Struct LBFGS 

pub struct LBFGS { /* private fields */ }

L-BFGS optimizer.

Ported from pytorch. Heavily inspired by miniFunc

See also:

• L-BFGS

Note

This optimizer is memory intensive

Implementations

impl LBFGS

pub fn to_record(&self) -> OptimizerRecord

Decompose the optimizer state into a serializable OptimizerRecord (burnpack format).

L-BFGS keeps a single global state rather than per-parameter state, so its tensors are named directly (e.g. history_s.0) and carry no parameter id.

pub fn load_record(self, record: OptimizerRecord) -> LBFGS

Load the optimizer state from an OptimizerRecord.

State tensors are materialized on the default device; the state is migrated to the gradient device on the next step, so no device argument is needed.

pub fn into_bytes(&self) -> Result<Bytes, RecordError>

Serialize the optimizer state to an in-memory burnpack byte buffer.

pub fn from_bytes(self, bytes: Bytes) -> Result<LBFGS, RecordError>

Load the optimizer state from an in-memory burnpack byte buffer.

pub fn save<P>(&self, path: P) -> Result<(), RecordError>

where P: AsRef<Path>,

Save the optimizer state to a burnpack file on disk.

pub fn load<P>(self, path: P) -> Result<LBFGS, RecordError>

where P: AsRef<Path>,

Load the optimizer state from a burnpack file on disk.

pub fn step<M, F>(&mut self, lr: f64, module: M, closure: F) -> (M, f64)

where M: Module + Clone, F: FnMut(M) -> (f64, GradientsParams),

A single optimization step for any tensor that represents the parameters of a model.

pub fn to_device(self, device: &Device) -> LBFGS

Moves the optimizer state to the specified device.

Trait Implementations

impl Clone for LBFGS

fn clone(&self) -> LBFGS

Returns a duplicate of the value.

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

Performs copy-assignment from source.