LostTech.TensorFlow : API Documentation

Type metric_learning

Namespace tensorflow.contrib.losses.metric_learning

Methods

Properties

Fields

Public static methods

object cluster_loss(IGraphNodeBase labels, IGraphNodeBase embeddings, double margin_multiplier, bool enable_pam_finetuning, string margin_type, bool print_losses)

object cluster_loss_dyn(object labels, object embeddings, object margin_multiplier, ImplicitContainer<T> enable_pam_finetuning, ImplicitContainer<T> margin_type, ImplicitContainer<T> print_losses)

Tensor compute_augmented_facility_locations(string pairwise_distances, IGraphNodeBase labels, IGraphNodeBase all_ids, double margin_multiplier, string margin_type)

Tensor compute_augmented_facility_locations(object pairwise_distances, IGraphNodeBase labels, IGraphNodeBase all_ids, double margin_multiplier, string margin_type)

Tensor compute_augmented_facility_locations(IGraphNodeBase pairwise_distances, IGraphNodeBase labels, IGraphNodeBase all_ids, double margin_multiplier, string margin_type)

object compute_augmented_facility_locations_dyn(object pairwise_distances, object labels, object all_ids, object margin_multiplier, object margin_type)

object compute_augmented_facility_locations_pam(string pairwise_distances, IGraphNodeBase labels, double margin_multiplier, string margin_type, object chosen_ids, int pam_max_iter)

object compute_augmented_facility_locations_pam(object pairwise_distances, IGraphNodeBase labels, double margin_multiplier, string margin_type, object chosen_ids, int pam_max_iter)

object compute_augmented_facility_locations_pam(IGraphNodeBase pairwise_distances, IGraphNodeBase labels, double margin_multiplier, string margin_type, object chosen_ids, int pam_max_iter)

object compute_augmented_facility_locations_pam_dyn(object pairwise_distances, object labels, object margin_multiplier, object margin_type, object chosen_ids, ImplicitContainer<T> pam_max_iter)

Tensor compute_clustering_score(IGraphNodeBase labels, IGraphNodeBase predictions, string margin_type)

object compute_clustering_score_dyn(object labels, object predictions, object margin_type)

object compute_facility_energy(IGraphNodeBase pairwise_distances, object centroid_ids)

object compute_facility_energy(object pairwise_distances, object centroid_ids)

object compute_facility_energy(string pairwise_distances, object centroid_ids)

object compute_facility_energy_dyn(object pairwise_distances, object centroid_ids)

Tensor compute_gt_cluster_score(IGraphNodeBase pairwise_distances, IGraphNodeBase labels)

Tensor compute_gt_cluster_score(object pairwise_distances, IGraphNodeBase labels)

Tensor compute_gt_cluster_score(string pairwise_distances, IGraphNodeBase labels)

object compute_gt_cluster_score_dyn(object pairwise_distances, object labels)

Tensor contrastive_loss(IGraphNodeBase labels, IGraphNodeBase embeddings_anchor, IGraphNodeBase embeddings_positive, double margin)

object contrastive_loss_dyn(object labels, object embeddings_anchor, object embeddings_positive, ImplicitContainer<T> margin)

Tensor get_cluster_assignment(string pairwise_distances, IGraphNodeBase centroid_ids)

Tensor get_cluster_assignment(object pairwise_distances, IGraphNodeBase centroid_ids)

Tensor get_cluster_assignment(IGraphNodeBase pairwise_distances, IGraphNodeBase centroid_ids)

object get_cluster_assignment_dyn(object pairwise_distances, object centroid_ids)

Tensor lifted_struct_loss(IGraphNodeBase labels, IGraphNodeBase embeddings, double margin)

object lifted_struct_loss_dyn(object labels, object embeddings, ImplicitContainer<T> margin)

object masked_maximum(IGraphNodeBase data, ValueTuple<PythonClassContainer, PythonClassContainer> mask, int dim)

object masked_maximum(object data, IGraphNodeBase mask, int dim)

object masked_maximum(IGraphNodeBase data, IGraphNodeBase mask, int dim)

object masked_maximum(object data, IndexedSlices mask, int dim)

object masked_maximum(object data, ValueTuple<PythonClassContainer, PythonClassContainer> mask, int dim)

object masked_maximum(string data, IGraphNodeBase mask, int dim)

object masked_maximum(string data, IndexedSlices mask, int dim)

object masked_maximum(string data, ValueTuple<PythonClassContainer, PythonClassContainer> mask, int dim)

