[Typing][B-71] Add type annotations for python/paddle/sparse/nn/layer/activation.py

python/paddle/sparse/nn/layer/activation.py

@@ -12,10 +12,17 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
 from paddle.nn import Layer
 
 from .. import functional as F
 
+if TYPE_CHECKING:
+    from paddle import Tensor
+
 __all__ = []
 
 
@@ -29,7 +36,7 @@ class ReLU(Layer):
         ReLU(x) = max(x, 0)
 
     Parameters:
-        name (str, optional): Name for the operation (optional, default is None).
+        name (str|None, optional): Name for the operation (optional, default is None).
             For more information, please refer to :ref:`api_guide_Name`.
 
     Shape:
@@ -51,14 +58,14 @@ class ReLU(Layer):
                    values=[0., 1.])
     """
 
-    def __init__(self, name=None):
+    def __init__(self, name: str | None = None) -> None:
         super().__init__()
         self._name = name
 
-    def forward(self, x):
+    def forward(self, x: Tensor) -> Tensor:
         return F.relu(x, self._name)
 
-    def extra_repr(self):
+    def extra_repr(self) -> str:
         name_str = f'name={self._name}' if self._name else ''
         return name_str
 
@@ -81,7 +88,7 @@ class Softmax(Layer):
 
     Parameters:
         axis (int, optional): The axis along which to perform softmax calculations. Only support -1 for SparseCsrTensor.
-        name (str, optional): Name for the operation (optional, default is None).
+        name (str|None, optional): Name for the operation (optional, default is None).
             For more information, please refer to :ref:`api_guide_Name`.
 
     Shape:
@@ -95,7 +102,7 @@ class Softmax(Layer):
             >>> paddle.seed(2022)
 
             >>> mask = paddle.rand((3, 4)) < 0.7
-            >>> x = paddle.rand((3, 4)) * mask
+            >>> x = paddle.rand((3, 4)) * mask.astype('float32')
             >>> print(x)
             Tensor(shape=[3, 4], dtype=float32, place=Place(cpu), stop_gradient=True,
             [[0.88156885, 0.14463395, 0.17831714, 0.43818203],
@@ -136,15 +143,15 @@ class Softmax(Layer):
                            0.42031071, 0.36666498, 0.59738696, 0.40261301])
     """
 
-    def __init__(self, axis=-1, name=None):
+    def __init__(self, axis: int = -1, name: str | None = None) -> None:
         super().__init__()
         self._axis = axis
         self._name = name
 
-    def forward(self, x):
+    def forward(self, x: Tensor) -> Tensor:
         return F.softmax(x, self._axis, self._name)
 
-    def extra_repr(self):
+    def extra_repr(self) -> str:
         name_str = f'name={self._name}' if self._name else ''
         return name_str
 
@@ -159,7 +166,7 @@ class ReLU6(Layer):
         ReLU6(x) = min(max(0,x), 6)
 
     Parameters:
-        name (str, optional): Name for the operation (optional, default is None).
+        name (str|None, optional): Name for the operation (optional, default is None).
             For more information, please refer to :ref:`api_guide_Name`.
 
     Shape:
@@ -177,14 +184,14 @@ class ReLU6(Layer):
             >>> out = relu6(sparse_x)
     """
 
-    def __init__(self, name=None):
+    def __init__(self, name: str | None = None) -> None:
         super().__init__()
         self._name = name
 
-    def forward(self, x):
+    def forward(self, x: Tensor) -> Tensor:
         return F.relu6(x, self._name)
 
-    def extra_repr(self):
+    def extra_repr(self) -> str:
         name_str = f'name={self._name}' if self._name else ''
         return name_str
 
@@ -207,7 +214,7 @@ class LeakyReLU(Layer):
     Parameters:
         negative_slope (float, optional): Slope of the activation function at
             :math:`x < 0` . Default is 0.01.
-        name (str, optional): Name for the operation (optional, default is None).
+        name (str|None, optional): Name for the operation (optional, default is None).
             For more information, please refer to :ref:`api_guide_Name`.
 
     Shape:
@@ -226,14 +233,16 @@ class LeakyReLU(Layer):
 
     """
 
-    def __init__(self, negative_slope=0.01, name=None):
+    def __init__(
+        self, negative_slope: float = 0.01, name: str | None = None
+    ) -> None:
         super().__init__()
         self._negative_slope = negative_slope
         self._name = name
 
-    def forward(self, x):
+    def forward(self, x: Tensor) -> Tensor:
         return F.leaky_relu(x, self._negative_slope, self._name)
 
-    def extra_repr(self):
+    def extra_repr(self) -> str:
         name_str = f'name={self._name}' if self._name else ''
         return name_str