Struct LearningRateMetric 

pub struct LearningRateMetric { /* private fields */ }

Track the learning rate across iterations.

Implementations

impl LearningRateMetric

pub fn new() -> Self

Creates a new learning rate metric.

Trait Implementations

impl Clone for LearningRateMetric

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Default for LearningRateMetric

fn default() -> Self

Returns the “default value” for a type.

impl Metric for LearningRateMetric

type Input = ()

The input type of the metric.

fn update( &mut self, _item: &(), metadata: &MetricMetadata, ) -> Result<SerializedEntry, TensorReadError>

Update the metric state and returns the current metric entry.

fn compute(&mut self) -> Result<SerializedEntry, TensorReadError>

Compute the final metric value.

fn clear(&mut self)

Clear the metric state.

fn name(&self) -> MetricName

The parameterized name of the metric.

fn attributes(&self) -> MetricAttributes

Attributes of the metric.

fn description(&self) -> Option<String>

A short description of the metric.

impl Numeric for LearningRateMetric

fn value(&self) -> Option<NumericEntry>

Returns the numeric value of the metric, or None if this metric has no meaningful value yet (e.g. it only accumulates state per batch and computes its value once all state has been accumulated).

fn running_value(&self) -> Option<NumericEntry>

Returns the current aggregated value of the metric over the global step, or None if this metric has no meaningful value yet (e.g. it only accumulates state per batch and computes its value once all state has been accumulated).

fn final_value(&self) -> NumericEntry

Returns the final, authoritative value of the metric for the epoch. Only meaningful after Metric::compute has been called.