Struct TrainerConfig

pub struct TrainerConfig {
    pub max_opts: usize,
    pub model_dir: Option<String>,
    pub opt_interval: usize,
    pub eval_interval: usize,
    pub flush_record_interval: usize,
    pub record_compute_cost_interval: usize,
    pub record_agent_info_interval: usize,
    pub warmup_period: usize,
    pub save_interval: usize,
}

Configuration of Trainer.

Fields

max_opts: usize

The maximum number of optimization steps.

model_dir: Option<String>

Directory where model parameters will be saved.

opt_interval: usize

Interval of optimization steps in environment steps.

eval_interval: usize

Interval of evaluation in optimization steps.

flush_record_interval: usize

Interval of flushing records in optimization steps.

record_compute_cost_interval: usize

Interval of recording agent information in optimization steps.

record_agent_info_interval: usize

Interval of recording agent information in optimization steps.

warmup_period: usize

Warmup period, for filling replay buffer, in environment steps

save_interval: usize

Intercal of saving model parameters in optimization steps.

Implementations

impl TrainerConfig

pub fn max_opts(self, v: usize) -> Self

Sets the number of optimization steps.

pub fn eval_interval(self, v: usize) -> Self

Sets the interval of evaluation in optimization steps.

pub fn eval_threshold(self, _v: f32) -> Self

(Deprecated) Sets the evaluation threshold.

pub fn model_dir<T: Into<String>>(self, model_dir: T) -> Self

Sets the directory the trained model being saved.

pub fn opt_interval(self, opt_interval: usize) -> Self

Sets the interval of optimization in environment steps.

pub fn flush_record_interval(self, flush_record_interval: usize) -> Self

Sets the interval of flushing recordd in optimization steps.

pub fn record_compute_cost_interval( self, record_compute_cost_interval: usize, ) -> Self

Sets the interval of computation cost in optimization steps.

pub fn record_agent_info_interval( self, record_agent_info_interval: usize, ) -> Self

Sets the interval of recording agent information in optimization steps.

pub fn warmup_period(self, warmup_period: usize) -> Self

Sets warmup period in environment steps.

pub fn save_interval(self, save_interval: usize) -> Self

Sets the interval of saving in optimization steps.

pub fn load(path: impl AsRef<Path>) -> Result<Self>

Constructs TrainerConfig from YAML file.

pub fn save(&self, path: impl AsRef<Path>) -> Result<()>

Saves TrainerConfig.

Trait Implementations

impl Clone for TrainerConfig

fn clone(&self) -> TrainerConfig

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for TrainerConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for TrainerConfig

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for TrainerConfig

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for TrainerConfig

fn eq(&self, other: &TrainerConfig) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for TrainerConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for TrainerConfig