tf.compat.v1.serialize_many_sparse

Serialize N-minibatch SparseTensor into an [N, 3] Tensor.

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.io.serialize_many_sparse

 
tf.compat.v1.serialize_many_sparse(
    sp_input,
    name=None,
    out_type=tf.dtypes.string
)

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].

sp_input The input rank R SparseTensor.
name A name prefix for the returned tensors (optional).
out_type The dtype to use for serialization.

A matrix (2-D Tensor) with N rows and 3 columns. Each column represents serialized SparseTensor's indices, values, and shape (respectively).

TypeError If sp_input is not a SparseTensor.