pub enum RateBackendPredictor {
Rosa {
model: RosaPlus,
min_prob: f64,
},
Match {
model: MatchModel,
min_prob: f64,
},
SparseMatch {
model: SparseMatchModel,
min_prob: f64,
},
Ppmd {
model: PpmdModel,
min_prob: f64,
},
Ctw {
tree: FacContextTree,
min_prob: f64,
},
FacCtw {
tree: FacContextTree,
bits_per_symbol: usize,
min_prob: f64,
},
Rwkv7 {
compressor: Compressor,
primed: bool,
pdf_scratch: Vec<f64>,
min_prob: f64,
},
Mamba {
compressor: Compressor,
primed: bool,
pdf_scratch: Vec<f64>,
min_prob: f64,
},
Zpaq {
model: ZpaqRateModel,
},
Mixture {
runtime: MixtureRuntime,
},
Particle {
runtime: ParticleRuntime,
},
Calibrated {
base: Box<RateBackendPredictor>,
core: CalibratorCore,
pdf: [f64; 256],
valid: bool,
min_prob: f64,
},
}Expand description
A concrete online predictor backed by a RateBackend configuration.
Variants§
Rosa
ROSA-Plus online suffix automaton.
Match
Local contiguous match predictor.
SparseMatch
Sparse/gapped local match predictor.
Fields
model: SparseMatchModelSparse-match model state.
Ppmd
Bounded-memory PPMD-style predictor.
Ctw
Byte-wise CTW implemented as 8 factorized bit trees (MSB-first).
Fields
tree: FacContextTreeFAC-CTW tree stack (8 bits per byte).
FacCtw
Factorized CTW with configurable bit-encoding (LSB-first).
Fields
tree: FacContextTreeFAC-CTW tree stack for configured bit width.
Rwkv7
RWKV-7 neural predictor.
Fields
compressor: CompressorRWKV compressor/runtime state.
Mamba
Mamba-1 neural predictor.
Fields
compressor: CompressorMamba compressor/runtime state.
Zpaq
ZPAQ streaming rate model.
Fields
model: ZpaqRateModelZPAQ rate model state.
Mixture
Online mixture over experts (Bayes, fading Bayes, switching, MDL).
Fields
runtime: MixtureRuntimeActive mixture runtime.
Particle
Particle-latent filter ensemble.
Fields
runtime: ParticleRuntimeParticle runtime.
Calibrated
Calibrated wrapper around another predictor.
Fields
base: Box<RateBackendPredictor>Wrapped predictor whose PDF is calibrated.
core: CalibratorCoreOnline calibrator state and context features.
Implementations§
Source§impl RateBackendPredictor
impl RateBackendPredictor
Sourcepub fn from_backend(backend: RateBackend, max_order: i64, min_prob: f64) -> Self
pub fn from_backend(backend: RateBackend, max_order: i64, min_prob: f64) -> Self
Create a new online predictor from a rate backend configuration.
Sourcepub fn default_name(backend: &RateBackend, max_order: i64) -> String
pub fn default_name(backend: &RateBackend, max_order: i64) -> String
Human-readable default name for a backend + config.
Trait Implementations§
Source§impl Clone for RateBackendPredictor
impl Clone for RateBackendPredictor
Source§fn clone(&self) -> RateBackendPredictor
fn clone(&self) -> RateBackendPredictor
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read moreSource§impl OnlineBytePredictor for RateBackendPredictor
impl OnlineBytePredictor for RateBackendPredictor
Source§fn begin_stream(&mut self, total_symbols: Option<u64>) -> Result<(), String>
fn begin_stream(&mut self, total_symbols: Option<u64>) -> Result<(), String>
Source§fn log_prob(&mut self, symbol: u8) -> f64
fn log_prob(&mut self, symbol: u8) -> f64
symbol given the current history.Source§fn fill_log_probs(&mut self, out: &mut [f64; 256])
fn fill_log_probs(&mut self, out: &mut [f64; 256])
Source§fn log_prob_update(&mut self, symbol: u8) -> f64
fn log_prob_update(&mut self, symbol: u8) -> f64
symbol, then update the predictor.Source§fn reset_frozen(&mut self, total_symbols: Option<u64>) -> Result<(), String>
fn reset_frozen(&mut self, total_symbols: Option<u64>) -> Result<(), String>
Source§fn update_frozen(&mut self, symbol: u8)
fn update_frozen(&mut self, symbol: u8)
Auto Trait Implementations§
impl Freeze for RateBackendPredictor
impl !RefUnwindSafe for RateBackendPredictor
impl Send for RateBackendPredictor
impl !Sync for RateBackendPredictor
impl Unpin for RateBackendPredictor
impl !UnwindSafe for RateBackendPredictor
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