pub struct MetaTrainingConfig {
pub population: usize,
pub iterations: usize,
pub sigma: f64,
pub meta_learning_rate: f64,
pub horizon: usize,
pub seed: u64,
}Expand description
Hyper-parameters for EsMetaTrainer.
Fields§
§population: usizeNumber of weight perturbations evaluated per iteration. Rounded up to the next even number, because perturbations are drawn in mirrored pairs.
iterations: usizeNumber of ES iterations.
sigma: f64Perturbation standard deviation σ. Too small and the finite-difference
signal drowns in rollout noise; too large and the estimate stops being the
gradient of anything local.
meta_learning_rate: f64Adam step size applied to the estimated meta-gradient.
horizon: usizeInner-loop rollout length: how many optimizer steps each evaluation runs.
seed: u64Seed for the perturbation draws, so a training run is reproducible.
Trait Implementations§
Source§impl Clone for MetaTrainingConfig
impl Clone for MetaTrainingConfig
Source§impl Debug for MetaTrainingConfig
impl Debug for MetaTrainingConfig
Auto Trait Implementations§
impl Freeze for MetaTrainingConfig
impl RefUnwindSafe for MetaTrainingConfig
impl Send for MetaTrainingConfig
impl Sync for MetaTrainingConfig
impl Unpin for MetaTrainingConfig
impl UnsafeUnpin for MetaTrainingConfig
impl UnwindSafe for MetaTrainingConfig
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