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Ops for building neural network losses.
See Contrib Losses.
Modules
metric_learning
module: Ops for building neural network losses.
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)