[API Compatibility No.218] support torch-style kwarg aliases for paddle.select_scatter

python/paddle/tensor/manipulation.py

@@ -8313,16 +8313,28 @@ def diagonal_scatter(
     return fill_diagonal_tensor(x, y, offset, axis1, axis2, name)
 
 
+@ParamAliasDecorator(
+    {
+        "x": ["input"],
+        "values": ["src"],
+        "axis": ["dim"],
+    }
+)
 def select_scatter(
     x: Tensor, values: Tensor, axis: int, index: int, name: str | None = None
 ) -> Tensor:
     """
     Embeds the values of the values tensor into x at the given index of axis.
 
+    .. note::
+        Alias Support: The parameter name ``input`` can be used as an alias for ``x``.
+        Alias Support: The parameter name ``src`` can be used as an alias for ``values``.
+        Alias Support: The parameter name ``dim`` can be used as an alias for ``axis``.
+
     Args:
-        x (Tensor) : The Destination Tensor. Supported data types are `bool`, `float16`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `bfloat16`, `complex64`, `complex128`.
-        values (Tensor) : The tensor to embed into x. Supported data types are `bool`, `float16`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `bfloat16`, `complex64`, `complex128`.
-        axis (int) : the dimension to insert the slice into.
+        x (Tensor) : The Destination Tensor. Supported data types are `bool`, `float16`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `bfloat16`, `complex64`, `complex128`. Alias: ``input``.
+        values (Tensor) : The tensor to embed into x. Supported data types are `bool`, `float16`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `bfloat16`, `complex64`, `complex128`. Alias: ``src``.
+        axis (int) : the dimension to insert the slice into. Alias: ``dim``.
         index (int) : the index to select with.
         name (str|None, optional): Name for the operation (optional, default is None).
 

test/legacy_test/test_select_scatter_op.py

@@ -127,6 +127,36 @@ def get_out_ref(self, out_ref, index, value_np):
                         out_ref[i, j, index, k, w] = value_np[i, j, k, w]
 
 
+class TestSelectScatterAliasAPI(unittest.TestCase):
+    def setUp(self):
+        self.place = get_places()
+
+    def test_api_alias_dygraph(self):
+        def run(place):
+            paddle.disable_static(place)
+            try:
+                x_tensor = paddle.zeros([2, 3], dtype='float32')
+                value_tensor = paddle.to_tensor([1.0, 2.0], dtype='float32')
+                out1 = paddle.select_scatter(
+                    x=x_tensor, values=value_tensor, axis=1, index=0
+                )
+                out2 = paddle.select_scatter(
+                    input=x_tensor, src=value_tensor, dim=1, index=0
+                )
+                expected = np.array(
+                    [[1.0, 0.0, 0.0], [2.0, 0.0, 0.0]], dtype='float32'
+                )
+                np.testing.assert_allclose(
+                    out1.numpy(), out2.numpy(), rtol=0.001
+                )
+                np.testing.assert_allclose(out2.numpy(), expected, rtol=0.001)
+            finally:
+                paddle.enable_static()
+
+        for place in self.place:
+            run(place)
+
+
 class TestSelectScatterAPIError(unittest.TestCase):
     def setUp(self):
         np.random.seed(0)
@@ -151,6 +181,14 @@ def test_one_of_size_not_equal_error(self):
             value_tensor = paddle.to_tensor([[2, 2], [2, 2]]).astype(np.float32)
             res = paddle.select_scatter(x_tensor, value_tensor, 1, 1)
 
+    def test_axis_and_dim_conflict_error(self):
+        with self.assertRaises(ValueError):
+            x_tensor = paddle.to_tensor(self.x_np)
+            value_tensor = paddle.to_tensor(self.value_np)
+            res = paddle.select_scatter(
+                x=x_tensor, values=value_tensor, axis=1, dim=1, index=1
+            )
+
 
 if __name__ == "__main__":
     paddle.enable_static()