TakeManySparseFromTensorsMap

public final class TakeManySparseFromTensorsMap

Read `SparseTensors` from a `SparseTensorsMap` and concatenate them.

The input `sparse_handles` must be an `int64` matrix of shape `[N, 1]` where `N` is the minibatch size and the rows correspond to the output handles of `AddSparseToTensorsMap` or `AddManySparseToTensorsMap`. The ranks of the original `SparseTensor` objects that went into the given input ops 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 on the left).

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 handles represent an input, which is a `[2, 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 `SparseTensor` will be:
index = [0  0]
             [0 10]
             [0 20]
             [1  2]
             [1 10]
     values = [1, 2, 3, 4, 5]
     shape = [2 50]
 

Nested Classes

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

static TakeManySparseFromTensorsMap.Options
container(String container)
static <T extends TType> TakeManySparseFromTensorsMap<T>
create(Scope scope, Operand<TInt64> sparseHandles, Class<T> dtype, Options... options)
Factory method to create a class wrapping a new TakeManySparseFromTensorsMap operation.
static TakeManySparseFromTensorsMap.Options
sharedName(String sharedName)
Output<TInt64>
sparseIndices()
2-D.
Output<TInt64>
sparseShape()
1-D.
Output<T>
sparseValues()
1-D.

Inherited Methods

org.tensorflow.op.RawOp
final boolean
equals(Object obj)
final int
Operation
op()
Return this unit of computation as a single Operation.
final String
boolean
equals(Object arg0)
final Class<?>
getClass()
int
hashCode()
final void
notify()
final void
notifyAll()
String
toString()
final void
wait(long arg0, int arg1)
final void
wait(long arg0)
final void
wait()
org.tensorflow.op.Op
abstract ExecutionEnvironment
env()
Return the execution environment this op was created in.
abstract Operation
op()
Return this unit of computation as a single Operation.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "TakeManySparseFromTensorsMap"

Public Methods

public static TakeManySparseFromTensorsMap.Options container (String container)

Parameters
container The container name for the `SparseTensorsMap` read by this op.

public static TakeManySparseFromTensorsMap<T> create (Scope scope, Operand<TInt64> sparseHandles, Class<T> dtype, Options... options)

Factory method to create a class wrapping a new TakeManySparseFromTensorsMap operation.

Parameters
scope current scope
sparseHandles 1-D, The `N` serialized `SparseTensor` objects. Shape: `[N]`.
dtype The `dtype` of the `SparseTensor` objects stored in the `SparseTensorsMap`.
options carries optional attributes values
Returns
  • a new instance of TakeManySparseFromTensorsMap

public static TakeManySparseFromTensorsMap.Options sharedName (String sharedName)

Parameters
sharedName The shared name for the `SparseTensorsMap` read by this op. It should not be blank; rather the `shared_name` or unique Operation name of the Op that created the original `SparseTensorsMap` should be used.

public Output<TInt64> sparseIndices ()

2-D. The `indices` of the minibatch `SparseTensor`.

public Output<TInt64> sparseShape ()

1-D. The `shape` of the minibatch `SparseTensor`.

public Output<T> sparseValues ()

1-D. The `values` of the minibatch `SparseTensor`.