tensorflow::
    
   ops::
    
   ParallelDynamicStitch
  
  
   #include <data_flow_ops.h>
  
  
   Interleave the values from the
   
    data
   
   tensors into a single tensor.
  
Summary
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.
   
   
Args:
- scope: A Scope object
 
Returns:
- 
     
Output: The merged tensor. 
     Constructors and Destructors | 
   |
|---|---|
     
      
       ParallelDynamicStitch
      
      (const ::
      
       tensorflow::Scope
      
      & scope, ::
      
       tensorflow::InputList
      
      indices, ::
      
       tensorflow::InputList
      
      data)
     
      | 
   
     Public attributes | 
   |
|---|---|
     
      
       merged
      
     
     | 
    |
     
      
       operation
      
     
     | 
    |
     Public functions | 
   |
|---|---|
     
      
       node
      
      () const
     
     | 
    
     
       ::tensorflow::Node *
      
      | 
   
     
      
       operator::tensorflow::Input
      
      () const
     
     | 
    
     
      
      | 
   
     
      
       operator::tensorflow::Output
      
      () const
     
     | 
    
     
      
      | 
   
Public attributes
Public functions
ParallelDynamicStitch
ParallelDynamicStitch( const ::tensorflow::Scope & scope, ::tensorflow::InputList indices, ::tensorflow::InputList data )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const