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opennn::Adam Member List
This is the complete list of members for opennn::Adam, including all inherited members.
| Adam(Loss *=nullptr) | opennn::Adam | explicit |
| batch_pool_size_override | opennn::Optimizer | protected |
| batch_size | opennn::Optimizer | protected |
| can_use_cuda_graph() const | opennn::Optimizer | inlineprotected |
| clip_gradient_norm(BackPropagation &, float) | opennn::Optimizer | protectedstatic |
| close_training_result(TrainingResult &, const EpochReport &, bool has_validation) const | opennn::Optimizer | protected |
| configure_for_task(NetworkTask) override | opennn::Adam | virtual |
| cuda_graph_capture_failed | opennn::Optimizer | protected |
| DataSlot enum name | opennn::Adam | |
| default_workers_number | opennn::Optimizer | protectedstatic |
| display | opennn::Optimizer | protected |
| display_epoch_results(Index epoch, float training_error, float training_accuracy, float validation_error, float validation_accuracy, bool has_validation, bool validation_fresh, bool is_token_cross_entropy, float elapsed_time) const | opennn::Optimizer | protected |
| display_period | opennn::Optimizer | protected |
| evaluate_epoch(ForwardPropagation &, ThreadSafeQueue< Batch * > &, const vector< vector< Index > > &, const FeatureSelection &, TrainingSession &) | opennn::Optimizer | protected |
| find_stopping_condition(const EpochReport &, float minimum_loss_decrease=-MAX) const | opennn::Optimizer | protected |
| from_JSON(const JsonDocument &) override | opennn::Adam | virtual |
| get_batch_pool_size(const Network &) const | opennn::Optimizer | protected |
| get_batch_size() const noexcept | opennn::Optimizer | inline |
| get_bf16_first_moment() const noexcept | opennn::Adam | inline |
| get_cuda_graph_capture_failed() const noexcept | opennn::Optimizer | inline |
| get_display() const noexcept | opennn::Optimizer | inline |
| get_epoch_budget() const noexcept | opennn::Optimizer | inlineprotected |
| get_epsilon() const noexcept | opennn::Adam | inline |
| get_learning_rate() const | opennn::Adam | inline |
| get_loss() const noexcept | opennn::Optimizer | inline |
| get_maximum_batch_size() const | opennn::Optimizer | |
| get_maximum_epochs() const noexcept | opennn::Optimizer | inline |
| get_name() const noexcept | opennn::Optimizer | inline |
| gradient_clip_norm | opennn::Optimizer | protected |
| GradientMoment enum value | opennn::Adam | |
| GraphScalars enum value | opennn::Adam | |
| joint_gradient_arena | opennn::Optimizer | protected |
| load(const filesystem::path &) | opennn::Optimizer | |
| loss | opennn::Optimizer | protected |
| maximum_epochs | opennn::Optimizer | protected |
| maximum_time | opennn::Optimizer | protected |
| maximum_validation_failures | opennn::Optimizer | protected |
| name | opennn::Optimizer | protected |
| network_has_active_dropout() const | opennn::Optimizer | protected |
| on_epoch_begin(Index, OptimizerData &) override | opennn::Adam | virtual |
| Optimizer(Loss *=nullptr) | opennn::Optimizer | explicit |
| post_batch_callback | opennn::Optimizer | |
| post_best_callback | opennn::Optimizer | |
| post_epoch_callback | opennn::Optimizer | |
| prefetch_batch(Batch &) | opennn::Optimizer | protected |
| prepare_full_batch_training(FullBatchContext &, const char *banner) | opennn::Optimizer | protected |
| prepare_training_artifacts() | opennn::Optimizer | protected |
| read_common_json(const Json *) | opennn::Optimizer | protected |
| restore_best | opennn::Optimizer | protected |
| restore_best_parameters(Network *, TrainingResult &, const BestModelSnapshot &) | opennn::Optimizer | protected |
| run_epoch_loop(EpochLoopContext &) | opennn::Optimizer | protected |
| run_graph_epoch(TrainingSession &, OptimizerData &, ForwardPropagation &, BackPropagation &, ThreadSafeQueue< Batch * > &, const vector< vector< Index > > &, const FeatureSelection &) | opennn::Optimizer | protected |
