parameters: (sp_input, name=None, out_type=dtypes.string)
return_statement: return serialize_many_sparse_v2(sp_input, out_type, name)
docstring: Serialize `N`-minibatch `SparseTensor` into an `[N, 3]` `Tensor`.
  
    The `SparseTensor` must have rank `R` greater than 1, and the first dimension
    is treated as the minibatch dimension.  Elements of the `SparseTensor`
    must be sorted in increasing order of this first dimension.  The serialized
    `SparseTensor` objects going into each row of the output `Tensor` will have
    rank `R-1`.
  
    The minibatch size `N` is extracted from `sparse_shape[0]`.
  
    Args:
      sp_input: The input rank `R` `SparseTensor`.
      name: A name prefix for the returned tensors (optional).
      out_type: The `dtype` to use for serialization.
  
    Returns:
      A matrix (2-D `Tensor`) with `N` rows and `3` columns. Each column
      represents serialized `SparseTensor`'s indices, values, and shape
      (respectively).
  
    Raises:
      TypeError: If `sp_input` is not a `SparseTensor`.
docstring_summary: Serialize `N`-minibatch `SparseTensor` into an `[N, 3]` `Tensor`.
docstring_tokens: Serialize N - minibatch SparseTensor into an [ N 3 ] Tensor .
function: def serialize_many_sparse(sp_input, name=None, out_type=dtypes.string):
    """Serialize `N`-minibatch `SparseTensor` into an `[N, 3]` `Tensor`.
  
    The `SparseTensor` must have rank `R` greater than 1, and the first dimension
    is treated as the minibatch dimension.  Elements of the `SparseTensor`
    must be sorted in increasing order of this first dimension.  The serialized
    `SparseTensor` objects going into each row of the output `Tensor` will have
    rank `R-1`.
  
    The minibatch size `N` is extracted from `sparse_shape[0]`.
  
    Args:
      sp_input: The input rank `R` `SparseTensor`.
      name: A name prefix for the returned tensors (optional).
      out_type: The `dtype` to use for serialization.
  
    Returns:
      A matrix (2-D `Tensor`) with `N` rows and `3` columns. Each column
      represents serialized `SparseTensor`'s indices, values, and shape
      (respectively).
  
    Raises:
      TypeError: If `sp_input` is not a `SparseTensor`.
    """
    return serialize_many_sparse_v2(sp_input, out_type, name)
function_tokens: def serialize_many_sparse ( sp_input , name = None , out_type = dtypes . string ) : return serialize_many_sparse_v2 ( sp_input , out_type , name )