parameters: (x, value=1.0, in_place=True)
return_statement: return out
docstring: The OP is usually used for control flow to increment the data of :attr:`x` by an amount :attr:`value`.
      Notice that the number of elements in :attr:`x` must be equal to 1.
  
      Parameters:
          x (Variable): A tensor that must always contain only one element, its data type supports
              float32, float64, int32 and int64.
          value (float, optional): The amount to increment the data of :attr:`x`. Default: 1.0.
          in_place (bool, optional): Whether the OP should be performed in-place. Default: True.
  
      Returns:
          Variable: The elementwise-incremented tensor with the same shape and data type as :attr:`x`.
  
      Examples:
          .. code-block:: python
  
            import paddle.fluid as fluid
            counter = fluid.layers.zeros(shape=[1], dtype='float32') # [0.]
            fluid.layers.increment(counter) # [1.]
docstring_summary: The OP is usually used for control flow to increment the data of :attr:`x` by an amount :attr:`value`.
      Notice that the number of elements in :attr:`x` must be equal to 1.
docstring_tokens: The OP is usually used for control flow to increment the data of : attr : x by an amount : attr : value . Notice that the number of elements in : attr : x must be equal to 1 .
function: def increment(x, value=1.0, in_place=True):
      """
      The OP is usually used for control flow to increment the data of :attr:`x` by an amount :attr:`value`.
      Notice that the number of elements in :attr:`x` must be equal to 1.
  
      Parameters:
          x (Variable): A tensor that must always contain only one element, its data type supports
              float32, float64, int32 and int64.
          value (float, optional): The amount to increment the data of :attr:`x`. Default: 1.0.
          in_place (bool, optional): Whether the OP should be performed in-place. Default: True.
  
      Returns:
          Variable: The elementwise-incremented tensor with the same shape and data type as :attr:`x`.
  
      Examples:
          .. code-block:: python
  
            import paddle.fluid as fluid
            counter = fluid.layers.zeros(shape=[1], dtype='float32') # [0.]
            fluid.layers.increment(counter) # [1.]
      """
      check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'],
                               'increment')
      helper = LayerHelper("increment", **locals())
      if not in_place:
          out = helper.create_variable_for_type_inference(dtype=x.dtype)
      else:
          out = x
      helper.append_op(
          type='increment',
          inputs={'X': [x]},
          outputs={'Out': [out]},
          attrs={'step': float(value)})
      return out
function_tokens: def increment ( x , value = 1.0 , in_place = True ) : check_variable_and_dtype ( x , 'x' , [ 'float32' , 'float64' , 'int32' , 'int64' ] , 'increment' ) helper = LayerHelper ( "increment" , * * locals ( ) ) if not in_place : out = helper . create_variable_for_type_inference ( dtype = x . dtype ) else : out = x helper . append_op ( type = 'increment' , inputs = { 'X' : [ x ] } , outputs = { 'Out' : [ out ] } , attrs = { 'step' : float ( value ) } ) return out