org.bytedeco.javacpp

Class tensorflow.ParallelDynamicStitch

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.tensorflow.ParallelDynamicStitch

All Implemented Interfaces:

AutoCloseable

Enclosing class:

tensorflow

@Namespace(value="tensorflow::ops")
 @NoOffset
public static class tensorflow.ParallelDynamicStitch
extends Pointer

Interleave the values from the data tensors into a single tensor. Builds a merged tensor such that

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

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

 python
      # 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:

 python
      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:

 python
      # 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.
  

Arguments: * scope: A Scope object Returns: * Output: The merged tensor.

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
ParallelDynamicStitch(Pointer p) Pointer cast constructor.
ParallelDynamicStitch(tensorflow.Scope scope, tensorflow.InputList indices, tensorflow.InputList data)

Method Summary

Modifier and Type	Method and Description
tensorflow.Input	asInput()
tensorflow.Output	asOutput()
tensorflow.Output	merged()
tensorflow.ParallelDynamicStitch	merged(tensorflow.Output merged)
tensorflow.Node	node()
tensorflow.Operation	operation()
tensorflow.ParallelDynamicStitch	operation(tensorflow.Operation operation)

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

ParallelDynamicStitch

public ParallelDynamicStitch(Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

ParallelDynamicStitch

public ParallelDynamicStitch(@Const @ByRef
                             tensorflow.Scope scope,
                             @ByVal
                             tensorflow.InputList indices,
                             @ByVal
                             tensorflow.InputList data)

Method Detail

asOutput

@ByVal
 @Name(value="operator tensorflow::Output")
public tensorflow.Output asOutput()

asInput

@ByVal
 @Name(value="operator tensorflow::Input")
public tensorflow.Input asInput()

node

public tensorflow.Node node()

operation

@ByRef
public tensorflow.Operation operation()

operation

public tensorflow.ParallelDynamicStitch operation(tensorflow.Operation operation)

merged

@ByRef
public tensorflow.Output merged()

merged

public tensorflow.ParallelDynamicStitch merged(tensorflow.Output merged)