tensorflow::ops::ParallelConcat
#include <array_ops.h>
Concatenates a list of N
tensors along the first dimension.
Summary
The input tensors are all required to have size 1 in the first dimension.
For example:
```prettyprint 'x' is [[1, 4]]
'y' is [[2, 5]]
'z' is [[3, 6]]
parallel_concat([x, y, z]) => [[1, 4], [2, 5], [3, 6]] # Pack along first dim. ```
The difference between concat and parallel_concat is that concat requires all of the inputs be computed before the operation will begin but doesn't require that the input shapes be known during graph construction. Parallel concat will copy pieces of the input into the output as they become available, in some situations this can provide a performance benefit.
Arguments:
 scope: A Scope object
 values: Tensors to be concatenated. All must have size 1 in the first dimension and same shape.
 shape: the final shape of the result; should be equal to the shapes of any input but with the number of input values in the first dimension.
Returns:
Output
: The concatenated tensor.
Constructors and Destructors 


ParallelConcat(const ::tensorflow::Scope & scope, ::tensorflow::InputList values, TensorShape shape)

Public attributes 


output

Public functions 


node() const

::tensorflow::Node *

operator::tensorflow::Input() const


operator::tensorflow::Output() const


Public attributes
output
::tensorflow::Output output
Public functions
ParallelConcat
ParallelConcat( const ::tensorflow::Scope & scope, ::tensorflow::InputList values, TensorShape shape )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const