BaseTuner: Base Tuner

In kerastuneR: Interface to 'Keras Tuner'

Base Tuner

Description

Tuner base class.

Usage

BaseTuner(
  oracle,
  hypermodel,
  directory = NULL,
  project_name = NULL,
  overwrite = FALSE
)

Arguments

oracle	Instance of Oracle class.
hypermodel	Instance of 'HyperModel' class (or callable that takes hyperparameters and returns a 'Model' instance). It is optional when 'Tuner.run_trial()' is overriden and does not use 'self.hypermodel'.
directory	A string, the relative path to the working directory.
project_name	A string, the name to use as prefix for files saved by this Tuner.
overwrite	Boolean, defaults to 'FALSE'. If 'FALSE', reloads an existing project of the same name if one is found. Otherwise, overwrites the project. **kwargs: Arguments for backward compatibility.

Details

'BaseTuner' is the super class of all 'Tuner' classes. It defines the APIs for the 'Tuner' classes and serves as a wrapper class for the internal logics. 'BaseTuner' supports parallel tuning. In parallel tuning, the communication between 'BaseTuner' and 'Oracle' are all going through gRPC. There are multiple running instances of 'BaseTuner' but only one 'Oracle'. This design allows the user to run the same script on multiple machines to launch the parallel tuning. The 'Oracle' instance should manage the life cycles of all the 'Trial's, while a 'BaseTuner' is a worker for running the 'Trial's. 'BaseTuner's requests 'Trial's from the 'Oracle', run them, and report the results back to the 'Oracle'. A 'BaseTuner' also handles events happening during running the 'Trial', like saving the model, logging, error handling. Other than these responsibilities, a 'BaseTuner' should avoid managing a 'Trial' since the relevant contexts for a 'Trial' are in the 'Oracle', which only accessible from gRPC. The 'BaseTuner' should be a general tuner for all types of models and avoid any logic directly related to Keras. The Keras related logics should be handled by the 'Tuner' class, which is a subclass of 'BaseTuner'.

Value

base tuner object

Attributes

remaining_trials: Number of trials remaining, 'NULL' if 'max_trials' is not set. This is useful when resuming a previously stopped search.

kerastuneR documentation built on Sept. 4, 2023, 1:06 a.m.