object masked_maximum(IGraphNodeBase data, IndexedSlices mask, int dim)

object masked_maximum_dyn(object data, object mask, ImplicitContainer<T> dim)

object masked_minimum(IGraphNodeBase data, IGraphNodeBase mask, int dim)

object masked_minimum(IGraphNodeBase data, IndexedSlices mask, int dim)

object masked_minimum(IGraphNodeBase data, ValueTuple<PythonClassContainer, PythonClassContainer> mask, int dim)

object masked_minimum_dyn(object data, object mask, ImplicitContainer<T> dim)

object npairs_loss(IGraphNodeBase labels, IGraphNodeBase embeddings_anchor, IGraphNodeBase embeddings_positive, double reg_lambda, bool print_losses)

object npairs_loss_dyn(object labels, object embeddings_anchor, object embeddings_positive, ImplicitContainer<T> reg_lambda, ImplicitContainer<T> print_losses)

object npairs_loss_multilabel(IEnumerable<SparseTensor> sparse_labels, IGraphNodeBase embeddings_anchor, IGraphNodeBase embeddings_positive, double reg_lambda, bool print_losses)

object npairs_loss_multilabel_dyn(object sparse_labels, object embeddings_anchor, object embeddings_positive, ImplicitContainer<T> reg_lambda, ImplicitContainer<T> print_losses)

object pairwise_distance(IGraphNodeBase feature, bool squared)

object pairwise_distance_dyn(object feature, ImplicitContainer<T> squared)

Tensor triplet_semihard_loss(IGraphNodeBase labels, IGraphNodeBase embeddings, double margin)

object triplet_semihard_loss_dyn(object labels, object embeddings, ImplicitContainer<T> margin)

Tensor update_1d_tensor(IGraphNodeBase y, object index, IGraphNodeBase value)

Tensor update_1d_tensor(IGraphNodeBase y, object index, IndexedSlices value)

Tensor update_1d_tensor(IGraphNodeBase y, object index, ValueTuple<PythonClassContainer, PythonClassContainer> value)

object update_1d_tensor_dyn(object y, object index, object value)

object update_all_medoids(object pairwise_distances, IGraphNodeBase predictions, IGraphNodeBase labels, object chosen_ids, object margin_multiplier, string margin_type)

object update_all_medoids_dyn(object pairwise_distances, object predictions, object labels, object chosen_ids, object margin_multiplier, object margin_type)

Tensor update_medoid_per_cluster(object pairwise_distances, IGraphNodeBase pairwise_distances_subset, IGraphNodeBase labels, IGraphNodeBase chosen_ids, IGraphNodeBase cluster_member_ids, IGraphNodeBase cluster_idx, object margin_multiplier, string margin_type)

Tensor update_medoid_per_cluster(object pairwise_distances, IGraphNodeBase pairwise_distances_subset, IGraphNodeBase labels, IGraphNodeBase chosen_ids, IGraphNodeBase cluster_member_ids, int cluster_idx, object margin_multiplier, string margin_type)

object update_medoid_per_cluster_dyn(object pairwise_distances, object pairwise_distances_subset, object labels, object chosen_ids, object cluster_member_ids, object cluster_idx, object margin_multiplier, object margin_type)

Public properties

PythonFunctionContainer cluster_loss_fn get;

PythonFunctionContainer compute_augmented_facility_locations_fn get;

PythonFunctionContainer compute_augmented_facility_locations_pam_fn get;

PythonFunctionContainer compute_clustering_score_fn get;

PythonFunctionContainer compute_facility_energy_fn get;

PythonFunctionContainer compute_gt_cluster_score_fn get;

PythonFunctionContainer contrastive_loss_fn get;

PythonFunctionContainer get_cluster_assignment_fn get;

PythonFunctionContainer lifted_struct_loss_fn get;

PythonFunctionContainer masked_maximum_fn get;

PythonFunctionContainer masked_minimum_fn get;

PythonFunctionContainer npairs_loss_fn get;

PythonFunctionContainer npairs_loss_multilabel_fn get;

PythonFunctionContainer pairwise_distance_fn get;

PythonFunctionContainer triplet_semihard_loss_fn get;

PythonFunctionContainer update_1d_tensor_fn get;

PythonFunctionContainer update_all_medoids_fn get;

PythonFunctionContainer update_medoid_per_cluster_fn get;

Public fields

bool HAS_SKLEARN

return bool