Remove kernel_interface.arrayobj

    - Merges core.kernel_interface.arrayobj into
      kernel_api_impl.spirv.arrayobj
    - Moves arrayobj.populate_array into target.py
    - Updated populate_array to use USMNdArray type.
    - Remove core.kernel_api

numba_dpex/dpnp_iface/arrayobj.py

@@ -16,10 +16,10 @@
 from numba.np.arrayobj import make_array
 from numba.np.numpy_support import is_nonelike
 
-from numba_dpex.core.kernel_interface.arrayobj import (
+from numba_dpex.core.types import DpnpNdArray
+from numba_dpex.kernel_api_impl.spirv.arrayobj import (
     _getitem_array_generic as kernel_getitem_array_generic,
 )
-from numba_dpex.core.types import DpnpNdArray
 from numba_dpex.kernel_api_impl.spirv.target import SPIRVTargetContext
 
 from ._intrinsic import (

numba_dpex/kernel_api_impl/spirv/arrayobj.py

@@ -1,6 +1,8 @@
+# SPDX-FileCopyrightText: 2012 - 2024 Anaconda Inc.
 # SPDX-FileCopyrightText: 2024 Intel Corporation
 #
 # SPDX-License-Identifier: Apache-2.0
+# SPDX-License-Identifier: BSD-2-Clause
 
 """Contains SPIR-V specific array functions."""
 
@@ -12,10 +14,68 @@
 from llvmlite.ir.builder import IRBuilder
 from numba.core import cgutils, errors, types
 from numba.core.base import BaseContext
+from numba.np import arrayobj as np_arrayobj
 
-from numba_dpex.kernel_api_impl.spirv.target import SPIRVTargetContext
 from numba_dpex.ocl.oclimpl import _get_target_data
 
+from .target import SPIRVTargetContext
+
+
+def make_view(
+    context, builder, ary, return_type, data, shapes, strides
+):  # pylint: disable=too-many-arguments
+    """
+    Build a view over the given array with the given parameters.
+
+    This is analog of numpy.np.arrayobj.make_view without parent and
+    meminfo fields, because they don't make sense on device. This function
+    intended to be used only in kernel targets.
+    """
+    retary = np_arrayobj.make_array(return_type)(context, builder)
+    context.populate_array(
+        retary, data=data, shape=shapes, strides=strides, itemsize=ary.itemsize
+    )
+    return retary
+
+
+def _getitem_array_generic(
+    context, builder, return_type, aryty, ary, index_types, indices
+):  # pylint: disable=too-many-arguments
+    """
+    Return the result of indexing *ary* with the given *indices*,
+    returning either a scalar or a view.
+
+    This is analog of numpy.np.arrayobj._getitem_array_generic without parent
+    and meminfo fields, because they don't make sense on device. This function
+    intended to be used only in kernel targets.
+    """
+    dataptr, view_shapes, view_strides = np_arrayobj.basic_indexing(
+        context,
+        builder,
+        aryty,
+        ary,
+        index_types,
+        indices,
+        boundscheck=context.enable_boundscheck,
+    )
+
+    if isinstance(return_type, types.Buffer):
+        # Build array view
+        retary = make_view(
+            context,
+            builder,
+            ary,
+            return_type,
+            dataptr,
+            view_shapes,
+            view_strides,
+        )
+        return retary._getvalue()  # pylint: disable=protected-access
+
+    # Load scalar from 0-d result
+    assert not view_shapes
+    return np_arrayobj.load_item(context, builder, aryty, dataptr)
+
 
 def get_itemsize(context: SPIRVTargetContext, array_type: types.Array):
     """

numba_dpex/kernel_api_impl/spirv/target.py

@@ -21,7 +21,7 @@
 from numba.core.typing import cmathdecl, enumdecl
 
 from numba_dpex.core.datamodel.models import _init_kernel_data_model_manager
-from numba_dpex.core.types import IntEnumLiteral
+from numba_dpex.core.types import IntEnumLiteral, USMNdArray
 from numba_dpex.core.typing import dpnpdecl
 from numba_dpex.kernel_api.flag_enum import FlagEnum
 from numba_dpex.ocl.mathimpl import lower_ocl_impl, sig_mapper
@@ -37,9 +37,7 @@
 
 class CompilationMode(IntEnum):
     """Flags used to determine how a function should be compiled by the
-    numba_dpex.experimental.dispatcher.KernelDispatcher. Note the functionality
-    will be merged into numba_dpex.core.kernel_interface.dispatcher in the
-    future.
+    numba_dpex.kernel_api_impl_spirv.dispatcher.KernelDispatcher.
 
