[API Compatibility No.6] Sink bitwise_xor and bitwise_xor_ to cpp -part

python/paddle/_paddle_docs.py

@@ -2709,3 +2709,56 @@ def abs(
 # zhanrongrun
 
 # other
+add_doc_and_signature(
+    "bitwise_xor_",
+    r"""
+    Performs an in-place bitwise XOR on the input tensor.
+
+    This API applies bitwise XOR between the elements of `x` and the corresponding elements of `y`,
+    modifies `x` in-place, and returns the modified `x`.
+
+    Note:
+        - Broadcasting is supported; see `Introduction to Tensor`_ for broadcasting rules.
+          .. _Introduction to Tensor: ../../guides/beginner/tensor_en.html#chapter5-broadcasting-of-tensor
+        - This is an in-place operation. It mutates `x`. Use with care in dynamic graph / autograd
+          scenarios as it may affect gradients and the computation graph.
+
+    Args:
+        x (Tensor): The input tensor to be modified in-place. Supported dtypes: bool, uint8, int8,
+            int16, int32, int64.
+        y (Tensor): The tensor whose values are XORed with `x`. Must have a dtype compatible with `x`.
+            Broadcasting with `x` is supported.
+        name (str|None, optional): Name for the operation (optional, default is None). Typically not required.
+
+    Returns:
+        Tensor: The modified tensor `x`.
+
+    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
+""",
+)

python/paddle/tensor/logic.py

@@ -1209,6 +1209,7 @@ 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:
@@ -1224,9 +1225,15 @@ def bitwise_xor(
 
         .. _Introduction to Tensor: ../../guides/beginner/tensor_en.html#chapter5-broadcasting-of-tensor
 
+    .. note::
+        Alias Support: The parameter name ``input`` can be used as an alias for ``x``, and ``other`` can be used as an alias for ``y``.
+        For example, ``bitwise_xor(input=tensor_x, other=tensor_y, ...)`` is equivalent to ``bitwise_xor(x=tensor_x, y=tensor_y, ...)``.
+
     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`.
@@ -1268,6 +1275,7 @@ def __rxor__(
 
 
 @inplace_apis_in_dygraph_only
+@ParamAliasDecorator({"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``.

test/legacy_test/test_inplace.py

@@ -1553,6 +1553,22 @@ def non_inplace_api_processing(self, var):
         return paddle.bitwise_xor(var, self.y)
 
 
+class TestDygraphInplacBitwiseXorAlias1(TestDygraphInplacBitwiseAnd):
+    def inplace_api_processing(self, var):
+        return paddle.bitwise_xor_(var, other=self.y)
+
+    def non_inplace_api_processing(self, var):
+        return paddle.bitwise_xor(var, other=self.y)
+
+
+class TestDygraphInplacBitwiseXorAlias2(TestDygraphInplacBitwiseAnd):
+    def inplace_api_processing(self, var):
+        return paddle.bitwise_xor_(input=var, other=self.y)
+
+    def non_inplace_api_processing(self, var):
+        return paddle.bitwise_xor(input=var, other=self.y)
+
+
 class TestDygraphInplacBitwiseNot(TestDygraphInplacBitwiseAnd):
     def inplace_api_processing(self, var):
         return paddle.bitwise_not_(var)