Support the copy keyword in asarray

.github/workflows/array-api-tests.yml

@@ -37,7 +37,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.9', '3.10', '3.11', '3.12']
 
     steps:
     - name: Checkout array-api-compat
@@ -55,16 +55,15 @@ jobs:
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
-      # NumPy 1.21 doesn't support Python 3.11. NumPy 2.0 doesn't support
-      # Python 3.8. There doesn't seem to be a way to put this in the numpy
-      # 1.21 config file.
-      if: "! ((matrix.python-version == '3.11' && inputs.package-name == 'numpy' && contains(inputs.package-version, '1.21')) || (matrix.python-version == '3.8' && inputs.package-name == 'numpy' && contains(inputs.xfails-file-extra, 'dev')))"
+      # NumPy 1.21 doesn't support Python 3.11. There doesn't seem to be a way
+      # to put this in the numpy 1.21 config file.
+      if: "! ((matrix.python-version == '3.11' || matrix.python-version == '3.12') && inputs.package-name == 'numpy' && contains(inputs.package-version, '1.21'))"
       run: |
         python -m pip install --upgrade pip
         python -m pip install '${{ inputs.package-name }} ${{ inputs.package-version }}' ${{ inputs.extra-requires }}
         python -m pip install -r ${GITHUB_WORKSPACE}/array-api-tests/requirements.txt
     - name: Run the array API testsuite (${{ inputs.package-name }})
-      if: "! ((matrix.python-version == '3.11' && inputs.package-name == 'numpy' && contains(inputs.package-version, '1.21')) || (matrix.python-version == '3.8' && inputs.package-name == 'numpy' && contains(inputs.xfails-file-extra, 'dev')))"
+      if: "! ((matrix.python-version == '3.11' || matrix.python-version == '3.12') && inputs.package-name == 'numpy' && contains(inputs.package-version, '1.21'))"
       env:
         ARRAY_API_TESTS_MODULE: array_api_compat.${{ inputs.module-name || inputs.package-name }}
         # This enables the NEP 50 type promotion behavior (without it a lot of

.github/workflows/docs-build.yml

@@ -3,7 +3,7 @@ name: Docs Build
 on: [push, pull_request]
 
 jobs:
-  build:
+  docs-build:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4

.github/workflows/docs-deploy.yml

@@ -6,7 +6,7 @@ on:
       - main
 
 jobs:
-  deploy:
+  docs-deploy:
     runs-on: ubuntu-latest
     environment:
       name: docs-deploy

.github/workflows/tests.yml

@@ -5,7 +5,13 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.9', '3.10', '3.11', '3.12']
+        numpy-version: ['1.21', '1.26', 'dev']
+        exclude:
+          - python-version: '3.11'
+            numpy-version: '1.21'
+          - python-version: '3.12'
+            numpy-version: '1.21'
       fail-fast: true
     steps:
       - uses: actions/checkout@v4
@@ -15,11 +21,21 @@ jobs:
       - name: Install Dependencies
         run: |
           python -m pip install --upgrade pip
-          python -m pip install pytest numpy torch dask[array] jax[cpu]
+          if [ "${{ matrix.numpy-version }}" == "dev" ]; then
+            PIP_EXTRA='numpy --pre --extra-index-url https://pypi.anaconda.org/scientific-python-nightly-wheels/simple'
+          elif [ "${{ matrix.numpy-version }}" == "1.21" ]; then
+            PIP_EXTRA='numpy==1.21.*'
+          else
+            PIP_EXTRA='numpy==1.26.*'
+          fi
+          python -m pip install -r requirements-dev.txt $PIP_EXTRA
 
       - name: Run Tests
         run: |
-          pytest
+          if [[ "${{ matrix.numpy-version }}" == "1.21" || "${{ matrix.numpy-version }}" == "dev" ]]; then
+             PYTEST_EXTRA=(-k "numpy and not jax and not torch and not dask")
+          fi
+          pytest -v "${PYTEST_EXTRA[@]}"
 
           # Make sure it installs
-          python setup.py install
+          python -m pip install .

array_api_compat/common/_aliases.py

@@ -6,18 +6,18 @@
 
 from typing import TYPE_CHECKING
 if TYPE_CHECKING:
-    import numpy as np
     from typing import Optional, Sequence, Tuple, Union
-    from ._typing import ndarray, Device, Dtype, NestedSequence, SupportsBufferProtocol
+    from ._typing import ndarray, Device, Dtype
 
 from typing import NamedTuple
-from types import ModuleType
 import inspect
 
-from ._helpers import _check_device, is_numpy_array, array_namespace
+from ._helpers import _check_device
 
