assert_raises(ValueError, lambda: a.to_device('gpu')) - assert np.array_equal(asarray(a, device='cpu'), a) + assert all(equal(asarray(a, device='cpu'), a)) assert_raises(ValueError, lambda: asarray(a, device='gpu')) diff --git a/numpy/array_api/tests/test_creation_functions.py b/numpy/array_api/tests/test_creation_functions.py index 7b633eaf1..ebbb6aab3 100644 --- a/numpy/array_api/tests/test_creation_functions.py +++ b/numpy/array_api/tests/test_creation_functions.py @@ -11,11 +11,13 @@ from .._creation_functions import ( full, full_like, linspace, + meshgrid, ones, ones_like, zeros, zeros_like, ) +from .._dtypes import float32, float64 from .._array_object import Array @@ -124,3 +126,11 @@ def test_zeros_like_errors(): assert_raises(ValueError, lambda: zeros_like(asarray(1), device="gpu")) assert_raises(ValueError, lambda: zeros_like(asarray(1), dtype=int)) assert_raises(ValueError, lambda: zeros_like(asarray(1), dtype="i")) + +def test_meshgrid_dtype_errors(): + # Doesn't raise + meshgrid() + meshgrid(asarray([1.], dtype=float32)) + meshgrid(asarray([1.], dtype=float32), asarray([1.], dtype=float32)) + + assert_raises(ValueError, lambda: meshgrid(asarray([1.], dtype=float32), asarray([1.], dtype=float64))) |