tensorflow:: ops:: DeserializeManySparse
#include <sparse_ops.h>
Deserialize and concatenate SparseTensors
from a serialized minibatch.
Summary
The input serialized_sparse
must be a string matrix of shape [N x 3]
where N
is the minibatch size and the rows correspond to packed outputs of SerializeSparse
. The ranks of the original SparseTensor
objects must all match. When the final SparseTensor
is created, it has rank one higher than the ranks of the incoming SparseTensor
objects (they have been concatenated along a new row dimension).
The output SparseTensor
object's shape values for all dimensions but the first are the max across the input SparseTensor
objects' shape values for the corresponding dimensions. Its first shape value is N
, the minibatch size.
The input SparseTensor
objects' indices are assumed ordered in standard lexicographic order. If this is not the case, after this step run SparseReorder
to restore index ordering.
For example, if the serialized input is a [2 x 3]
matrix representing two original SparseTensor
objects:
index = [ 0] [10] [20] values = [1, 2, 3] shape = [50]
and
index = [ 2] [10] values = [4, 5] shape = [30]
then the final deserialized SparseTensor
will be:
index = [0 0] [0 10] [0 20] [1 2] [1 10] values = [1, 2, 3, 4, 5] shape = [2 50]
Args:
- scope: A Scope object
- serialized_sparse: 2-D, The
N
serializedSparseTensor
objects. Must have 3 columns. - dtype: The
dtype
of the serializedSparseTensor
objects.
Returns:
Constructors and Destructors |
|
---|---|
DeserializeManySparse(const ::tensorflow::Scope & scope, ::tensorflow::Input serialized_sparse, DataType dtype)
|
Public attributes |
|
---|---|
operation
|
|
sparse_indices
|
|
sparse_shape
|
|
sparse_values
|
Public attributes
operation
Operation operation
sparse_indices
::tensorflow::Output sparse_indices
sparse_shape
::tensorflow::Output sparse_shape
sparse_values
::tensorflow::Output sparse_values
Public functions
DeserializeManySparse
DeserializeManySparse( const ::tensorflow::Scope & scope, ::tensorflow::Input serialized_sparse, DataType dtype )