tensorflow:: ops:: SoftmaxCrossEntropyWithLogits

#include <nn_ops.h>

Computes softmax cross entropy cost and gradients to backpropagate.

Summary

Inputs are the logits, not probabilities.

Args:

  • scope: A Scope object
  • 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.

Returns:

  • Output loss: Per example loss (batch_size vector).
  • Output backprop: backpropagated gradients (batch_size x num_classes matrix).

Constructors and Destructors

SoftmaxCrossEntropyWithLogits (const :: tensorflow::Scope & scope, :: tensorflow::Input features, :: tensorflow::Input labels)

Public attributes

backprop
loss
operation

Public attributes

backprop 

::tensorflow::Output backprop

loss 

::tensorflow::Output loss

operation 

Operation operation

Public functions

SoftmaxCrossEntropyWithLogits 

 SoftmaxCrossEntropyWithLogits(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input features,
  ::tensorflow::Input labels
)