Adds device keyword argument to astype

Author: ndgrigorian

dpctl/tensor/_copy_utils.py

@@ -26,6 +26,7 @@
 import dpctl.utils
 from dpctl.tensor._data_types import _get_dtype
 from dpctl.tensor._device import normalize_queue_device
+from dpctl.tensor._type_utils import _dtype_supported_by_device_impl
 
 __doc__ = (
     "Implementation module for copy- and cast- operations on "
@@ -121,7 +122,7 @@ def from_numpy(np_ary, device=None, usm_type="device", sycl_queue=None):
             output array is created. Device can be specified by a
             a filter selector string, an instance of
             :class:`dpctl.SyclDevice`, an instance of
-            :class:`dpctl.SyclQueue`, an instance of
+            :class:`dpctl.SyclQueue`, or an instance of
             :class:`dpctl.tensor.Device`. If the value is `None`,
             returned array is created on the default-selected device.
             Default: `None`.
@@ -564,9 +565,11 @@ def copy(usm_ary, order="K"):
     return R
 
 
-def astype(usm_ary, newdtype, order="K", casting="unsafe", copy=True):
+def astype(
+    usm_ary, newdtype, /, order="K", casting="unsafe", *, copy=True, device=None
+):
     """ astype(array, new_dtype, order="K", casting="unsafe", \
-            copy=True)
+            copy=True, device=None)
 
     Returns a copy of the :class:`dpctl.tensor.usm_ndarray`, cast to a
     specified type.
@@ -576,7 +579,8 @@ def astype(usm_ary, newdtype, order="K", casting="unsafe", copy=True):
             An input array.
         new_dtype (dtype):
             The data type of the resulting array. If `None`, gives default
-            floating point type supported by device where `array` is allocated.
+            floating point type supported by device where the resulting array
+            will be located.
         order ({"C", "F", "A", "K"}, optional):
             Controls memory layout of the resulting array if a copy
             is returned.
@@ -587,6 +591,14 @@ def astype(usm_ary, newdtype, order="K", casting="unsafe", copy=True):
             By default, `astype` always returns a newly allocated array.
             If this keyword is set to `False`, a view of the input array
             may be returned when possible.
+        device (object): array API specification of device where the
+            output array is created. Device can be specified by a
+            a filter selector string, an instance of
+            :class:`dpctl.SyclDevice`, an instance of
+            :class:`dpctl.SyclQueue`, or an instance of
+            :class:`dpctl.tensor.Device`. If the value is `None`,
+            returned array is created on the same device as `array`.
+            Default: `None`.
 
     Returns:
         usm_ndarray:
@@ -604,7 +616,25 @@ def astype(usm_ary, newdtype, order="K", casting="unsafe", copy=True):
         )
     order = order[0].upper()
     ary_dtype = usm_ary.dtype
-    target_dtype = _get_dtype(newdtype, usm_ary.sycl_queue)
+    if device is not None:
+        if not isinstance(device, dpctl.SyclQueue):
+            if isinstance(device, dpt.Device):
+                device = device.sycl_queue
+            else:
+                device = dpt.Device.create_device(device).sycl_queue
+        d = device.sycl_device
+        target_dtype = _get_dtype(newdtype, device)
+        if not _dtype_supported_by_device_impl(
+            target_dtype, d.has_aspect_fp16, d.has_aspect_fp64
+        ):
+            raise ValueError(
+                f"Requested dtype `{target_dtype}` is not supported by the "
+                "target device"
+            )
+        usm_ary = usm_ary.to_device(device)
+    else:
+        target_dtype = _get_dtype(newdtype, usm_ary.sycl_queue)
+
     if not dpt.can_cast(ary_dtype, target_dtype, casting=casting):
         raise TypeError(
             f"Can not cast from {ary_dtype} to {newdtype} "

dpctl/tensor/_type_utils.py

@@ -13,6 +13,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from __future__ import annotations
 
 import numpy as np
 

dpctl/tests/test_usm_ndarray_ctor.py

@@ -1313,6 +1313,20 @@ def test_astype_invalid_order():
         dpt.astype(X, "i4", order="WRONG")
 
 
+def test_astype_device():
+    get_queue_or_skip()
+    q1 = dpctl.SyclQueue()
+    q2 = dpctl.SyclQueue()
+
+    x = dpt.arange(5, dtype="i4", sycl_queue=q1)
+    r = dpt.astype(x, "f4")
+    assert r.sycl_queue == x.sycl_queue
+    assert r.sycl_device == x.sycl_device
+
+    r = dpt.astype(x, "f4", device=q2)
+    assert r.sycl_queue == q2
+
+
 def test_copy():
     try:
         X = dpt.usm_ndarray((5, 5), "i4")[2:4, 1:4]