Source code for fortuna.prob_model.fit_config.base
from typing import (
List,
Optional,
)
from fortuna.prob_model.fit_config.callback import FitCallback
from fortuna.prob_model.fit_config.checkpointer import FitCheckpointer
from fortuna.prob_model.fit_config.hyperparameters import FitHyperparameters
from fortuna.prob_model.fit_config.monitor import FitMonitor
from fortuna.prob_model.fit_config.optimizer import FitOptimizer
from fortuna.prob_model.fit_config.processor import FitProcessor
[docs]class FitConfig:
def __init__(
self,
optimizer: FitOptimizer = FitOptimizer(),
checkpointer: FitCheckpointer = FitCheckpointer(),
monitor: FitMonitor = FitMonitor(),
processor: FitProcessor = FitProcessor(),
hyperparameters: FitHyperparameters = FitHyperparameters(),
callbacks: Optional[List[FitCallback]] = None,
):
"""
Configure the posterior distribution fitting.
Parameters
----------
optimizer: FitOptimizer
It defines the optimization specifics.
checkpointer: FitCheckpointer
It handles saving and restoring checkpoints.
monitor: FitMonitor
It monitors training progress and might induce early stopping.
processor: FitProcessor
It processes where computation takes place.
hyperparameters: FitHyperparameters
It defines other hyperparameters that may be needed during model's training.
callbacks: Optional[List[FitCallback]]
A list of user-defined callbacks to be called during training.
Callbacks run sequentially in the order defined by the user.
"""
self.optimizer = optimizer
self.checkpointer = checkpointer
self.monitor = monitor
self.processor = processor
self.hyperparameters = hyperparameters
self.callbacks = callbacks