Merge branch 'main' into typ_v4

Author: crusaderky

array_api_compat/common/_helpers.py

@@ -772,41 +772,27 @@ def _cupy_to_device(
     stream: int | Any | None = None,
 ) -> cp.ndarray:
     import cupy as cp
-    from cupy.cuda import Device as _Device  # pyright: ignore
-    from cupy.cuda import stream as stream_module  # pyright: ignore
-    from cupy_backends.cuda.api import runtime  # pyright: ignore
 
-    if device == x.device:
-        return x
-    elif device == "cpu":
+    if device == "cpu":
         # allowing us to use `to_device(x, "cpu")`
         # is useful for portable test swapping between
         # host and device backends
         return x.get()
-    elif not isinstance(device, _Device):
-        raise ValueError(f"Unsupported device {device!r}")
-    else:
-        # see cupy/cupy#5985 for the reason how we handle device/stream here
-        prev_device: Device = runtime.getDevice()  # pyright: ignore[reportUnknownMemberType]
-        prev_stream = None
-        if stream is not None:
-            prev_stream = stream_module.get_current_stream()  # pyright: ignore
-            # stream can be an int as specified in __dlpack__, or a CuPy stream
-            if isinstance(stream, int):
-                stream = cp.cuda.ExternalStream(stream)  # pyright: ignore
-            elif isinstance(stream, cp.cuda.Stream):  # pyright: ignore[reportUnknownMemberType]
-                pass
-            else:
-                raise ValueError("the input stream is not recognized")
-            stream.use()  # pyright: ignore[reportUnknownMemberType]
-        try:
-            runtime.setDevice(device.id)  # pyright: ignore[reportUnknownMemberType]
-            arr = x.copy()
-        finally:
-            runtime.setDevice(prev_device)  # pyright: ignore[reportUnknownMemberType]
-            if prev_stream is not None:
-                prev_stream.use()
-        return arr
+    if not isinstance(device, cp.cuda.Device):
+        raise TypeError(f"Unsupported device type {device!r}")
+
+    if stream is None:
+        with device:
+            return cp.asarray(x)
+
+    # stream can be an int as specified in __dlpack__, or a CuPy stream
+    if isinstance(stream, int):
+        stream = cp.cuda.ExternalStream(stream)
+    elif not isinstance(stream, cp.cuda.Stream):
+        raise TypeError(f"Unsupported stream type {stream!r}")
+
+    with device, stream:
+        return cp.asarray(x)
 
 
 def _torch_to_device(

array_api_compat/cupy/_aliases.py

@@ -63,8 +63,6 @@
 finfo = get_xp(cp)(_aliases.finfo)
 iinfo = get_xp(cp)(_aliases.iinfo)
 
-_copy_default = object()
-
 
 # asarray also adds the copy keyword, which is not present in numpy 1.0.
 def asarray(
@@ -83,25 +81,13 @@ def asarray(
     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)
+        if copy is None:
+            return cp.asarray(obj, dtype=dtype, **kwargs)
+        else:
+            res = cp.array(obj, dtype=dtype, copy=copy, **kwargs)
+            if not copy and res is not obj:
+                raise ValueError("Unable to avoid copy while creating an array as requested")
+            return res
 
 
 def astype(

cupy-xfails.txt

@@ -11,9 +11,6 @@ array_api_tests/test_array_object.py::test_scalar_casting[__index__(int64)]
 # testsuite bug (https://github.com/data-apis/array-api-tests/issues/172)
 array_api_tests/test_array_object.py::test_getitem
 
-# copy=False is not yet implemented
-array_api_tests/test_creation_functions.py::test_asarray_arrays
-
 # attributes are np.float32 instead of float
 # (see also https://github.com/data-apis/array-api/issues/405)
 array_api_tests/test_data_type_functions.py::test_finfo[float32]

tests/test_common.py

@@ -17,6 +17,7 @@
 from array_api_compat import (
     device, is_array_api_obj, is_lazy_array, is_writeable_array, size, to_device
 )
+from array_api_compat.common._helpers import _DASK_DEVICE
 from ._helpers import all_libraries, import_, wrapped_libraries, xfail
 
 
@@ -189,23 +190,26 @@ class C:
 
 
 @pytest.mark.parametrize("library", all_libraries)
-def test_device(library, request):
+def test_device_to_device(library, request):
     if library == "ndonnx":
-        xfail(request, reason="Needs ndonnx >=0.9.4")
+        xfail(request, reason="Stub raises ValueError")
+    if library == "sparse":
+        xfail(request, reason="No __array_namespace_info__()")
 
     xp = import_(library, wrapper=True)
+    devices = xp.__array_namespace_info__().devices()
 
-    # We can't test much for device() and to_device() other than that
-    # x.to_device(x.device) works.
-
+    # Default device
     x = xp.asarray([1, 2, 3])
     dev = device(x)
 
-    x2 = to_device(x, dev)
-    assert device(x2) == device(x)
-
-    x3 = xp.asarray(x, device=dev)
-    assert device(x3) == device(x)
+    for dev in devices:
+        if dev is None:  # JAX >=0.5.3
+            continue
+        if dev is _DASK_DEVICE:  # TODO this needs a better design
+            continue
+        y = to_device(x, dev)
+        assert device(y) == dev
 
 
 @pytest.mark.parametrize("library", wrapped_libraries)

tests/test_cupy.py

@@ -0,0 +1,22 @@
+import pytest
+from array_api_compat import device, to_device
+
+xp = pytest.importorskip("array_api_compat.cupy")
+from cupy.cuda import Stream
+
+
+def test_to_device_with_stream():
+    devices = xp.__array_namespace_info__().devices()
+    streams = [
+        Stream(),
+        Stream(non_blocking=True), 
+        Stream(null=True),
+        Stream(ptds=True), 
+        123,  # dlpack stream
+    ]
+
+    a = xp.asarray([1, 2, 3])
+    for dev in devices:
+        for stream in streams:
+            b = to_device(a, dev, stream=stream)
+            assert device(b) == dev