Used new native extension modules

Author: oleksandr-pavlyk

dpctl/tensor/_clip.py

@@ -16,6 +16,7 @@
 
 import dpctl
 import dpctl.tensor as dpt
+import dpctl.tensor._tensor_elementwise_impl as tei
 import dpctl.tensor._tensor_impl as ti
 from dpctl.tensor._copy_utils import (
     _empty_like_orderK,
@@ -429,9 +430,9 @@ def clip(x, min=None, max=None, out=None, order="K"):
             "only one of `min` and `max` is permitted to be `None`"
         )
     elif max is None:
-        return _clip_none(x, min, out, order, ti._maximum)
+        return _clip_none(x, min, out, order, tei._maximum)
     elif min is None:
-        return _clip_none(x, max, out, order, ti._minimum)
+        return _clip_none(x, max, out, order, tei._minimum)
     else:
         q1, x_usm_type = x.sycl_queue, x.usm_type
         q2, min_usm_type = _get_queue_usm_type(min)

dpctl/tensor/_elementwise_funcs.py

@@ -14,7 +14,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 
-import dpctl.tensor._tensor_impl as ti
+import dpctl.tensor._tensor_elementwise_impl as ti
 
 from ._elementwise_common import BinaryElementwiseFunc, UnaryElementwiseFunc
 from ._type_utils import _acceptance_fn_divide

dpctl/tensor/_reduction.py

@@ -19,6 +19,7 @@
 import dpctl
 import dpctl.tensor as dpt
 import dpctl.tensor._tensor_impl as ti
+import dpctl.tensor._tensor_reductions_impl as tri
 
 from ._type_utils import _to_device_supported_dtype
 
@@ -220,8 +221,8 @@ def sum(x, axis=None, dtype=None, keepdims=False):
         axis,
         dtype,
         keepdims,
-        ti._sum_over_axis,
-        ti._sum_over_axis_dtype_supported,
+        tri._sum_over_axis,
+        tri._sum_over_axis_dtype_supported,
         _default_reduction_dtype,
         _identity=0,
     )
@@ -281,8 +282,8 @@ def prod(x, axis=None, dtype=None, keepdims=False):
         axis,
         dtype,
         keepdims,
-        ti._prod_over_axis,
-        ti._prod_over_axis_dtype_supported,
+        tri._prod_over_axis,
+        tri._prod_over_axis_dtype_supported,
         _default_reduction_dtype,
         _identity=1,
     )
@@ -335,8 +336,8 @@ def logsumexp(x, axis=None, dtype=None, keepdims=False):
         axis,
         dtype,
         keepdims,
-        ti._logsumexp_over_axis,
-        lambda inp_dt, res_dt, *_: ti._logsumexp_over_axis_dtype_supported(
+        tri._logsumexp_over_axis,
+        lambda inp_dt, res_dt, *_: tri._logsumexp_over_axis_dtype_supported(
             inp_dt, res_dt
         ),
         _default_reduction_dtype_fp_types,
@@ -391,8 +392,8 @@ def reduce_hypot(x, axis=None, dtype=None, keepdims=False):
         axis,
         dtype,
         keepdims,
-        ti._hypot_over_axis,
-        lambda inp_dt, res_dt, *_: ti._hypot_over_axis_dtype_supported(
+        tri._hypot_over_axis,
+        lambda inp_dt, res_dt, *_: tri._hypot_over_axis_dtype_supported(
             inp_dt, res_dt
         ),
         _default_reduction_dtype_fp_types,
@@ -468,7 +469,7 @@ def max(x, axis=None, keepdims=False):
             entire array, a zero-dimensional array is returned. The returned
             array has the same data type as `x`.
     """
-    return _comparison_over_axis(x, axis, keepdims, ti._max_over_axis)
+    return _comparison_over_axis(x, axis, keepdims, tri._max_over_axis)
 
 
 def min(x, axis=None, keepdims=False):
@@ -496,7 +497,7 @@ def min(x, axis=None, keepdims=False):
             entire array, a zero-dimensional array is returned. The returned
             array has the same data type as `x`.
     """
-    return _comparison_over_axis(x, axis, keepdims, ti._min_over_axis)
+    return _comparison_over_axis(x, axis, keepdims, tri._min_over_axis)
 
 
 def _search_over_axis(x, axis, keepdims, _reduction_fn):
@@ -577,7 +578,7 @@ def argmax(x, axis=None, keepdims=False):
             zero-dimensional array is returned. The returned array has the
             default array index data type for the device of `x`.
     """
-    return _search_over_axis(x, axis, keepdims, ti._argmax_over_axis)
+    return _search_over_axis(x, axis, keepdims, tri._argmax_over_axis)
 
 
 def argmin(x, axis=None, keepdims=False):
@@ -609,4 +610,4 @@ def argmin(x, axis=None, keepdims=False):
             zero-dimensional array is returned. The returned array has the
             default array index data type for the device of `x`.
     """
-    return _search_over_axis(x, axis, keepdims, ti._argmin_over_axis)
+    return _search_over_axis(x, axis, keepdims, tri._argmin_over_axis)

dpctl/tensor/_utility_functions.py

@@ -3,6 +3,7 @@
 import dpctl
 import dpctl.tensor as dpt
 import dpctl.tensor._tensor_impl as ti
+import dpctl.tensor._tensor_reductions_impl as tri
 
 
 def _boolean_reduction(x, axis, keepdims, func):
@@ -94,7 +95,7 @@ def all(x, axis=None, keepdims=False):
             An array with a data type of `bool`
             containing the results of the logical AND reduction.
     """
-    return _boolean_reduction(x, axis, keepdims, ti._all)
+    return _boolean_reduction(x, axis, keepdims, tri._all)
 
 
 def any(x, axis=None, keepdims=False):
@@ -122,4 +123,4 @@ def any(x, axis=None, keepdims=False):
             An array with a data type of `bool`
             containing the results of the logical OR reduction.
     """
-    return _boolean_reduction(x, axis, keepdims, ti._any)
+    return _boolean_reduction(x, axis, keepdims, tri._any)