org.tensorflow.op.core

Class UniqueWithCounts<T,V extends Number>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.UniqueWithCounts<T,V>

Type Parameters:

T - data type for y() output

V - data type for idx() output

All Implemented Interfaces:

Op

@Operator
public final class UniqueWithCounts<T,V extends Number>
extends PrimitiveOp

Finds unique elements along an axis of a tensor.

This operation either returns a tensor `y` containing unique elements along the `axis` of a tensor. The returned unique elements is sorted in the same order as they occur along `axis` in `x`. This operation also returns a tensor `idx` and a tensor `count` that are the same size as the number of the elements in `x` along the `axis` dimension. The `idx` contains the index in the unique output `y` and the `count` contains the count in the unique output `y`. In other words, for an `1-D` tensor `x` with `axis = None:

`y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1]`

For example:

 # tensor 'x' is [1, 1, 2, 4, 4, 4, 7, 8, 8]
 y, idx, count = unique_with_counts(x)
 y ==> [1, 2, 4, 7, 8]
 idx ==> [0, 0, 1, 2, 2, 2, 3, 4, 4]
 count ==> [2, 1, 3, 1, 2]
 

For an `2-D` tensor `x` with `axis = 0`:

 # tensor 'x' is [[1, 0, 0],
 #                [1, 0, 0],
 #                [2, 0, 0]]
 y, idx, count = unique_with_counts(x, axis=0)
 y ==> [[1, 0, 0],
        [2, 0, 0]]
 idx ==> [0, 0, 1]
 count ==> [2, 1]
 

For an `2-D` tensor `x` with `axis = 1`:

 # tensor 'x' is [[1, 0, 0],
 #                [1, 0, 0],
 #                [2, 0, 0]]
 y, idx, count = unique_with_counts(x, axis=1)
 y ==> [[1, 0],
        [1, 0],
        [2, 0]]
 idx ==> [0, 1, 1]
 count ==> [1, 2]
 

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
Output<V>	count() A 1-D Tensor.
static <T,U extends Number> UniqueWithCounts<T,Integer>	create(Scope scope, Operand<T> x, Operand<U> axis) Factory method to create a class wrapping a new UniqueWithCounts operation using default output types.
static <T,V extends Number,U extends Number> UniqueWithCounts<T,V>	create(Scope scope, Operand<T> x, Operand<U> axis, Class<V> outIdx) Factory method to create a class wrapping a new UniqueWithCounts operation.
Output<V>	idx() A 1-D Tensor.
Output<T>	y() A `Tensor`.

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, op, toString

Methods inherited from class java.lang.Object

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

Method Detail

create

public static <T,V extends Number,U extends Number> UniqueWithCounts<T,V> create(Scope scope,
                                                                                 Operand<T> x,
                                                                                 Operand<U> axis,
                                                                                 Class<V> outIdx)

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

Parameters:

scope - current scope

x - A `Tensor`.

axis - A `Tensor` of type `int32` (default: None). The axis of the Tensor to find the unique elements.

outIdx -

Returns:

a new instance of UniqueWithCounts

create

public static <T,U extends Number> UniqueWithCounts<T,Integer> create(Scope scope,
                                                                      Operand<T> x,
                                                                      Operand<U> axis)

Factory method to create a class wrapping a new UniqueWithCounts operation using default output types.

Parameters:

scope - current scope

x - A `Tensor`.

axis - A `Tensor` of type `int32` (default: None). The axis of the Tensor to find the unique elements.

Returns:

a new instance of UniqueWithCounts

y

public Output<T> y()

A `Tensor`. Unique elements along the `axis` of `Tensor` x.

idx

public Output<V> idx()

A 1-D Tensor. Has the same type as x that contains the index of each value of x in the output y.

count

public Output<V> count()

A 1-D Tensor. The count of each value of x in the output y.