Merge pull request #1412 from IntelPython/merge_exp_spv_targt_into_sp…

…v_target

Completely remove numba_dpex.experimental module

numba_dpex/__init__.py

@@ -18,6 +18,7 @@
 
 from .kernel_api_impl.spirv import target as spirv_kernel_target
 from .numba_patches import patch_arrayexpr_tree_to_ir, patch_is_ufunc
+from .register_kernel_api_overloads import init_kernel_api_spirv_overloads
 
 
 def load_dpctl_sycl_interface():
@@ -136,11 +137,16 @@ def parse_sem_version(version_string: str) -> Tuple[int, int, int]:
 __version__ = get_versions()["version"]
 del get_versions
 
+# Initialize the kernel_api SPIRV overloads
+init_kernel_api_spirv_overloads()
+
 __all__ = types.__all__ + [
     "call_kernel",
+    "call_kernel_async",
     "device_func",
     "dpjit",
     "kernel",
+    "prange",
     "Range",
     "NdRange",
 ]

numba_dpex/core/decorators.py

@@ -13,9 +13,11 @@
 )
 
 from numba_dpex.core.targets.dpjit_target import DPEX_TARGET_NAME
-from numba_dpex.experimental.target import DPEX_KERNEL_EXP_TARGET_NAME
 from numba_dpex.kernel_api_impl.spirv.dispatcher import SPIRVKernelDispatcher
-from numba_dpex.kernel_api_impl.spirv.target import CompilationMode
+from numba_dpex.kernel_api_impl.spirv.target import (
+    SPIRV_TARGET_NAME,
+    CompilationMode,
+)
 
 
 def _parse_func_or_sig(signature_or_function):
@@ -154,7 +156,7 @@ def vecadd(item: kapi.Item, a, b, c):
 
     # dispatcher is a type:
     # <class 'numba_dpex.experimental.kernel_dispatcher.KernelDispatcher'>
-    dispatcher = resolve_dispatcher_from_str(DPEX_KERNEL_EXP_TARGET_NAME)
+    dispatcher = resolve_dispatcher_from_str(SPIRV_TARGET_NAME)
     if "_compilation_mode" in options:
         user_compilation_mode = options["_compilation_mode"]
         warn(
@@ -280,7 +282,7 @@ def another_kernel(nd_item: NdItem, a):
 
         dpex_exp.call_kernel(another_kernel, dpex.NdRange((N,), (N,)), b)
     """
-    dispatcher = resolve_dispatcher_from_str(DPEX_KERNEL_EXP_TARGET_NAME)
+    dispatcher = resolve_dispatcher_from_str(SPIRV_TARGET_NAME)
 
     if "_compilation_mode" in options:
         user_compilation_mode = options["_compilation_mode"]
@@ -342,4 +344,4 @@ def dpjit(*args, **kws):
 # add it to the decorator registry, this is so e.g. @overload can look up a
 # JIT function to do the compilation work.
 jit_registry[target_registry[DPEX_TARGET_NAME]] = dpjit
-jit_registry[target_registry[DPEX_KERNEL_EXP_TARGET_NAME]] = device_func
+jit_registry[target_registry[SPIRV_TARGET_NAME]] = device_func

numba_dpex/core/typing/typeof.py

@@ -8,11 +8,15 @@
 from numba.extending import typeof_impl
 from numba.np import numpy_support
 
+from numba_dpex.kernel_api import AtomicRef, Group, Item, LocalAccessor, NdItem
 from numba_dpex.kernel_api.ranges import NdRange, Range
 from numba_dpex.utils.constants import address_space
 
 from ..types.dpctl_types import DpctlSyclEvent, DpctlSyclQueue
 from ..types.dpnp_ndarray_type import DpnpNdArray
+from ..types.kernel_api.atomic_ref import AtomicRefType
+from ..types.kernel_api.index_space_ids import GroupType, ItemType, NdItemType
+from ..types.kernel_api.local_accessor import LocalAccessorType
 from ..types.kernel_api.ranges import NdRangeType, RangeType
 from ..types.usm_ndarray_type import USMNdArray
 
@@ -150,3 +154,83 @@ def typeof_ndrange(val, c):
     Returns: A numba_dpex.core.types.range_types.RangeType instance.
     """
     return NdRangeType(val.global_range.ndim)
+
+
+@typeof_impl.register(AtomicRef)
+def typeof_atomic_ref(val: AtomicRef, ctx) -> AtomicRefType:
+    """Returns a ``numba_dpex.experimental.dpctpp_types.AtomicRefType``
+    instance for a Python AtomicRef object.
+
+    Args:
+        val (AtomicRef): Instance of the AtomicRef type.
+        ctx : Numba typing context used for type inference.
+
+    Returns: AtomicRefType object corresponding to the AtomicRef object.
+
+    """
+    dtype = typeof_impl(val.ref, ctx)
+
+    return AtomicRefType(
+        dtype=dtype,
+        memory_order=val.memory_order.value,
+        memory_scope=val.memory_scope.value,
+        address_space=val.address_space.value,
+    )
+
+
+@typeof_impl.register(Group)
+def typeof_group(val: Group, c):
+    """Registers the type inference implementation function for a
+    numba_dpex.kernel_api.Group PyObject.
+
+    Args:
+        val : An instance of numba_dpex.kernel_api.Group.
+        c : Unused argument used to be consistent with Numba API.
+
+    Returns: A numba_dpex.experimental.core.types.kernel_api.items.GroupType
+        instance.
+    """
+    return GroupType(val.ndim)
+
+
+@typeof_impl.register(Item)
+def typeof_item(val: Item, c):
+    """Registers the type inference implementation function for a
+    numba_dpex.kernel_api.Item PyObject.
+
+    Args:
+        val : An instance of numba_dpex.kernel_api.Item.
+        c : Unused argument used to be consistent with Numba API.
+
+    Returns: A numba_dpex.experimental.core.types.kernel_api.items.ItemType
+        instance.
+    """
+    return ItemType(val.dimensions)
+
+
+@typeof_impl.register(NdItem)
+def typeof_nditem(val: NdItem, c):
+    """Registers the type inference implementation function for a
+    numba_dpex.kernel_api.NdItem PyObject.
+
+    Args:
+        val : An instance of numba_dpex.kernel_api.NdItem.
+        c : Unused argument used to be consistent with Numba API.
+
+    Returns: A numba_dpex.experimental.core.types.kernel_api.items.NdItemType
+        instance.
+    """
+    return NdItemType(val.dimensions)
+
+
+@typeof_impl.register(LocalAccessor)
+def typeof_local_accessor(val: LocalAccessor, c) -> LocalAccessorType:
+    """Returns a ``numba_dpex.experimental.dpctpp_types.LocalAccessorType``
+    instance for a Python LocalAccessor object.
+    Args:
+        val (LocalAccessor): Instance of the LocalAccessor type.
+        c : Numba typing context used for type inference.
+    Returns: LocalAccessorType object corresponding to the LocalAccessor object.
+    """
+    # pylint: disable=protected-access
+    return LocalAccessorType(ndim=len(val._shape), dtype=val._dtype)