ParallelDynamicStitch

Interleave the values from the `data` tensors into a single tensor.

Builds a merged tensor such that

merged[indices[m][i, ..., j], ...] = data[m][i, ..., j, ...]
 

For example, if each `indices[m]` is scalar or vector, we have

# Scalar indices:
     merged[indices[m], ...] = data[m][...]
 
     # Vector indices:
     merged[indices[m][i], ...] = data[m][i, ...]
 

Each `data[i].shape` must start with the corresponding `indices[i].shape`, and the rest of `data[i].shape` must be constant w.r.t. `i`. That is, we must have `data[i].shape = indices[i].shape + constant`. In terms of this `constant`, the output shape is

merged.shape = [max(indices)] + constant

Values may be merged in parallel, so if an index appears in both `indices[m][i]` and `indices[n][j]`, the result may be invalid. This differs from the normal DynamicStitch operator that defines the behavior in that case.

For example:

indices[0] = 6
     indices[1] = [4, 1]
     indices[2] = [[5, 2], [0, 3]]
     data[0] = [61, 62]
     data[1] = [[41, 42], [11, 12]]
     data[2] = [[[51, 52], [21, 22]], [[1, 2], [31, 32]]]
     merged = [[1, 2], [11, 12], [21, 22], [31, 32], [41, 42],
               [51, 52], [61, 62]]
 

This method can be used to merge partitions created by `dynamic_partition` as illustrated on the following example:

# Apply function (increments x_i) on elements for which a certain condition
     # apply (x_i != -1 in this example).
     x=tf.constant([0.1, -1., 5.2, 4.3, -1., 7.4])
     condition_mask=tf.not_equal(x,tf.constant(-1.))
     partitioned_data = tf.dynamic_partition(
         x, tf.cast(condition_mask, tf.int32) , 2)
     partitioned_data[1] = partitioned_data[1] + 1.0
     condition_indices = tf.dynamic_partition(
         tf.range(tf.shape(x)[0]), tf.cast(condition_mask, tf.int32) , 2)
     x = tf.dynamic_stitch(condition_indices, partitioned_data)
     # Here x=[1.1, -1., 6.2, 5.3, -1, 8.4], the -1. values remain
     # unchanged.
 

Constants

String

OP_NAME

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

Public Methods

Output<T>	asOutput() Returns the symbolic handle of the tensor.
static <T extends TType> ParallelDynamicStitch<T>	create(Scope scope, Iterable<Operand<TInt32>> indices, Iterable<Operand<T>> data) Factory method to create a class wrapping a new ParallelDynamicStitch operation.
Output<T>	merged()

Inherited Methods

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single Operation.
final String	toString()

From class java.lang.Object

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()

From interface 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.

From interface org.tensorflow.Operand

abstract Output<T>	asOutput() Returns the symbolic handle of the tensor.
abstract T	asTensor() Returns the tensor at this operand.
abstract Shape	shape() Returns the (possibly partially known) shape of the tensor referred to by the Output of this operand.
abstract Class<T>	type() Returns the tensor type of this operand

From interface org.tensorflow.ndarray.Shaped

abstract int	rank()
abstract Shape	shape()
abstract long	size() Computes and returns the total size of this container, in number of values.