LossesHelper

public class LossesHelper

These are helper methods for Losses and Metrics and will be module private when Java modularity is applied to TensorFlow Java. These methods should not be used outside of the losses and metrics packages.

Public Constructors

LossesHelper()

Public Methods

static <T extends TNumber> Operand<TInt32>	allAxes(Ops tf, Operand<T> op) Gets a Constant integer array representing all the axes of the operand.
static <T extends TNumber> Operand<T>	computeWeightedLoss(Ops tf, Operand<T> loss, Reduction reduction, Operand<T> sampleWeight) Computes the weighted loss
static <T extends TNumber> Operand<T>	rangeCheck(Ops tf, String prefix, Operand<T> values, Operand<T> minValue, Operand<T> maxValue) Perform an inclusive range check on the values
static <T extends TNumber> LossTuple<T>	removeSqueezableDimensions(Ops tf, Operand<T> labels, Operand<T> predictions) Squeeze last dim if ranks differ from expected by exactly 1.
static <T extends TNumber> LossTuple<T>	removeSqueezableDimensions(Ops tf, Operand<T> labels, Operand<T> predictions, int expectedRankDiff) Squeeze last dim if ranks differ from expected by exactly 1.
static <T extends TNumber> Operand<T>	safeMean(Ops tf, Operand<T> losses, long numElements) Computes a safe mean of the losses.
static <T extends TNumber> LossTuple<T>	squeezeOrExpandDimensions(Ops tf, Operand<T> labels, Operand<T> predictions) Squeeze or expand last dimension if needed with a sampleWeights of one.
static <T extends TNumber> LossTuple<T>	squeezeOrExpandDimensions(Ops tf, Operand<T> labels, Operand<T> predictions, Operand<T> sampleWeights) Squeeze or expand last dimension if needed.
static <T extends TNumber> Operand<T>	valueCheck(Ops tf, String prefix, Operand<T> values, Operand<T> allowedValues) Checks to see if all the values are in the allowed values set.

Inherited Methods

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

Public Constructors

public LossesHelper ()

Public Methods

public static Operand<TInt32> allAxes (Ops tf, Operand<T> op)

Gets a Constant integer array representing all the axes of the operand.

Parameters

tf	the TensorFlow Ops
op	the TensorFlow Ops

Returns

• a Constant that represents all the axes of the operand.

public static Operand<T> computeWeightedLoss (Ops tf, Operand<T> loss, Reduction reduction, Operand<T> sampleWeight)

Computes the weighted loss

Parameters

tf	the TensorFlow Ops
loss	the unweighted loss
reduction	the type of reduction
sampleWeight	the sample weight, if null then this defaults to one.

Returns

• the weighted loss

public static Operand<T> rangeCheck (Ops tf, String prefix, Operand<T> values, Operand<T> minValue, Operand<T> maxValue)

Perform an inclusive range check on the values

Parameters

tf	the TensorFlow Ops
prefix	A String prefix to include in the error message
values	the values to check
minValue	the minimum value
maxValue	the maximum value

Returns

• the values possibly with control dependencies if the TensorFlow Ops represents a Graph Session

Throws

IllegalArgumentException	if the TensorFlow Ops represents an Eager Session

public static LossTuple<T> removeSqueezableDimensions (Ops tf, Operand<T> labels, Operand<T> predictions)

Squeeze last dim if ranks differ from expected by exactly 1.

Parameters

tf	the TensorFlowOps
labels	Label values, a Tensor whose dimensions match predictions .
predictions	Predicted values, a Tensor of arbitrary dimensions.

Returns

• labels and predictions, possibly with last dim squeezed.

public static LossTuple<T> removeSqueezableDimensions (Ops tf, Operand<T> labels, Operand<T> predictions, int expectedRankDiff)

Squeeze last dim if ranks differ from expected by exactly 1.

Parameters

tf	the TensorFlowOps
labels	Label values, a Operand whose dimensions match predictions .
predictions	Predicted values, a Tensor of arbitrary dimensions.
expectedRankDiff	Expected result of rank(predictions) - rank(labels).

Returns

• labels and predictions, possibly with last dim squeezed.

public static Operand<T> safeMean (Ops tf, Operand<T> losses, long numElements)

Computes a safe mean of the losses.

Parameters

tf	the TensorFlow Ops
losses	Operand whose elements contain individual loss measurements.
numElements	The number of measurable elements in losses.

Returns

• A scalar representing the mean of losses. If numElements is zero, then zero is returned.

public static LossTuple<T> squeezeOrExpandDimensions (Ops tf, Operand<T> labels, Operand<T> predictions)

Squeeze or expand last dimension if needed with a sampleWeights of one.

1. Squeezes last dim of predictions or labels if their rank differs by 1 (using removeSqueezableDimensions(Ops, Operand<T>, Operand<T>)).
2. Squeezes or expands last dim of sampleWeight if its rank differs by 1 from the new rank of predictions. If sampleWeight is scalar, it is kept scalar.

Parameters

tf	the TensorFlow Ops
labels	Optional label Operand whose dimensions match prediction .
predictions	Predicted values, a Operand of arbitrary dimensions.

Returns

• LossTuple of prediction, label,sampleWeight will be null. Each of them possibly has the last dimension squeezed, sampleWeight could be extended by one dimension. If sampleWeight is null, (prediction, label) is returned.

public static LossTuple<T> squeezeOrExpandDimensions (Ops tf, Operand<T> labels, Operand<T> predictions, Operand<T> sampleWeights)

Squeeze or expand last dimension if needed.

1. Squeezes last dim of predictions or labels if their rank do not differ by 1.
2. Squeezes or expands last dim of sampleWeight if its rank differs by 1 from the new rank of predictions. If sampleWeight is scalar, it is kept scalar.

Parameters

tf	the TensorFlow Ops
labels	Optional label Operand whose dimensions match prediction .
predictions	Predicted values, a Operand of arbitrary dimensions.
sampleWeights	Optional sample weight(s) Operand whose dimensions match prediction.

Returns

• LossTuple of predictions, labels and sampleWeight . Each of them possibly has the last dimension squeezed, sampleWeight could be extended by one dimension. If sampleWeight is null, only the possibly shape modified predictions and labels are returned.

public static Operand<T> valueCheck (Ops tf, String prefix, Operand<T> values, Operand<T> allowedValues)

Checks to see if all the values are in the allowed values set. Running the operand in Graph mode will throw TFInvalidArgumentException, if at least one value is not in the allowed values set. In Eager mode, this method will throw an IllegalArgumentException if at least one value is not in the allowed values set.

Parameters

tf	The TensorFlow Ops
prefix	A String prefix to include in the error message
values	the values to check
allowedValues	the allowed values

Returns

• the values possibly with control dependencies if the TensorFlow Ops represents a Graph Session

Throws

IllegalArgumentException	if the Session is in Eager mode and at least one value is not in the allowed values set