tf.contrib.losses

 

upper level

 

Modules

 

metric_learning:

Ops for building neural network losses.

 

Classes

 

None

 

Functions

 

absolute_difference(…):

Adds an Absolute Difference loss to the training procedure. (deprecated)

add_loss(…):

Adds a externally defined loss to the collection of losses. (deprecated)

compute_weighted_loss(…):

Computes the weighted loss. (deprecated)

cosine_distance(…):

Adds a cosine-distance loss to the training procedure. (deprecated arguments) (deprecated)

get_losses(…):

Gets the list of losses from the loss_collection. (deprecated)

get_regularization_losses(…):

Gets the regularization losses. (deprecated)

get_total_loss(…):

Returns a tensor whose value represents the total loss. (deprecated)

hinge_loss(…):

Method that returns the loss tensor for hinge loss. (deprecated)

log_loss(…):

Adds a Log Loss term to the training procedure. (deprecated)

mean_pairwise_squared_error(…):

Adds a pairwise-errors-squared loss to the training procedure. (deprecated)

mean_squared_error(…):

Adds a Sum-of-Squares loss to the training procedure. (deprecated)

sigmoid_cross_entropy(…):

Creates a cross-entropy loss using tf.nn.sigmoid_cross_entropy_with_logits. (deprecated)

softmax_cross_entropy(…):

Creates a cross-entropy loss using tf.nn.softmax_cross_entropy_with_logits. (deprecated)

sparse_softmax_cross_entropy(…):

Cross-entropy loss using tf.nn.sparse_softmax_cross_entropy_with_logits. (deprecated)