pub struct AdaptiveLRConfig<A: Float + Send + Sync> {Show 14 fields
pub base_lr: A,
pub min_lr: A,
pub max_lr: A,
pub enable_gradient_adaptation: bool,
pub enable_performance_adaptation: bool,
pub enable_drift_adaptation: bool,
pub enable_resource_adaptation: bool,
pub enable_meta_learning: bool,
pub history_window_size: usize,
pub adaptation_frequency: usize,
pub adaptation_sensitivity: A,
pub use_ensemble_voting: bool,
pub step_time_budget: Option<Duration>,
pub memory_budget_mb: Option<f64>,
}Expand description
Configuration for adaptive learning rate controller
Fields§
§base_lr: ABase learning rate
min_lr: AMinimum allowed learning rate
max_lr: AMaximum allowed learning rate
enable_gradient_adaptation: boolEnable gradient-based adaptation
enable_performance_adaptation: boolEnable performance-based adaptation
enable_drift_adaptation: boolEnable drift-aware adaptation
enable_resource_adaptation: boolEnable resource-aware adaptation
enable_meta_learning: boolEnable meta-learning optimization
history_window_size: usizeHistory window size
adaptation_frequency: usizeAdaptation frequency (steps)
adaptation_sensitivity: ASensitivity to changes
use_ensemble_voting: boolUse ensemble voting for conflicting signals
step_time_budget: Option<Duration>Wall-clock budget for a single optimizer step, when the deployment has one. Without it there is nothing to measure time pressure against, so the resource signal reports no time term rather than inventing one.
memory_budget_mb: Option<f64>Memory budget in MB, when the deployment has one.
Trait Implementations§
Auto Trait Implementations§
impl<A> Freeze for AdaptiveLRConfig<A>where
A: Freeze,
impl<A> RefUnwindSafe for AdaptiveLRConfig<A>where
A: RefUnwindSafe,
impl<A> Send for AdaptiveLRConfig<A>
impl<A> Sync for AdaptiveLRConfig<A>
impl<A> Unpin for AdaptiveLRConfig<A>where
A: Unpin,
impl<A> UnsafeUnpin for AdaptiveLRConfig<A>where
A: UnsafeUnpin,
impl<A> UnwindSafe for AdaptiveLRConfig<A>where
A: UnwindSafe,
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