| save(const filesystem::path &) const | opennn::Optimizer | |
| set(Loss *new_loss) | opennn::Optimizer | inline |
| set_batch_pool_size(int size) | opennn::Optimizer | inline |
| set_batch_size(const Index new_batch_size) | opennn::Optimizer | inline |
| set_beta_1(const float) | opennn::Adam | |
| set_beta_2(const float) | opennn::Adam | |
| set_bf16_first_moment(const bool enabled) | opennn::Adam | inline |
| set_cuda_graph(bool enabled) | opennn::Optimizer | inline |
| set_display(bool new_display) | opennn::Optimizer | inlinevirtual |
| set_display_period(const Index new_display_period) | opennn::Optimizer | inline |
| set_epsilon(float) | opennn::Adam | |
| set_gradient_clip_norm(const float new_clip) | opennn::Optimizer | inline |
| set_joint_gradient_arena(bool enabled) noexcept | opennn::Optimizer | inline |
| set_learning_rate(const float new_learning_rate) | opennn::Adam | inline |
| set_loss_goal(const float new_loss_goal) | opennn::Optimizer | inline |
| set_maximum_epochs(const Index new_maximum_epochs) | opennn::Optimizer | inline |
| set_maximum_time(const float new_maximum_time) | opennn::Optimizer | inline |
| set_maximum_validation_failures(const Index new_maximum_validation_failures) | opennn::Optimizer | inline |
| set_names() | opennn::Optimizer | protected |
| set_restore_best(bool enabled) | opennn::Optimizer | inline |
| set_shuffle(bool enabled) | opennn::Optimizer | inline |
| set_validation_period(const Index n) | opennn::Optimizer | inline |
| set_workers_number(int new_workers_number) | opennn::Optimizer | inline |
| setup_batch_pools(BatchPools &pools, Dataset &dataset, Network &network, Index training_batch_size, Index validation_batch_size, bool has_validation, TrainingSession &training_session) | opennn::Optimizer | protected |
| setup_device_training() | opennn::Optimizer | protected |
| should_display(Index epoch) const noexcept | opennn::Optimizer | inlineprotected |
| shuffle_samples | opennn::Optimizer | protected |
| SquareGradientMoment enum value | opennn::Adam | |
| start_batch_prefetch(ThreadSafeQueue< Batch * > &, const vector< vector< Index > > &, const FeatureSelection &, FillMode, WorkerProfileCounters *profile_counters=nullptr) | opennn::Optimizer | protected |
| StoppingCondition typedef | opennn::Optimizer | |
| sync_device(bool on_gpu, bool has_recurrent_layers, TrainingSession &) | opennn::Optimizer | protected |
| teardown_device_training() | opennn::Optimizer | protected |
| to_JSON(JsonWriter &) const override | opennn::Adam | virtual |
| train() | opennn::Optimizer | virtual |
| train_epoch(TrainingContext &, ThreadSafeQueue< Batch * > &, const vector< vector< Index > > &, const FeatureSelection &, TrainingSession &, OptimizerData &) | opennn::Optimizer | protected |
| train_full_batch(FullBatchContext &, const FullBatchHooks &) | opennn::Optimizer | protected |
| training_loss_goal | opennn::Optimizer | protected |
| update_best_parameters(Network *, float, Index, Index &, BestModelSnapshot &) | opennn::Optimizer | protected |
| update_parameters(BackPropagation &, OptimizerData &, UpdateMode=UpdateMode::Standard) override | opennn::Adam | virtual |
| UpdateMode enum name | opennn::Optimizer | protected |
| use_cuda_graph | opennn::Optimizer | protected |
| uses_joint_gradient_arena() const noexcept | opennn::Optimizer | protected |
| validation_period | opennn::Optimizer | protected |
| warmup_device_training(TrainingContext &, ThreadSafeQueue< Batch * > &, const vector< vector< Index > > &, const FeatureSelection &, TrainingSession &, OptimizerData &, ForwardPropagation *validation_forward_propagation=nullptr, ThreadSafeQueue< Batch * > *validation_empty_queue=nullptr, const vector< vector< Index > > *validation_batches=nullptr) | opennn::Optimizer | protected |
| workers_number | opennn::Optimizer | protected |
| write_common_json(JsonWriter &) const | opennn::Optimizer | protected |
| ~Optimizer() | opennn::Optimizer | virtual |
