add back the definition of bitwise_xor as delete it will cause failure

Author: Manfredss

python/paddle/_paddle_docs.py

@@ -3003,6 +3003,52 @@ def asin(
 """,
 )
 
+add_doc_and_signature(
+    "bitwise_xor",
+    r"""
+
+    Apply ``bitwise_xor`` on Tensor ``X`` and ``Y`` .
+
+    .. math::
+        Out = X ^\wedge Y
+
+    Note:
+        ``paddle.bitwise_xor`` supports broadcasting. If you want know more about broadcasting, please refer to please refer to `Introduction to Tensor`_ .
+
+        .. _Introduction to Tensor: ../../guides/beginner/tensor_en.html#chapter5-broadcasting-of-tensor
+
+    Args:
+        x (Tensor): Input Tensor of ``bitwise_xor`` . It is a N-D Tensor of bool, uint8, int8, int16, int32, int64.
+            Alias : ``input``
+        y (Tensor): Input Tensor of ``bitwise_xor`` . It is a N-D Tensor of bool, uint8, int8, int16, int32, int64.
+            Alias: ``other``
+        out (Tensor|None, optional): Result of ``bitwise_xor`` . It is a N-D Tensor with the same data type of input Tensor. Default: None.
+        name (str|None, optional): The default value is None.  Normally there is no need for
+            user to set this property.  For more information, please refer to :ref:`api_guide_Name`.
+
+    Returns:
+        Tensor: Result of ``bitwise_xor`` . It is a N-D Tensor with the same data type of input Tensor.
+
+    Examples:
+        .. code-block:: python
+
+            >>> import paddle
+            >>> x = paddle.to_tensor([-5, -1, 1])
+            >>> y = paddle.to_tensor([4,  2, -3])
+            >>> res = paddle.bitwise_xor(x, y)
+            >>> print(res)
+            Tensor(shape=[3], dtype=int64, place=Place(cpu), stop_gradient=True,
+            [-1, -3, -4])
+    """,
+    """
+def bitwise_xor(
+    x: Tensor,
+    y: Tensor,
+    name: str | None = None,
+) -> Tensor
+""",
+)
+
 add_doc_and_signature(
     "bitwise_xor_",
     r"""
@@ -3029,30 +3075,28 @@ def asin(
 
     Examples:
         .. code-block:: python
-
             >>> import paddle
-
             >>> # Integer example
             >>> x = paddle.to_tensor([-5, -1, 1], dtype='int64')
             >>> y = paddle.to_tensor([ 4,  2, -3], dtype='int64')
             >>> paddle.bitwise_xor_(x, y)       # in-place; equivalent to x.bitwise_xor_(y)
             >>> print(x)
             Tensor(shape=[3], dtype=int64, place=Place(cpu), stop_gradient=True,
             [-1, -3, -4])
-
             >>> # Boolean example
             >>> x = paddle.to_tensor([True, False, True], dtype='bool')
             >>> y = paddle.to_tensor([True, True, False], dtype='bool')
             >>> x.bitwise_xor_(y)               # in-place
             >>> print(x)
             Tensor(shape=[3], dtype=bool, place=Place(cpu), stop_gradient=True,
             [False, True, True])
-    """,
+
+""",
     """
 def bitwise_xor_(
     x: Tensor,
     y: Tensor,
     name: str | None = None,
-) -> Tensor
+) -> Tensor:
 """,
 )

python/paddle/tensor/logic.py

@@ -21,7 +21,6 @@
 import paddle
 from paddle import _C_ops
 from paddle._C_ops import (  # noqa: F401
-    bitwise_xor,
     greater_than,
     isclose,
     logical_and,
@@ -50,7 +49,6 @@
 if TYPE_CHECKING:
     from paddle import Tensor
 
-
 __all__ = []
 
 
@@ -1211,6 +1209,52 @@ def bitwise_or_(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
         return _C_ops.bitwise_or_(x, y)
 
 
+@param_two_alias(["x", "input"], ["y", "other"])
+def bitwise_xor(
+    x: Tensor, y: Tensor, out: Tensor | None = None, name: str | None = None
+) -> Tensor:
+    r"""
+
+    Apply ``bitwise_xor`` on Tensor ``X`` and ``Y`` .
+
+    .. math::
+        Out = X ^\wedge Y
+
+    Note:
+        ``paddle.bitwise_xor`` supports broadcasting. If you want know more about broadcasting, please refer to please refer to `Introduction to Tensor`_ .
+
+        .. _Introduction to Tensor: ../../guides/beginner/tensor_en.html#chapter5-broadcasting-of-tensor
+
+    Args:
+        x (Tensor): Input Tensor of ``bitwise_xor`` . It is a N-D Tensor of bool, uint8, int8, int16, int32, int64.
+            Alias : ``input``
+        y (Tensor): Input Tensor of ``bitwise_xor`` . It is a N-D Tensor of bool, uint8, int8, int16, int32, int64.
+            Alias: ``other``
+        out (Tensor|None, optional): Result of ``bitwise_xor`` . It is a N-D Tensor with the same data type of input Tensor. Default: None.
+        name (str|None, optional): The default value is None.  Normally there is no need for
+            user to set this property.  For more information, please refer to :ref:`api_guide_Name`.
+
+    Returns:
+        Tensor: Result of ``bitwise_xor`` . It is a N-D Tensor with the same data type of input Tensor.
+
+    Examples:
+        .. code-block:: python
+
+            >>> import paddle
+            >>> x = paddle.to_tensor([-5, -1, 1])
+            >>> y = paddle.to_tensor([4,  2, -3])
+            >>> res = paddle.bitwise_xor(x, y)
+            >>> print(res)
+            Tensor(shape=[3], dtype=int64, place=Place(cpu), stop_gradient=True,
+            [-1, -3, -4])
+    """
+    if in_dynamic_or_pir_mode() and out is None:
+        return _C_ops.bitwise_xor(x, y)
+    return _bitwise_op(
+        op_name="bitwise_xor", x=x, y=y, name=name, out=out, binary_op=True
+    )
+
+
 def __rxor__(
     x: Tensor,
     y: int | bool,
@@ -1227,7 +1271,7 @@ def __rxor__(
 
 
 @inplace_apis_in_dygraph_only
-@ParamAliasDecorator({"x": ["input"], "y": ["other"]})
+@param_two_alias(["x", "input"], ["y", "other"])
 def bitwise_xor_(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
     r"""
     Inplace version of ``bitwise_xor`` API, the output Tensor will be inplaced with input ``x``.