SparseCategoricalCrossentropy

Stay organized with collections Save and categorize content based on your preferences.
public class SparseCategoricalCrossentropy

A metric that computes the sparse categorical cross-entropy loss between true labels and predicted labels.

Inherited Constants

Public Constructors

SparseCategoricalCrossentropy(Ops tf, String name, boolean fromLogits, int axis, long seed, Class<T> type)
Creates a SparseCategoricalCrossentropy metric

Public Methods

Operand<T>
call(Operand<? extends TNumber> labels, Operand<? extends TNumber> predictions)
Calculates the weighted loss between labels and predictions

Inherited Methods

Public Constructors

public SparseCategoricalCrossentropy (Ops tf, String name, boolean fromLogits, int axis, long seed, Class<T> type)

Creates a SparseCategoricalCrossentropy metric

Parameters
tf the TensorFlow Ops
name the name of this metric, if null then metric name is getSimpleName().
fromLogits Whether to interpret predictions as a tensor of logit values as opposed to a probability distribution.
axis The dimension along which the entropy is computed.
seed the seed for random number generation. An initializer created with a given seed will always produce the same random tensor for a given shape and data type.
type the type for the variables and result

Public Methods

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

Calculates the weighted loss between labels and predictions

Parameters
labels the truth values or labels
predictions the predictions
Returns
  • the loss