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Library APIs for Neural Structured Learning.
class GenNeighbor: Abstract class for generating neighbors.
adv_regularizer(...): Calculates adversarial loss from generated adversarial samples.
apply_feature_mask(...): Applies a feature mask on features if the mask is not None.
bimodal_integration(...): Compute the bimodal integration between x and y.
decay_over_time(...): Returns a decayed value of init_value over time.
gen_adv_neighbor(...): Functional interface of _GenAdvNeighbor.
get_target_indices(...): Selects targeting classes for adversarial attack (classification only).
jensen_shannon_divergence(...): Adds a Jensen-Shannon divergence to the training procedure.
kl_divergence(...): Adds a KL-divergence to the training procedure.
maximize_within_unit_norm(...): Solves the maximization problem weights^T*x with the constraint norm(x)=1.
normalize(...): Normalizes the values in tensor with respect to the specified vector norm.
pairwise_distance_wrapper(...): A wrapper to compute pairwise distance between sources and targets.
replicate_embeddings(...): Replicates the embeddings by
unpack_neighbor_features(...): Extracts sample features, neighbor features, and neighbor weights.
virtual_adv_regularizer(...): API to calculate virtual adversarial loss for given input.