energy_optim - Module

`struct EnergyAwareOptimizer`

Wrapper that adds energy awareness to any optimizer

Source: energy_optim.joule:20

`enum EnergyOptimMode`

Source: energy_optim.joule:60

`struct EnergyOptimConfig`

Source: energy_optim.joule:75

`fn default() -> Self`

Source: energy_optim.joule:102

`fn new(inner: O, energy_tracker: Arc<EnergyTracker>) -> Self`

Create new energy-aware optimizer

Source: energy_optim.joule:118

`fn with_budget(mut self, budget: EnergyBudget) -> Self`

Set energy budget

Source: energy_optim.joule:136

`fn with_target_efficiency(mut self, efficiency: f64) -> Self`

Set target efficiency

Source: energy_optim.joule:143

`fn with_mode(mut self, mode: EnergyOptimMode) -> Self`

Set mode

Source: energy_optim.joule:150

`fn with_config(mut self, config: EnergyOptimConfig) -> Self`

Set configuration

Source: energy_optim.joule:156

`fn begin_step(&mut self)`

Begin step (call before forward/backward)

Source: energy_optim.joule:162

`fn record_loss(&mut self, loss: f64, prev_loss: f64)`

Record loss for efficiency calculation

Source: energy_optim.joule:168

`fn should_skip(&self) -> bool`

Should skip this update (if inefficient)?

Source: energy_optim.joule:179

`fn step_energy(&self) -> Joules`

Get energy consumed this step

Source: energy_optim.joule:192

`fn current_efficiency(&self) -> f64`

Get current efficiency estimate

Source: energy_optim.joule:197

`fn total_energy(&self) -> Joules`

Get total energy consumed

Source: energy_optim.joule:202

`fn lr_scale(&self) -> f64`

Get learning rate scale

Source: energy_optim.joule:207

`fn remaining_budget(&self) -> Option<Joules>`

Get remaining budget

Source: energy_optim.joule:212

`fn step(&mut self)`

Source: energy_optim.joule:219

`fn zero_grad(&mut self)`

Source: energy_optim.joule:289

`fn get_lr(&self) -> f64`

Source: energy_optim.joule:293

`fn set_lr(&mut self, lr: f64)`

Source: energy_optim.joule:297

`fn state_dict(&self) -> HashMap<String, Tensor>`

Source: energy_optim.joule:301

`fn load_state_dict(&mut self, state: &HashMap<String, Tensor>)`

Source: energy_optim.joule:305

`fn adapt_learning_rate(&mut self)`

Adapt learning rate based on efficiency

Source: energy_optim.joule:312

`struct ScheduledPowerOptimizer`

Optimizer with scheduled power states (like GPU P-states)

Source: energy_optim.joule:366

`struct PowerPhase`

Source: energy_optim.joule:376

`fn new(inner: O, energy_tracker: Arc<EnergyTracker>) -> Self`

Source: energy_optim.joule:390

`fn with_warmup(mut self, steps: u64) -> Self`

Add warmup phase (low power, low learning rate)

Source: energy_optim.joule:409

`fn with_cooldown(mut self, steps: u64) -> Self`

Add cooldown phase (low power)

Source: energy_optim.joule:421

`fn with_high_perf_phase(mut self, steps: u64) -> Self`

Add high-performance phase

Source: energy_optim.joule:433

`fn current_phase(&self) -> &PowerPhase`

Get current phase

Source: energy_optim.joule:452

`fn advance_phase(&mut self)`

Source: energy_optim.joule:456

`fn step(&mut self)`

Source: energy_optim.joule:476

`fn zero_grad(&mut self)`

Source: energy_optim.joule:492

`fn get_lr(&self) -> f64`

Source: energy_optim.joule:496

`fn set_lr(&mut self, lr: f64)`

Source: energy_optim.joule:500

`fn state_dict(&self) -> HashMap<String, Tensor>`

Source: energy_optim.joule:504

`fn load_state_dict(&mut self, state: &HashMap<String, Tensor>)`

Source: energy_optim.joule:508

`struct CheckpointingOptimizer`

Optimizer that uses gradient checkpointing for memory/energy trade-off

Source: energy_optim.joule:518

`fn new(inner: O, checkpoint_every: usize) -> Self`

Source: energy_optim.joule:526

`fn recompute_count(&self) -> u64`

Get number of recomputes performed

Source: energy_optim.joule:536

`fn saved_compute_energy(&self) -> Joules`

Get estimated saved compute energy (from not storing all activations)

