Update

Author: Micky774

jax/experimental/array_api/_data_type_functions.py

@@ -11,12 +11,17 @@
 # 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 builtins
 import functools
-from typing import NamedTuple
+from typing import Any, NamedTuple
 import jax
 import jax.numpy as jnp
+from jax._src.lib import xla_client as xc
+from jax._src.sharding import Sharding
+from jax._src.api import device_put
 
 
 from jax.experimental.array_api._dtypes import (
@@ -124,9 +129,24 @@ def _promote_types(t1, t2):
     raise ValueError("No promotion path for {t1} & {t2}")
 
 
-def astype(x, dtype, /, *, copy=True):
-  return jnp.array(x, dtype=dtype, copy=copy)
-
+def astype(x, dtype, /, *, copy: builtins.bool | None = True, device: xc.Device | Sharding | None = None):
+  arr = jnp.array(x, dtype=dtype)
+  src_device = arr.devices().pop()
+  # TODO(micky774): refactor into a common utility with _place_array in gh-20175
+  if device is not None:
+    if copy is not None and not copy:
+      raise ValueError(
+        f"Specified {device=} which requires a copy since the source device "
+        f"is {repr(src_device)}, however copy=False. Set copy=True or "
+        "copy=None to perform the requested operation."
+      )
+    else:
+      return device_put(arr, device)
+  if copy:
+    # TODO(micky774): Remove if clause and replace with jnp.array(arr, copy=copy)
+    # when we support Numpy 2.0 copy semantics
+    return jnp.array(arr, copy=True)
+  return arr
 
 def can_cast(from_, to, /):
   if isinstance(from_, jax.Array):