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XlaConcatND

public final class XlaConcatND

Concats input tensor across all dimensions.

An op which merges slices the input tensor based on the given num_splits attribute, strips paddings optionally, and returns the merged tensor without paddings.

This op may be generated via the TPU bridge.

For example, with `input` tensor:

[[0, 1],
  [4, 5]]
 [[2, 3],
  [6, 7]]
 [[8, 9],
  [12, 13]]
 [[10, 11],
  [14, 15]]
 
`num_splits`:
[2, 2]
 
and `paddings`:
[1, 1]
 
the expected `outputs` is:
[[0, 1, 2],
  [4, 5, 6],
  [8, 9, 10]]
 

Nested Classes

class XlaConcatND.Options Optional attributes for XlaConcatND  

Public Methods

Output<T>
asOutput()
Returns the symbolic handle of a tensor.
static <T> XlaConcatND<T>
create(Scope scope, Iterable<Operand<T>> inputs, List<Long> numConcats, Options... options)
Factory method to create a class wrapping a new XlaConcatND operation.
Output<T>
output()
static XlaConcatND.Options
paddings(List<Long> paddings)

Inherited Methods

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of a tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static XlaConcatND<T> create (Scope scope, Iterable<Operand<T>> inputs, List<Long> numConcats, Options... options)

Factory method to create a class wrapping a new XlaConcatND operation.

Parameters
scope current scope
inputs Input tensor slices in row-major order to merge across all dimensions. All inputs must have the same shape. } out_arg { name: "output" description: <
numConcats Number of ways to merge per dimension.
options carries optional attributes values
Returns
  • a new instance of XlaConcatND

public Output<T> output ()

public static XlaConcatND.Options paddings (List<Long> paddings)

Parameters
paddings Optional list of right paddings per dimension to strip from the final merged tensor. These paddings must not exceed the dimension size of the merged result prior to stripping paddings.