org.tensorflow.op.core

Class OneHot<U>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.OneHot<U>

Type Parameters:

U - data type for output() output

All Implemented Interfaces:

Op, Operand<U>

@Operator
public final class OneHot<U>
extends PrimitiveOp
implements Operand<U>

Returns a one-hot tensor.

The locations represented by indices in `indices` take value `on_value`, while all other locations take value `off_value`.

If the input `indices` is rank `N`, the output will have rank `N+1`, The new axis is created at dimension `axis` (default: the new axis is appended at the end).

If `indices` is a scalar the output shape will be a vector of length `depth`.

If `indices` is a vector of length `features`, the output shape will be:

   features x depth if axis == -1
   depth x features if axis == 0
 

If `indices` is a matrix (batch) with shape `[batch, features]`, the output shape will be:

   batch x features x depth if axis == -1
   batch x depth x features if axis == 1
   depth x batch x features if axis == 0
 

Examples =========

Suppose that

   indices = [0, 2, -1, 1]
   depth = 3
   on_value = 5.0
   off_value = 0.0
   axis = -1
 

Then output is `[4 x 3]`:

 output =
   [5.0 0.0 0.0]  // one_hot(0)
   [0.0 0.0 5.0]  // one_hot(2)
   [0.0 0.0 0.0]  // one_hot(-1)
   [0.0 5.0 0.0]  // one_hot(1)
 

Suppose that

   indices = [0, 2, -1, 1]
   depth = 3
   on_value = 0.0
   off_value = 3.0
   axis = 0
 

Then output is `[3 x 4]`:

 output =
   [0.0 3.0 3.0 3.0]
   [3.0 3.0 3.0 0.0]
   [3.0 3.0 3.0 3.0]
   [3.0 0.0 3.0 3.0]
 //  ^                one_hot(0)
 //      ^            one_hot(2)
 //          ^        one_hot(-1)
 //              ^    one_hot(1)
 

Suppose that

   indices = [[0, 2], [1, -1]]
   depth = 3
   on_value = 1.0
   off_value = 0.0
   axis = -1
 

Then output is `[2 x 2 x 3]`:

 output =
   [
     [1.0, 0.0, 0.0]  // one_hot(0)
     [0.0, 0.0, 1.0]  // one_hot(2)
   ][
     [0.0, 1.0, 0.0]  // one_hot(1)
     [0.0, 0.0, 0.0]  // one_hot(-1)
   ]
 

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	OneHot.Options Optional attributes for OneHot

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
Output<U>	asOutput() Returns the symbolic handle of a tensor.
static OneHot.Options	axis(Long axis)
static <U,T extends Number> OneHot<U>	create(Scope scope, Operand<T> indices, Operand<Integer> depth, Operand<U> onValue, Operand<U> offValue, OneHot.Options... options) Factory method to create a class wrapping a new OneHot operation.
Output<U>	output() The one-hot 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 <U,T extends Number> OneHot<U> create(Scope scope,
                                                    Operand<T> indices,
                                                    Operand<Integer> depth,
                                                    Operand<U> onValue,
                                                    Operand<U> offValue,
                                                    OneHot.Options... options)

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

Parameters:

scope - current scope

indices - A tensor of indices.

depth - A scalar defining the depth of the one hot dimension.

onValue - A scalar defining the value to fill in output when `indices[j] = i`.

offValue - A scalar defining the value to fill in output when `indices[j] != i`.

options - carries optional attributes values

Returns:

a new instance of OneHot

axis

public static OneHot.Options axis(Long axis)

Parameters:

axis - The axis to fill (default: -1, a new inner-most axis).

output

public Output<U> output()

The one-hot tensor.

asOutput

public Output<U> asOutput()

Description copied from interface: Operand

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.

Specified by:

asOutput in interface Operand<U>

See Also:

OperationBuilder.addInput(Output)