 # These functions are modified from the NumPy versions.
 
+# Creation functions add the device keyword (which does nothing for NumPy)
+
 def arange(
     start: Union[int, float],
     /,
@@ -268,90 +268,6 @@ def var(
 def permute_dims(x: ndarray, /, axes: Tuple[int, ...], xp) -> ndarray:
     return xp.transpose(x, axes)
 
-# Creation functions add the device keyword (which does nothing for NumPy)
-
-# asarray also adds the copy keyword
-def _asarray(
-    obj: Union[
-        ndarray,
-        bool,
-        int,
-        float,
-        NestedSequence[bool | int | float],
-        SupportsBufferProtocol,
-    ],
-    /,
-    *,
-    dtype: Optional[Dtype] = None,
-    device: Optional[Device] = None,
-    copy: "Optional[Union[bool, np._CopyMode]]" = None,
-    namespace = None,
-    **kwargs,
-) -> ndarray:
-    """
-    Array API compatibility wrapper for asarray().
-
-    See the corresponding documentation in NumPy/CuPy and/or the array API
-    specification for more details.
-
-    """
-    if namespace is None:
-        try:
-            xp = array_namespace(obj, _use_compat=False)
-        except ValueError:
-            # TODO: What about lists of arrays?
-            raise ValueError("A namespace must be specified for asarray() with non-array input")
-    elif isinstance(namespace, ModuleType):
-        xp = namespace
-    elif namespace == 'numpy':
-        import numpy as xp
-    elif namespace == 'cupy':
-        import cupy as xp
-    elif namespace == 'dask.array':
-        import dask.array as xp
-    else:
-        raise ValueError("Unrecognized namespace argument to asarray()")
-
-    _check_device(xp, device)
-    if is_numpy_array(obj):
-        import numpy as np
-        if hasattr(np, '_CopyMode'):
-            # Not present in older NumPys
-            COPY_FALSE = (False, np._CopyMode.IF_NEEDED)
-            COPY_TRUE = (True, np._CopyMode.ALWAYS)
-        else:
-            COPY_FALSE = (False,)
-            COPY_TRUE = (True,)
-    else:
-        COPY_FALSE = (False,)
-        COPY_TRUE = (True,)
-    if copy in COPY_FALSE and namespace != "dask.array":
-        # copy=False is not yet implemented in xp.asarray
-        raise NotImplementedError("copy=False is not yet implemented")
-    if (hasattr(xp, "ndarray") and isinstance(obj, xp.ndarray)):
-        if dtype is not None and obj.dtype != dtype:
-            copy = True
-        if copy in COPY_TRUE:
-            return xp.array(obj, copy=True, dtype=dtype)
-        return obj
-    elif namespace == "dask.array":
-        if copy in COPY_TRUE:
-            if dtype is None:
-                return obj.copy()
-            # Go through numpy, since dask copy is no-op by default
-            import numpy as np
-            obj = np.array(obj, dtype=dtype, copy=True)
-            return xp.array(obj, dtype=dtype)
-        else:
-            import dask.array as da
-            import numpy as np
-            if not isinstance(obj, da.Array):
-                obj = np.asarray(obj, dtype=dtype)
-                return da.from_array(obj)
-            return obj
-
-    return xp.asarray(obj, dtype=dtype, **kwargs)
-
 # np.reshape calls the keyword argument 'newshape' instead of 'shape'
 def reshape(x: ndarray,
             /,

array_api_compat/cupy/_aliases.py

@@ -1,15 +1,14 @@
 from __future__ import annotations
 
-from functools import partial
-
 import cupy as cp
 
 from ..common import _aliases
 from .._internal import get_xp
 
-asarray = asarray_cupy = partial(_aliases._asarray, namespace='cupy')
-asarray.__doc__ = _aliases._asarray.__doc__
-del partial
+from typing import TYPE_CHECKING
+if TYPE_CHECKING:
+    from typing import Optional, Union
+    from ._typing import ndarray, Device, Dtype, NestedSequence, SupportsBufferProtocol
 
 bool = cp.bool_
 
@@ -62,6 +61,52 @@
 matrix_transpose = get_xp(cp)(_aliases.matrix_transpose)
 tensordot = get_xp(cp)(_aliases.tensordot)
 
