!33956 Add a nn cell for softsign.

Merge pull request !33956 from liqiliang/softsign-cpu

docs/api/api_python/mindspore.nn.rst

@@ -115,6 +115,7 @@ MindSpore中 `mindspore.nn` 接口与上一版本相比，新增、删除和支
     mindspore.nn.LeakyReLU
     mindspore.nn.LogSigmoid
     mindspore.nn.LogSoftmax
+    mindspore.nn.Softsign
     mindspore.nn.PReLU
     mindspore.nn.ReLU
     mindspore.nn.ReLU6

docs/api/api_python/nn/mindspore.nn.Softsign.rst

@@ -0,0 +1,26 @@
+mindspore.nn.Softsign
+=====================
+
+.. py:class:: mindspore.nn.Softsign
+
+    Softsign激活函数。
+
+    按元素计算Softsign激活函数。
+
+    Softsign函数定义为：
+
+    .. math::
+        \text{SoftSign}(x) = \frac{x}{1 + |x|}
+
+    **输入：**
+
+    **input_x** (Tensor) - shape为 :math:`(N, *)` 的Tensor, 其中 :math:`*` 表示任意个数的维度。它的数据类型必须为float16或float32。
+
+    **输出：**
+
+    Tensor，数据类型和shape与 `input_x` 相同。
+
+    **异常：**
+
+    - **TypeError** - `input_x` 不是Tensor。
+    - **TypeError** - `input_x` 的数据类型既不是float16也不是float32。

docs/api/api_python_en/mindspore.nn.rst

@@ -115,6 +115,7 @@ Nonlinear Activation Function Layer
     mindspore.nn.LeakyReLU
     mindspore.nn.LogSigmoid
     mindspore.nn.LogSoftmax
+    mindspore.nn.Softsign
     mindspore.nn.PReLU
     mindspore.nn.ReLU
     mindspore.nn.ReLU6

mindspore/python/mindspore/nn/layer/activation.py

@@ -32,6 +32,7 @@ __all__ = ['Softmax',
            'GELU',
            'FastGelu',
            'Sigmoid',
+           'Softsign',
            'PReLU',
            'get_activation',
            'LeakyReLU',
@@ -612,6 +613,49 @@ class Sigmoid(Cell):
         return self.sigmoid(x)
 
 
+class Softsign(Cell):
+    r"""
+    Softsign activation function.
+
+    Applies the Softsign function element-wise.
+
+    Softsign is defined as:
+
+    .. math::
+
+        \text{SoftSign}(x) = \frac{x}{1 + |x|}
+
+    Inputs:
+        - **input_x** (Tensor) - Tensor of shape :math:`(N, *)`, where :math:`*` means, any number of
+          additional dimensions, with float16 or float32 data type.
+
+    Outputs:
+        Tensor, with the same type and shape as the `input_x`.
+
+    Raises:
+        TypeError: If `input_x` is not a Tensor.
+        TypeError: If dtype of `input_x` is neither float16 nor float32.
+
+    Supported Platforms:
+        ``Ascend`` `CPU``
+
+    Examples:
+        >>> input_x = Tensor(np.array([0, -1, 2, 30, -30]), mindspore.float32)
+        >>> softsign = nn.Softsign()
+        >>> output = softsign(input_x)
+        >>> print(output)
+        [ 0.        -0.5         0.6666667  0.9677419 -0.9677419]
+    """
+
+    def __init__(self):
+        """Initialize Softsign."""
+        super(Softsign, self).__init__()
+        self.softsign = P.Softsign()
+
+    def construct(self, x):
+        return self.softsign(x)
+
+
 class PReLU(Cell):
     r"""
     PReLU activation function.
@@ -665,6 +709,7 @@ class PReLU(Cell):
            [0.9 0.9]]]]
 
     """
+
     @cell_attr_register(attrs="")
     def __init__(self, channel=1, w=0.25):
         """Initialize PReLU."""
@@ -952,6 +997,7 @@ _activation = {
     'fast_gelu': FastGelu,
     'elu': ELU,
     'sigmoid': Sigmoid,
+    'softsign': Softsign,
     'prelu': PReLU,
     'leakyrelu': LeakyReLU,
     'hswish': HSwish,

mindspore/python/mindspore/ops/operations/nn_ops.py

@@ -433,7 +433,7 @@ class Softsign(Primitive):
 
     .. math::
 
-        \text{SoftSign}(x) = \frac{x}{ 1 + |x|}
+        \text{SoftSign}(x) = \frac{x}{1 + |x|}
 
     Inputs:
         - **input_x** (Tensor) - Tensor of shape :math:`(N, *)`, where :math:`*` means, any number of

tests/ut/python/nn/test_activation.py

@@ -105,3 +105,23 @@ def test_compile_leaky_relu():
     net = NetLeakyReLU(alpha=0.1)
     input_data = Tensor(np.array([[1.6, 0, 0.6], [6, 0, -6]], dtype=np.float32))
     _cell_graph_executor.compile(net, input_data)
+
+
+class NetSoftsign(nn.Cell):
+    def __init__(self):
+        super(NetSoftsign, self).__init__()
+        self.softsign = nn.Softsign()
+
+    def construct(self, x):
+        return self.softsign(x)
+
+
+def test_compile_softsign():
+    """
+    Feature: ALL To ALL
+    Description: test cases for Softsign
+    Expectation: no exception
+    """
+    net = NetSoftsign()
+    x = np.array([0, -1, 2, 30, -30], dtype=np.float32)
+    _cell_graph_executor.compile(net, Tensor(x))