tensorflow:: ops:: SparseSoftmaxCrossEntropyWithLogits

#include <nn_ops.h>

Computes softmax cross entropy cost and gradients to backpropagate.

Summary

Unlike SoftmaxCrossEntropyWithLogits , this operation does not accept a matrix of label probabilities, but rather a single label per row of features. This label is considered to have probability 1.0 for the given row.

Inputs are the logits, not probabilities.

Args:

  • scope: A Scope object
  • features: batch_size x num_classes matrix
  • labels: batch_size vector with values in [0, num_classes). This is the label for the given minibatch entry.

Returns:

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

Constructors and Destructors

SparseSoftmaxCrossEntropyWithLogits (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

SparseSoftmaxCrossEntropyWithLogits 

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