Add basic support for dpctl.SyclQueue as a Numba type.

   - Adds a Numba type to represent dpctl.SyclQueue and
     infer it as an opaque pointer inside the compiler.

Author: Diptorup Deb

numba_dpex/core/datamodel/models.py

@@ -4,12 +4,13 @@
 
 from numba.core import datamodel, types
 from numba.core.datamodel.models import ArrayModel as DpnpNdArrayModel
-from numba.core.datamodel.models import PrimitiveModel, StructModel
+from numba.core.datamodel.models import OpaqueModel, PrimitiveModel, StructModel
 from numba.core.extending import register_model
 
-from numba_dpex.core.types import Array, DpnpNdArray, USMNdArray
 from numba_dpex.utils import address_space
 
+from ..types import Array, DpctlSyclQueue, DpnpNdArray, USMNdArray
+
 
 class GenericPointerModel(PrimitiveModel):
     def __init__(self, dmm, fe_type):
@@ -81,3 +82,7 @@ def _init_data_model_manager():
 # Register the DpnpNdArray type with the Numba ArrayModel
 register_model(DpnpNdArray)(DpnpNdArrayModel)
 dpex_data_model_manager.register(DpnpNdArray, DpnpNdArrayModel)
+
+# Register the DpctlSyclQueue type with Numba's OpaqueModel
+register_model(DpctlSyclQueue)(OpaqueModel)
+dpex_data_model_manager.register(DpctlSyclQueue, OpaqueModel)

numba_dpex/core/types/__init__.py

@@ -3,6 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 from .array_type import Array
+from .dpctl_types import DpctlSyclQueue
 from .dpnp_ndarray_type import DpnpNdArray
 from .numba_types_short_names import (
     b1,
@@ -31,6 +32,7 @@
 
 __all__ = [
     "Array",
+    "DpctlSyclQueue",
     "DpnpNdArray",
     "USMNdArray",
     "none",

numba_dpex/core/types/dpctl_types.py

@@ -0,0 +1,40 @@
+# SPDX-FileCopyrightText: 2020 - 2022 Intel Corporation
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from dpctl import SyclQueue
+from numba import types
+from numba.extending import NativeValue, box, type_callable, unbox
+
+
+class DpctlSyclQueue(types.Type):
+    """A Numba type to represent a dpctl.SyclQueue PyObject.
+
+    For now, a dpctl.SyclQueue is represented as a Numba opaque type that allows
+    passing in and using a SyclQueue object as an opaque pointer type inside
+    Numba.
+    """
+
+    def __init__(self):
+        super().__init__(name="DpctlSyclQueueType")
+
+
+sycl_queue_ty = DpctlSyclQueue()
+
+
+@type_callable(SyclQueue)
+def type_interval(context):
+    def typer():
+        return sycl_queue_ty
+
+    return typer
+
+
+@unbox(DpctlSyclQueue)
+def unbox_sycl_queue(typ, obj, c):
+    return NativeValue(obj)
+
+
+@box(DpctlSyclQueue)
+def box_pyobject(typ, val, c):
+    return val

numba_dpex/core/typing/typeof.py

@@ -2,15 +2,19 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
+from dpctl import SyclQueue
 from dpctl.tensor import usm_ndarray
 from dpnp import ndarray
+from numba.core import types
 from numba.extending import typeof_impl
 from numba.np import numpy_support
 
-from numba_dpex.core.types.dpnp_ndarray_type import DpnpNdArray
-from numba_dpex.core.types.usm_ndarray_type import USMNdArray
 from numba_dpex.utils import address_space
 
+from ..types.dpctl_types import sycl_queue_ty
+from ..types.dpnp_ndarray_type import DpnpNdArray
+from ..types.usm_ndarray_type import USMNdArray
+
 
 def _typeof_helper(val, array_class_type):
     """Creates a Numba type of the specified ``array_class_type`` for ``val``."""
@@ -90,3 +94,17 @@ def typeof_dpnp_ndarray(val, c):
     Returns: The Numba type corresponding to dpnp.ndarray
     """
     return _typeof_helper(val, DpnpNdArray)
+
+
+@typeof_impl.register(SyclQueue)
+def typeof_dpctl_sycl_queue(val, c):
+    """Registers the type inference implementation function for a
+    dpctl.SyclQueue PyObject.
+
+    Args:
+        val : An instance of dpctl.SyclQueue.
+        c : Unused argument used to be consistent with Numba API.
+
+    Returns: A numba_dpex.core.types.dpctl_types.DpctlSyclQueue instance.
+    """
+    return sycl_queue_ty

numba_dpex/tests/dpjit_tests/test_box_unbox.py

@@ -0,0 +1,27 @@
+# SPDX-FileCopyrightText: 2020 - 2022 Intel Corporation
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""
+Tests for boxing and unboxing of types supported inside dpjit
+"""
+
+import dpctl
+import pytest
+
+from numba_dpex import dpjit
+
+
+@pytest.mark.parametrize(
+    "obj",
+    [
+        pytest.param(dpctl.SyclQueue()),
+    ],
+)
+def test_boxing_unboxing(obj):
+    @dpjit
+    def func(a):
+        return a
+
+    o = func(obj)
+    assert id(o) == id(obj)