SoftmaxCrossEntropyWithLogits

public final class SoftmaxCrossEntropyWithLogits

Computes softmax cross entropy cost and gradients to backpropagate.

Inputs are the logits, not probabilities.

String OP_NAME The name of this op, as known by TensorFlow core engine

Output<T>	backprop() backpropagated gradients (batch_size x num_classes matrix).
static <T extends TNumber> SoftmaxCrossEntropyWithLogits<T>	create(Scope scope, Operand<T> features, Operand<T> labels) Factory method to create a class wrapping a new SoftmaxCrossEntropyWithLogits operation.
Output<T>	loss() Per example loss (batch_size vector).

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single `Operation`.
final String	toString()

From class java.lang.Object

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single `Operation`.

Constants

The name of this op, as known by TensorFlow core engine

Constant Value: "SoftmaxCrossEntropyWithLogits"

backpropagated gradients (batch_size x num_classes matrix).

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

scope	current scope
features	batch_size x num_classes matrix
labels	batch_size x num_classes matrix The caller must ensure that each batch of labels represents a valid probability distribution.

Per example loss (batch_size vector).