parameters: (sp_input, name=None)
return_statement: return gen_sparse_ops._serialize_sparse(
        sp_input.indices,
        sp_input.values,
        sp_input.shape,
        name=name)
docstring: Serialize a `SparseTensor` into a string 3-vector (1-D `Tensor`) object.
  
    Args:
      sp_input: The input `SparseTensor`.
      name: A name prefix for the returned tensors (optional).
  
    Returns:
      A string 3-vector (1D `Tensor`), with each column representing the
      serialized `SparseTensor`'s indices, values, and shape (respectively).
  
    Raises:
      TypeError: If `sp_input` is not a `SparseTensor`.
docstring_summary: Serialize a `SparseTensor` into a string 3-vector (1-D `Tensor`) object.
docstring_tokens: Serialize a SparseTensor into a string 3 - vector ( 1 - D Tensor ) object .
function: def serialize_sparse(sp_input, name=None):
    """Serialize a `SparseTensor` into a string 3-vector (1-D `Tensor`) object.
  
    Args:
      sp_input: The input `SparseTensor`.
      name: A name prefix for the returned tensors (optional).
  
    Returns:
      A string 3-vector (1D `Tensor`), with each column representing the
      serialized `SparseTensor`'s indices, values, and shape (respectively).
  
    Raises:
      TypeError: If `sp_input` is not a `SparseTensor`.
    """
    if not isinstance(sp_input, ops.SparseTensor):
      raise TypeError("Input must be a SparseTensor.")
  
    return gen_sparse_ops._serialize_sparse(
        sp_input.indices,
        sp_input.values,
        sp_input.shape,
        name=name)
function_tokens: def serialize_sparse ( sp_input , name = None ) : if not isinstance ( sp_input , ops . SparseTensor ) : raise TypeError ( "Input must be a SparseTensor." ) return gen_sparse_ops . _serialize_sparse ( sp_input . indices , sp_input . values , sp_input . shape , name = name )