org.bytedeco.javacpp

Class tensorflow.DynamicStitch

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.tensorflow.DynamicStitch

All Implemented Interfaces:

AutoCloseable

Enclosing class:

tensorflow

@Namespace(value="tensorflow::ops")
 @NoOffset
public static class tensorflow.DynamicStitch
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 are merged in order, so if an index appears in both indices[m][i] and indices[n][j] for (m,i) < (n,j) the slice data[n][j] will appear in the merged result. If you do not need this guarantee, ParallelDynamicStitch might perform better on some devices. 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
DynamicStitch(Pointer p) Pointer cast constructor.
DynamicStitch(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.DynamicStitch	merged(tensorflow.Output merged)
tensorflow.Node	node()
tensorflow.Operation	operation()
tensorflow.DynamicStitch	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

DynamicStitch

public DynamicStitch(Pointer p)

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

DynamicStitch

public DynamicStitch(@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.DynamicStitch operation(tensorflow.Operation operation)

merged

@ByRef
public tensorflow.Output merged()

merged

public tensorflow.DynamicStitch merged(tensorflow.Output merged)