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Hinge

public class Hinge

Computes the hinge loss between labels and predictions.

loss = maximum(1 - labels * predictions, 0) .

labels values are expected to be -1 or 1. If binary (0 or 1) labels are provided, they will be converted to -1 or 1.

Standalone usage:

    Operand<TFloat32> labels =
        tf.constant(new float[][] { {0.f, 1.f}, {0.f, 0.f} });
    Operand<TFloat32> predictions =
        tf.constant(new float[][] { {0.6f, 0.4f}, {0.4f, 0.6f} });
    Hinge hingeLoss = new Hinge(tf);
    Operand<TFloat32> result = hingeLoss.call(labels, predictions);
    // produces 1.3f
 

Calling with sample weight:

    Operand<TFloat32> sampleWeight = tf.constant(new float[] {1.f, 0.f});
    Operand<TFloat32> result = hingeLoss.call(labels, predictions, sampleWeight);
    // produces 0.55f
 

Using SUM reduction type:

    Hinge hingeLoss = new Hinge(tf, Reduction.SUM);
    Operand<TFloat32> result = hingeLoss.call(labels, predictions);
    // produces 2.6f
 

Using NONE reduction type:

    Hinge hingeLoss = new Hinge(tf, Reduction.NONE);
    Operand<TFloat32> result = hingeLoss.call(labels, predictions);
    // produces [1.1f, 1.5f]
 

Inherited Fields

Public Constructors

Hinge (Ops tf)
Creates a Hinge Loss using getSimpleName() as the loss name and a Loss Reduction of REDUCTION_DEFAULT
Hinge (Ops tf, Reduction reduction)
Creates a Hinge Loss using getSimpleName() as the loss name
Hinge (Ops tf, String name, Reduction reduction)
Creates a Hinge

Public Methods

<T extends TNumber > Operand <T>
call ( Operand <? extends TNumber > labels, Operand <T> predictions, Operand <T> sampleWeights)
Generates an Operand that calculates the loss.

Inherited Methods

Public Constructors

public Hinge (Ops tf)

Creates a Hinge Loss using getSimpleName() as the loss name and a Loss Reduction of REDUCTION_DEFAULT

Parameters
tf the TensorFlow Ops

public Hinge (Ops tf, Reduction reduction)

Creates a Hinge Loss using getSimpleName() as the loss name

Parameters
tf the TensorFlow Ops
reduction Type of Reduction to apply to the loss.

public Hinge (Ops tf, String name, Reduction reduction)

Creates a Hinge

Parameters
tf the TensorFlow Ops
name the name of the loss
reduction Type of Reduction to apply to the loss.

Public Methods

public Operand <T> call ( Operand <? extends TNumber > labels, Operand <T> predictions, Operand <T> sampleWeights)

Generates an Operand that calculates the loss.

If run in Graph mode, the computation will throw TFInvalidArgumentException if the label values are not in the set [-1., 0., 1.]. In Eager Mode, this call will throw IllegalArgumentException , if the label values are not in the set [-1., 0., 1.].

Parameters
labels the truth values or labels, must be either -1, 0, or 1. Values are expected to be -1 or 1. If binary (0 or 1) labels are provided they will be converted to -1 or 1.
predictions the predictions, values must be in the range [0. to 1.] inclusive.
sampleWeights Optional sampleWeights acts as a coefficient for the loss. If a scalar is provided, then the loss is simply scaled by the given value. If sampleWeights is a tensor of size [batch_size], then the total loss for each sample of the batch is rescaled by the corresponding element in the SampleWeights vector. If the shape of SampleWeights is [batch_size, d0, .. dN-1] (or can be broadcast to this shape), then each loss element of predictions is scaled by the corresponding value of SampleWeights. (Note on dN-1: all loss functions reduce by 1 dimension, usually axis=-1.)
Returns
  • the loss
Throws
IllegalArgumentException if the predictions are outside the range [0.-1.].