parameters: (tensor_in, prob, name=None)
docstring: Adds dropout node and stores probability tensor into graph collection.
  
    This is deprecated. Please use contrib.layers.dropout instead.
  
    Args:
      tensor_in: Input tensor.
      prob: Float or Tensor.
      name: Operation name.
  
    Returns:
      Tensor of the same shape of `tensor_in`.
  
    Raises:
      ValueError: If `keep_prob` is not in `(0, 1]`.
docstring_summary: Adds dropout node and stores probability tensor into graph collection.
docstring_tokens: Adds dropout node and stores probability tensor into graph collection .
function: def dropout(tensor_in, prob, name=None):
    """Adds dropout node and stores probability tensor into graph collection.
  
    This is deprecated. Please use contrib.layers.dropout instead.
  
    Args:
      tensor_in: Input tensor.
      prob: Float or Tensor.
      name: Operation name.
  
    Returns:
      Tensor of the same shape of `tensor_in`.
  
    Raises:
      ValueError: If `keep_prob` is not in `(0, 1]`.
    """
    with ops.op_scope([tensor_in], name, "dropout") as name:
      if isinstance(prob, float):
        prob = vs.get_variable("prob", [],
                               initializer=init_ops.constant_initializer(prob),
                               trainable=False)
      ops.add_to_collection(DROPOUTS, prob)
      return contrib_dropout(tensor_in, keep_prob=prob)
function_tokens: def dropout ( tensor_in , prob , name = None ) : with ops . op_scope ( [ tensor_in ] , name , "dropout" ) as name : if isinstance ( prob , float ) : prob = vs . get_variable ( "prob" , [ ] , initializer = init_ops . constant_initializer ( prob ) , trainable = False ) ops . add_to_collection ( DROPOUTS , prob ) return contrib_dropout ( tensor_in , keep_prob = prob )