diff --git a/python/paddle/tensor/creation.py b/python/paddle/tensor/creation.py
index b68f8e48df26d7..07c92fb2a26283 100644
--- a/python/paddle/tensor/creation.py
+++ b/python/paddle/tensor/creation.py
@@ -1267,6 +1267,7 @@ def ones(
     shape: ShapeLike,
     dtype: DTypeLike | None = None,
     *,
+    out: paddle.Tensor | None = None,
     device: PlaceLike | None = None,
     requires_grad: bool = False,
     name: str | None = None,
@@ -1280,6 +1281,7 @@ def ones(
             If ``shape`` is an Tensor, it should be an 1-D Tensor which represents a list.
         dtype (np.dtype|str, optional): Data type of output Tensor, it should be one of
             bool, float16, float32, float64, int32 and int64. If it is set to None, the data type will be float32.
+        out(Tensor, optional): The output tensor.
         device(PlaceLike|None, optional): The desired device of returned tensor.
             if None, uses the current device for the default tensor type (see paddle.device.set_device()).
             device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. Default: None.
@@ -1321,6 +1323,7 @@ def ones(
         shape,
         1,
         dtype,
+        out=out,
         device=device,
         requires_grad=requires_grad,
         name=name,
@@ -1385,6 +1388,7 @@ def zeros(
     shape: ShapeLike,
     dtype: DTypeLike | None = None,
     *,
+    out: paddle.Tensor | None = None,
     device: PlaceLike | None = None,
     requires_grad: bool = False,
     name: str | None = None,
@@ -1398,12 +1402,13 @@ def zeros(
             If ``shape`` is an Tensor, it should be an 1-D Tensor which represents a list.
         dtype(np.dtype|str, optional): Data type of output Tensor, it supports
             bool, float16, float32, float64, int32 and int64. Default: if None, the data type is float32.
-        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`.
+        out(Tensor, optional): The output tensor.
         device(PlaceLike|None, optional): The desired device of returned tensor.
             if None, uses the current device for the default tensor type (see paddle.device.set_device()).
             device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. Default: None.
         requires_grad(bool, optional):  If autograd should record operations on the returned tensor. Default: False.
+        name(str|None, optional): The default value is None.  Normally there is no need for user to set this
 
     Returns:
         Tensor: A tensor of data type :attr:`dtype` with shape :attr:`shape` and all elements set to 0.
@@ -1440,6 +1445,7 @@ def zeros(
         shape,
         0,
         dtype,
+        out=out,
         device=device,
         requires_grad=requires_grad,
         name=name,
@@ -1505,6 +1511,7 @@ def eye(
     num_columns: int | None = None,
     dtype: DTypeLike | None = None,
     *,
+    out: paddle.Tensor | None = None,
     device: PlaceLike | None = None,
     requires_grad: bool = False,
     name: str | None = None,
@@ -1520,6 +1527,7 @@ def eye(
         dtype(np.dtype|str, optional): The data type of the returned Tensor.
             It should be int32, int64, float16, float32, float64, complex64, complex128. Default: if None, the data type
             is float32.
+        out(Tensor, optional): The output tensor.
         device(PlaceLike|None, optional): The desired device of returned tensor.
             if None, uses the current device for the default tensor type (see paddle.device.set_device()).
             device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. Default: None.
@@ -1574,6 +1582,7 @@ def _check_attr(attr, message):
                 if device is not None
                 else _current_expected_place()
             ),
+            out=out,
         )
         if requires_grad is True:
             tensor.stop_gradient = False
@@ -1617,6 +1626,7 @@ def full(
     fill_value: bool | float | paddle.Tensor,
     dtype: DTypeLike | None = None,
     *,
+    out: paddle.Tensor | None = None,
     device: PlaceLike | None = None,
     requires_grad: bool = False,
     name: str | None = None,
@@ -1634,6 +1644,7 @@ def full(
         dtype(np.dtype|str, optional): Data type of the output Tensor
             which can be float16, float32, float64, int32, int64, if dtype is `None`, the data
             type of created Tensor is `float32`.
+        out(Tensor, optional): The output tensor.
         device(PlaceLike|None, optional): The desired device of returned tensor.
             if None, uses the current device for the default tensor type (see paddle.device.set_device()).
             device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. Default: None.
@@ -1689,7 +1700,12 @@ def full(
             dtype = paddle.get_default_dtype()
 
     tensor = fill_constant(
-        shape=shape, dtype=dtype, value=fill_value, place=device, name=name
+        shape=shape,
+        dtype=dtype,
+        value=fill_value,
+        out=out,
+        place=device,
+        name=name,
     )
     if requires_grad is True:
         tensor.stop_gradient = False
@@ -2559,6 +2575,7 @@ def empty(
     shape: ShapeLike,
     dtype: DTypeLike | None = None,
     *,
+    out: paddle.Tensor | None = None,
     device: PlaceLike | None = None,
     requires_grad: bool = False,
     name: str | None = None,
@@ -2574,6 +2591,7 @@ def empty(
             which can be bool, float16, float32, float64, int32, int64, complex64, complex128 if dtype is `None`, the data
             type of created Tensor use global default dtype (see ``get_default_dtype``
             for details).
+        out(Tensor, optional): The output tensor.
         device(PlaceLike|None, optional): The desired device of returned tensor.
             if None, uses the current device for the default tensor type (see paddle.device.set_device()).
             device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. Default: None.
@@ -2663,6 +2681,7 @@ def empty(
                 if device is not None
                 else _current_expected_place()
             ),
+            out=out,
         )
         if requires_grad is True:
             tensor.stop_gradient = False
@@ -3178,7 +3197,7 @@ def complex(
         real (Tensor): The real component. The data type should be 'float32' or 'float64'.
         imag (Tensor): The image component. The data type should be the same as ``real``.
         name(str|None, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None.
-        out (Tensor|None, optional): The output tensor. Default: None.
+        out(Tensor|None, optional): The output tensor. Default: None.
 
     Returns:
         Tensor, The output tensor. The data type is 'complex64' or 'complex128', with the same precision as ``real`` and ``imag``.