Defined in tensorflow/contrib/losses/__init__.py.
Ops for building neural network losses.
See Losses (contrib).
metric_learning module: Ops for building neural network losses.
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)
__cached__
__loader__
__spec__
© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/contrib/losses