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entrenar/optim/
mod.rs

1//! Optimizers for training neural networks
2
3mod adam;
4mod adamw;
5mod clip;
6mod convergence_tests; // Tests split into convergence_tests/ directory
7pub mod dp;
8pub mod hpo;
9mod optimizer;
10mod scheduler;
11mod sgd;
12mod simd;
13
14pub use adam::Adam;
15pub use adamw::AdamW;
16pub use clip::{clip_grad_norm, clip_grad_norm_refs};
17pub use dp::{
18    add_gaussian_noise, clip_gradient, estimate_noise_multiplier, grad_norm, privacy_cost_per_step,
19    DpError, DpSgd, DpSgdConfig, PrivacyBudget, RdpAccountant,
20};
21pub use hpo::{
22    AcquisitionFunction, GridSearch, HPOError, HyperbandScheduler, HyperparameterSpace,
23    ParameterDomain, ParameterValue, SearchStrategy, SurrogateModel, TPEOptimizer, Trial,
24    TrialStatus,
25};
26pub use optimizer::Optimizer;
27pub use scheduler::{
28    CosineAnnealingLR, LRScheduler, LinearWarmupLR, StepDecayLR, WarmupCosineDecayLR,
29};
30pub use sgd::SGD;
31pub use simd::{simd_adam_update, simd_adamw_update, simd_axpy};