Source: energy_optim.joule:541

`fn step(&mut self)`

Source: energy_optim.joule:547

`fn zero_grad(&mut self)`

Source: energy_optim.joule:551

`fn get_lr(&self) -> f64`

Source: energy_optim.joule:555

`fn set_lr(&mut self, lr: f64)`

Source: energy_optim.joule:559

`fn state_dict(&self) -> HashMap<String, Tensor>`

Source: energy_optim.joule:563

`fn load_state_dict(&mut self, state: &HashMap<String, Tensor>)`

Source: energy_optim.joule:567

`struct LazyOptimizer`

Optimizer that defers updates until beneficial

Source: energy_optim.joule:577

`fn new(inner: O, energy_tracker: Arc<EnergyTracker>, update_threshold: f64) -> Self`

Source: energy_optim.joule:588

`fn total_deferred(&self) -> u64`

Get number of deferred updates

Source: energy_optim.joule:601

`fn energy_saved(&self) -> Joules`

Get energy saved by deferring

Source: energy_optim.joule:606

`fn should_update(&self, grad_norm: f64) -> bool`

Check if gradients are significant enough to update

Source: energy_optim.joule:611

`fn step(&mut self)`

Source: energy_optim.joule:617

`fn zero_grad(&mut self)`

Source: energy_optim.joule:622

`fn get_lr(&self) -> f64`

Source: energy_optim.joule:626

`fn set_lr(&mut self, lr: f64)`

Source: energy_optim.joule:630

`fn state_dict(&self) -> HashMap<String, Tensor>`

Source: energy_optim.joule:634

`fn load_state_dict(&mut self, state: &HashMap<String, Tensor>)`

Source: energy_optim.joule:638

`struct MixedPrecisionEnergyOptimizer`

Optimizer that dynamically adjusts precision for energy efficiency

Source: energy_optim.joule:648

`enum PrecisionMode`

Source: energy_optim.joule:662

`fn new(inner: O, energy_tracker: Arc<EnergyTracker>, mode: PrecisionMode) -> Self`

Source: energy_optim.joule:674

`fn loss_scale(&self) -> f64`

Get current loss scale

Source: energy_optim.joule:689

`fn precision_mode(&self) -> PrecisionMode`

Get current precision mode

Source: energy_optim.joule:694

`fn update_scale(&mut self, found_inf: bool)`

Update loss scale based on gradient health

Source: energy_optim.joule:699

`fn step(&mut self)`

Source: energy_optim.joule:721

`fn zero_grad(&mut self)`

Source: energy_optim.joule:726

`fn get_lr(&self) -> f64`

Source: energy_optim.joule:730

`fn set_lr(&mut self, lr: f64)`

Source: energy_optim.joule:734

`fn state_dict(&self) -> HashMap<String, Tensor>`

Source: energy_optim.joule:738

`fn load_state_dict(&mut self, state: &HashMap<String, Tensor>)`

Source: energy_optim.joule:742

`fn energy_adam(`

Create energy-aware Adam optimizer

Source: energy_optim.joule:752

`fn energy_adamw(`

Create energy-aware AdamW optimizer

Source: energy_optim.joule:762

`fn energy_sgd(`

Create energy-aware SGD optimizer

Source: energy_optim.joule:773

`fn budget_optimizer<O: Optimizer>(`

Create budget-constrained optimizer

Source: energy_optim.joule:784

`fn max_efficiency_optimizer<O: Optimizer>(`

Create efficiency-maximizing optimizer

Source: energy_optim.joule:794

`fn test_energy_aware_optimizer()`

Source: energy_optim.joule:814

`fn test_power_phases()`

Source: energy_optim.joule:824