+_copy_default = object()
+
+# asarray also adds the copy keyword, which is not present in numpy 1.0.
+def asarray(
+    obj: Union[
+        ndarray,
+        bool,
+        int,
+        float,
+        NestedSequence[bool | int | float],
+        SupportsBufferProtocol,
+    ],
+    /,
+    *,
+    dtype: Optional[Dtype] = None,
+    device: Optional[Device] = None,
+    copy: Optional[bool] = _copy_default,
+    **kwargs,
+) -> ndarray:
+    """
+    Array API compatibility wrapper for asarray().
+
+    See the corresponding documentation in the array library and/or the array API
+    specification for more details.
+    """
+    with cp.cuda.Device(device):
+        # cupy is like NumPy 1.26 (except without _CopyMode). See the comments
+        # in asarray in numpy/_aliases.py.
+        if copy is not _copy_default:
+            # A future version of CuPy will change the meaning of copy=False
+            # to mean no-copy. We don't know for certain what version it will
+            # be yet, so to avoid breaking that version, we use a different
+            # default value for copy so asarray(obj) with no copy kwarg will
+            # always do the copy-if-needed behavior.
+
+            # This will still need to be updated to remove the
+            # NotImplementedError for copy=False, but at least this won't
+            # break the default or existing behavior.
+            if copy is None:
+                copy = False
+            elif copy is False:
+                raise NotImplementedError("asarray(copy=False) is not yet supported in cupy")
+            kwargs['copy'] = copy
+
+        return cp.array(obj, dtype=dtype, **kwargs)
+
 # These functions are completely new here. If the library already has them
 # (i.e., numpy 2.0), use the library version instead of our wrapper.
 if hasattr(cp, 'vecdot'):
@@ -73,7 +118,7 @@
 else:
     isdtype = get_xp(cp)(_aliases.isdtype)
 
-__all__ = _aliases.__all__ + ['asarray', 'asarray_cupy', 'bool', 'acos',
+__all__ = _aliases.__all__ + ['asarray', 'bool', 'acos',
                               'acosh', 'asin', 'asinh', 'atan', 'atan2',
                               'atanh', 'bitwise_left_shift', 'bitwise_invert',
                               'bitwise_right_shift', 'concat', 'pow']

array_api_compat/dask/array/_aliases.py

@@ -37,7 +37,7 @@
 if TYPE_CHECKING:
     from typing import Optional, Union
 
-    from ...common._typing import Device, Dtype, Array
+    from ...common._typing import Device, Dtype, Array, NestedSequence, SupportsBufferProtocol
 
 import dask.array as da
 
@@ -76,10 +76,6 @@ def _dask_arange(
 arange = get_xp(da)(_dask_arange)
 eye = get_xp(da)(_aliases.eye)
 
-from functools import partial
-asarray = partial(_aliases._asarray, namespace='dask.array')
-asarray.__doc__ = _aliases._asarray.__doc__
-
 linspace = get_xp(da)(_aliases.linspace)
 eye = get_xp(da)(_aliases.eye)
 UniqueAllResult = get_xp(da)(_aliases.UniqueAllResult)
@@ -113,6 +109,47 @@ def _dask_arange(
 matmul = get_xp(np)(_aliases.matmul)
 tensordot = get_xp(np)(_aliases.tensordot)
 
+
+# asarray also adds the copy keyword, which is not present in numpy 1.0.
+def asarray(
+    obj: Union[
+        Array,
+        bool,
+        int,
+        float,
+        NestedSequence[bool | int | float],
+        SupportsBufferProtocol,
+    ],
+    /,
+    *,
+    dtype: Optional[Dtype] = None,
+    device: Optional[Device] = None,
+    copy: "Optional[Union[bool, np._CopyMode]]" = None,
+    **kwargs,
+) -> Array:
+    """
+    Array API compatibility wrapper for asarray().
+
+    See the corresponding documentation in the array library and/or the array API
+    specification for more details.
+    """
+    if copy is False:
+        # copy=False is not yet implemented in dask
+        raise NotImplementedError("copy=False is not yet implemented")
+    elif copy is True:
+        if isinstance(obj, da.Array) and dtype is None:
+            return obj.copy()
+        # Go through numpy, since dask copy is no-op by default
+        obj = np.array(obj, dtype=dtype, copy=True)
+        return da.array(obj, dtype=dtype)
+    else:
+        if not isinstance(obj, da.Array) or dtype is not None and obj.dtype != dtype:
+            obj = np.asarray(obj, dtype=dtype)
+            return da.from_array(obj)
+        return obj
+
+    return da.asarray(obj, dtype=dtype, **kwargs)
+
 from dask.array import (
     # Element wise aliases
     arccos as acos,

array_api_compat/numpy/__init__.py

@@ -21,4 +21,10 @@
 
 from ..common._helpers import * # noqa: F403
 
+try:
+    # Used in asarray(). Not present in older versions.
+    from numpy import _CopyMode # noqa: F401
+except ImportError:
+    pass
+
 __array_api_version__ = '2022.12'