def serialize_many_sparse(sp_input, name=None):
"""Serialize an `N`-minibatch `SparseTensor` into an `[N, 3]` string `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).
Returns:
A string 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`.
"""
if not isinstance(sp_input, ops.SparseTensor):
raise TypeError("Input must be a SparseTensor.")
return gen_sparse_ops._serialize_many_sparse(sp_input.indices,
sp_input.values,
sp_input.shape,
name=name)
def serialize_many_sparse(sp_input, name=None):
"""Serialize an `N`-minibatch `SparseTensor` into an `[N, 3]` string `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).
Returns:
A string 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`.
"""
if not isinstance(sp_input, ops.SparseTensor):
raise TypeError("Input must be a SparseTensor.")
return gen_sparse_ops._serialize_many_sparse(
sp_input.indices,
sp_input.values,
sp_input.shape,
name=name)
