parameters: (x, name=None)
return_statement: return out
docstring: r"""
      softsign activation
  
      .. math::
  
          softsign(x) = \frac{x}{1 + |x|}
  
      Parameters:
          x (Tensor): The input Tensor with data type float32, float64.
          name (str, optional): Name for the operation (optional, default is None).
              For more information, please refer to :ref:`api_guide_Name`.
  
      Returns:
          A Tensor with the same data type and shape as ``x`` .
  
      Examples:
          .. code-block:: python
  
              import paddle
              import paddle.nn.functional as F
              import numpy as np
  
              x = paddle.to_tensor(np.array([-0.4, -0.2, 0.1, 0.3]))
              out = F.softsign(x) # [-0.285714, -0.166667, 0.0909091, 0.230769]
docstring_summary: r"""
      softsign activation
docstring_tokens: r softsign activation
function: def softsign(x, name=None):
      r"""
      softsign activation
  
      .. math::
  
          softsign(x) = \frac{x}{1 + |x|}
  
      Parameters:
          x (Tensor): The input Tensor with data type float32, float64.
          name (str, optional): Name for the operation (optional, default is None).
              For more information, please refer to :ref:`api_guide_Name`.
  
      Returns:
          A Tensor with the same data type and shape as ``x`` .
  
      Examples:
          .. code-block:: python
  
              import paddle
              import paddle.nn.functional as F
              import numpy as np
  
              x = paddle.to_tensor(np.array([-0.4, -0.2, 0.1, 0.3]))
              out = F.softsign(x) # [-0.285714, -0.166667, 0.0909091, 0.230769]
      """
      if in_dygraph_mode():
          return _C_ops.softsign(x)
  
      check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'],
                               'softsign')
      helper = LayerHelper('softsign', **locals())
      out = helper.create_variable_for_type_inference(x.dtype)
      helper.append_op(type='softsign', inputs={'X': x}, outputs={'Out': out})
      return out
function_tokens: def softsign ( x , name = None ) : if in_dygraph_mode ( ) : return _C_ops . softsign ( x ) check_variable_and_dtype ( x , 'x' , [ 'float16' , 'float32' , 'float64' ] , 'softsign' ) helper = LayerHelper ( 'softsign' , * * locals ( ) ) out = helper . create_variable_for_type_inference ( x . dtype ) helper . append_op ( type = 'softsign' , inputs = { 'X' : x } , outputs = { 'Out' : out } ) return out