Introduce and experimental data model manager.

Author: Diptorup Deb

numba_dpex/experimental/launcher.py

@@ -11,6 +11,7 @@
 
 from llvmlite import ir as llvmir
 from numba.core import cgutils, cpu, types
+from numba.core.datamodel import default_manager as numba_default_dmm
 from numba.extending import intrinsic, overload
 
 from numba_dpex import config, dpjit
@@ -192,23 +193,27 @@ def create_llvm_values_for_index_space(
         ndim = indexer_argty.ndim
         grange_extents = []
         lrange_extents = []
-        datamodel = self._kernel_targetctx.data_model_manager.lookup(
-            indexer_argty
-        )
+        indexer_datamodel = numba_default_dmm.lookup(indexer_argty)
 
         if isinstance(indexer_argty, RangeType):
             for dim_num in range(ndim):
-                dim_pos = datamodel.get_field_position("dim" + str(dim_num))
+                dim_pos = indexer_datamodel.get_field_position(
+                    "dim" + str(dim_num)
+                )
                 grange_extents.append(
                     self._builder.extract_value(index_space_arg, dim_pos)
                 )
         elif isinstance(indexer_argty, NdRangeType):
             for dim_num in range(ndim):
-                gdim_pos = datamodel.get_field_position("gdim" + str(dim_num))
+                gdim_pos = indexer_datamodel.get_field_position(
+                    "gdim" + str(dim_num)
+                )
                 grange_extents.append(
                     self._builder.extract_value(index_space_arg, gdim_pos)
                 )
-                ldim_pos = datamodel.get_field_position("ldim" + str(dim_num))
+                ldim_pos = indexer_datamodel.get_field_position(
+                    "ldim" + str(dim_num)
+                )
                 lrange_extents.append(
                     self._builder.extract_value(index_space_arg, ldim_pos)
                 )

numba_dpex/experimental/models.py

@@ -2,19 +2,38 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
-"""Provides Numba datamodel for the numba_dpex types introduced in the
+"""Provides the Numba data models for the numba_dpex types introduced in the
 numba_dpex.experimental module.
 """
 
-from numba.core.datamodel import models
+from numba.core.datamodel import DataModelManager, models
 from numba.core.extending import register_model
 
-from numba_dpex.core.datamodel.models import dpex_data_model_manager as dmm
+import numba_dpex.core.datamodel.models as dpex_core_models
 
 from .types import KernelDispatcherType
 
-# Register the types and datamodel in the DpexKernelTargetContext
-dmm.register(KernelDispatcherType, models.OpaqueModel)
 
-# Register the types and datamodel in the DpexTargetContext
+def _init_exp_data_model_manager() -> DataModelManager:
+    """Initializes a DpexExpKernelTarget-specific data model manager.
+
+    Extends the DpexKernelTargetContext's datamodel manager with all
+    experimental types that are getting added to the kernel API.
+
+    Returns:
+        DataModelManager: A numba-dpex DpexExpKernelTarget-specific data model
+        manager
+    """
+
+    dmm = dpex_core_models.dpex_data_model_manager.copy()
+
+    # Register the types and data model in the DpexExpTargetContext
+    # Add here...
+
+    return dmm
+
+
+exp_dmm = _init_exp_data_model_manager()
+
+# Register any new type that should go into numba.core.datamodel.default_manager
 register_model(KernelDispatcherType)(models.OpaqueModel)

numba_dpex/experimental/target.py

@@ -16,6 +16,7 @@
     DpexKernelTargetContext,
     DpexKernelTypingContext,
 )
+from numba_dpex.experimental.models import exp_dmm
 
 
 #  pylint: disable=R0903
@@ -51,6 +52,10 @@ class DpexExpKernelTargetContext(DpexKernelTargetContext):
     they are stable enough to be migrated to DpexKernelTargetContext.
     """
 
+    def __init__(self, typingctx, target=DPEX_KERNEL_EXP_TARGET_NAME):
+        super().__init__(typingctx, target)
+        self.data_model_manager = exp_dmm
+
 
 class DpexExpKernelTarget(TargetDescriptor):
     """