         KERNEL :         Indicates that the function will be compiled into an
                          LLVM function that has ``spir_kernel`` calling
@@ -220,6 +218,75 @@ def _generate_spir_kernel_wrapper(self, func, argtypes):
         module.get_function(func.name).linkage = "internal"
         return wrapper
 
+    def _populate_array(
+        self, arraystruct, data, shape, strides, itemsize
+    ):  # pylint: disable=too-many-arguments,too-many-locals
+        """
+        Helper function for populating array structures.
+
+        The function is copied from upstream Numba and modified to support the
+        USMNdArray data type that uses a different data model on SYCL devices
+        than the upstream types.Array data type. USMNdArray data model does not
+        have the ``parent`` and ``meminfo`` fields. This function intended to be
+        used only in the SPIRVKernelTarget.
+
+        *shape* and *strides* can be Python tuples or LLVM arrays.
+        """
+        context = arraystruct._context  # pylint: disable=protected-access
+        builder = arraystruct._builder  # pylint: disable=protected-access
+        datamodel = arraystruct._datamodel  # pylint: disable=protected-access
+        # doesn't matter what this array type instance is, it's just to get the
+        # fields for the data model of the standard array type in this context
+        standard_array = USMNdArray(ndim=1, layout="C", dtype=nb_types.float64)
+        standard_array_type_datamodel = context.data_model_manager[
+            standard_array
+        ]
+        required_fields = set(standard_array_type_datamodel._fields)
+        datamodel_fields = set(datamodel._fields)
+        # Make sure that the presented array object has a data model that is
+        # close enough to an array for this function to proceed.
+        if (required_fields & datamodel_fields) != required_fields:
+            missing = required_fields - datamodel_fields
+            msg = (
+                f"The datamodel for type {arraystruct} is missing "
+                f"field{'s' if len(missing) > 1 else ''} {missing}."
+            )
+            raise ValueError(msg)
+
+        intp_t = context.get_value_type(nb_types.intp)
+        if isinstance(shape, (tuple, list)):
+            shape = cgutils.pack_array(builder, shape, intp_t)
+        if isinstance(strides, (tuple, list)):
+            strides = cgutils.pack_array(builder, strides, intp_t)
+        if isinstance(itemsize, int):
+            itemsize = intp_t(itemsize)
+
+        attrs = {
+            "shape": shape,
+            "strides": strides,
+            "data": data,
+            "itemsize": itemsize,
+        }
+
+        # Calc num of items from shape
+        nitems = context.get_constant(nb_types.intp, 1)
+        unpacked_shape = cgutils.unpack_tuple(builder, shape, shape.type.count)
+        # (note empty shape => 0d array therefore nitems = 1)
+        for axlen in unpacked_shape:
+            nitems = builder.mul(nitems, axlen, flags=["nsw"])
+        attrs["nitems"] = nitems
+
+        # Make sure that we have all the fields
+        got_fields = set(attrs.keys())
+        if got_fields != required_fields:
+            raise ValueError(f"missing {required_fields - got_fields}")
+
+        # Set field value
+        for k, v in attrs.items():
+            setattr(arraystruct, k, v)
+
+        return arraystruct
+
     def get_getattr(self, typ, attr):
         """
         Overrides the get_getattr function to provide an implementation for
@@ -419,10 +486,7 @@ def populate_array(self, arr, **kwargs):
         """
         Populate array structure.
         """
-        # pylint: disable=import-outside-toplevel
-        from numba_dpex.core.kernel_interface import arrayobj
-
-        return arrayobj.populate_array(arr, **kwargs)
+        return self._populate_array(arr, **kwargs)
 
     def get_executable(self, func, fndesc, env):
         """Not implemented for SPIRVTargetContext"""