Move ti.bitwise_invert()/ceil()/conj() and reust them

Author: vlad-perevezentsev

dpctl_ext/tensor/__init__.py

@@ -92,6 +92,9 @@
     asinh,
     atan,
     atanh,
+    bitwise_invert,
+    ceil,
+    conj,
 )
 from ._reduction import (
     argmax,
@@ -133,10 +136,13 @@
     "astype",
     "atan",
     "atanh",
+    "bitwise_invert",
     "broadcast_arrays",
     "broadcast_to",
     "can_cast",
+    "ceil",
     "concat",
+    "conj",
     "copy",
     "count_nonzero",
     "clip",

dpctl_ext/tensor/_elementwise_funcs.py

@@ -236,6 +236,94 @@
 )
 del _atanh_docstring
 
+# U08: ===== BITWISE_INVERT        (x)
+_bitwise_invert_docstring = r"""
+bitwise_invert(x, /, \*, out=None, order='K')
+
+Inverts (flips) each bit for each element `x_i` of the input array `x`.
+
+Args:
+    x (usm_ndarray):
+        Input array, expected to have integer or boolean data type.
+    out (Union[usm_ndarray, None], optional):
+        Output array to populate.
+        Array must have the correct shape and the expected data type.
+    order ("C","F","A","K", optional):
+        Memory layout of the new output array, if parameter
+        `out` is ``None``.
+        Default: "K".
+
+Returns:
+    usm_ndarray:
+        An array containing the element-wise results.
+        The data type of the returned array is same as the data type of the
+        input array.
+"""
+
+bitwise_invert = UnaryElementwiseFunc(
+    "bitwise_invert",
+    ti._bitwise_invert_result_type,
+    ti._bitwise_invert,
+    _bitwise_invert_docstring,
+)
+del _bitwise_invert_docstring
+
+# U09: ==== CEIL          (x)
+_ceil_docstring = r"""
+ceil(x, /, \*, out=None, order='K')
+
+Returns the ceiling for each element `x_i` for input array `x`.
+
+The ceil of `x_i` is the smallest integer `n`, such that `n >= x_i`.
+
+Args:
+    x (usm_ndarray):
+        Input array, expected to have a boolean or real-valued data type.
+    out (Union[usm_ndarray, None], optional):
+        Output array to populate.
+        Array must have the correct shape and the expected data type.
+    order ("C","F","A","K", optional):
+        Memory layout of the new output array, if parameter
+        `out` is ``None``.
+        Default: "K".
+
+Returns:
+    usm_ndarray:
+        An array containing the element-wise ceiling.
+"""
+
+ceil = UnaryElementwiseFunc(
+    "ceil", ti._ceil_result_type, ti._ceil, _ceil_docstring
+)
+del _ceil_docstring
+
+# U10: ==== CONJ          (x)
+_conj_docstring = r"""
+conj(x, /, \*, out=None, order='K')
+
+Computes conjugate of each element `x_i` for input array `x`.
+
+Args:
+    x (usm_ndarray):
+        Input array. May have any data type.
+    out (Union[usm_ndarray, None], optional):
+        Output array to populate.
+        Array must have the correct shape and the expected data type.
+    order ("C","F","A","K", optional):
+        Memory layout of the new output array, if parameter
+        `out` is ``None``.
+        Default: "K".
+
+Returns:
+    usm_ndarray:
+        An array containing the element-wise conjugate values.
+"""
+
+conj = UnaryElementwiseFunc(
+    "conj", ti._conj_result_type, ti._conj, _conj_docstring
+)
+del _conj_docstring
+
 # U43: ==== ANGLE        (x)
 _angle_docstring = r"""
 angle(x, /, \*, out=None, order='K')

dpnp/dpnp_iface_bitwise.py

@@ -46,6 +46,9 @@
 import dpctl.tensor._tensor_elementwise_impl as ti
 import numpy
 
+# TODO: revert to `import dpctl.tensor...`
+# when dpnp fully migrates dpctl/tensor
+import dpctl_ext.tensor._tensor_elementwise_impl as ti_ext
 import dpnp.backend.extensions.ufunc._ufunc_impl as ufi
 from dpnp.dpnp_algo.dpnp_elementwise_common import DPNPBinaryFunc, DPNPUnaryFunc
 
@@ -514,8 +517,8 @@ def binary_repr(num, width=None):
 
 invert = DPNPUnaryFunc(
     "invert",
-    ti._bitwise_invert_result_type,
-    ti._bitwise_invert,
+    ti_ext._bitwise_invert_result_type,
+    ti_ext._bitwise_invert,
     _INVERT_DOCSTRING,
 )
 

dpnp/dpnp_iface_mathematical.py

@@ -647,8 +647,8 @@ def around(x, /, decimals=0, out=None):
 
 ceil = DPNPUnaryFunc(
     "ceil",
-    ti._ceil_result_type,
-    ti._ceil,
+    ti_ext._ceil_result_type,
+    ti_ext._ceil,
     _CEIL_DOCSTRING,
     mkl_fn_to_call="_mkl_ceil_to_call",
     mkl_impl_fn="_ceil",
@@ -782,8 +782,8 @@ def clip(a, /, min=None, max=None, *, out=None, order="K", **kwargs):
 
 conj = DPNPUnaryFunc(
     "conj",
-    ti._conj_result_type,
-    ti._conj,
+    ti_ext._conj_result_type,
+    ti_ext._conj,
     _CONJ_DOCSTRING,
     mkl_fn_to_call="_mkl_conj_to_call",
     mkl_impl_fn="_conj",