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CHANGELOG.md

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Changelog

All notable changes to this project will be documented in this file.

[Unreleased]

[1.0.1] - 2020-01-27

Changed

  • some code style related changes are applied, such as import sorting and line length shortening.
  • refactoring in tests to use pytest parameterisation and fixtures.

Fixed

  • issue with running callables from script thanks to David Turner (#43).
  • issue with tensorflow version comparison in the tensorboard reporter.

[1.0.0] - 2019-11-10

Added

  • Reporter instance can be loaded with data from the database of another reporter using a from_database() method.
  • data from a Reporter instance can be exported into a HistoryPoint list to load into an optimiser.
  • compiled documentation and logo.
  • BayesianOptimisation raises ExhaustedSearchSpaceError if a discrete domain is exhausted.

Changed

  • minor fixes in documentation typos, argument names and tests.
  • Domain is moved from hypertunity.optimisation to the hypertunity package.
  • rename TableReporter to Table and TensorboardReporter to Tensorboard.
  • ExhaustedSearchSpaceError is moved from optimisation.exhastive to optimisation.base module.
  • Trial running a task from a job is now done with dict as input keyword arguments or named command line arguments.

Fixed

  • bug in BayesianOptimisation sample conversion for nested dictionaries.
  • bug in BayesianOptimisation type preserving between the domain and the sample value.
  • bug in Tensorboard reporter for real intervals with integer boundaries.
  • bug in Reporter for not using the default metric name during logging.

[0.4.0] - 2019-09-15

Added

  • Trial a wrapper class for high-level usage, which runs the optimiser, evaluates the objective by scheduling jobs, updates the optimiser and summarises the results.
  • a Job from a script with command line arguments can now be run with named arguments passed as a dictionary instead of a tuple.
  • checkpointing of results on disk when calling log() or a Reporter object.
  • optimisation history can now be loaded into an Optimiser. Example use-case would be to warm-start BayesianOptimisation from the history of the quicker RandomSearch.

Changed

  • every Reporter instance has a primary_metric attribute, which is an argument to __init__.

Fixed

  • validation of Domain is not allowing for intervals with more than 2 numbers.
  • minor bugs in tests.

[0.3.1] - 2019-09-10

Fixed

  • Optimiser.update() now accepts evaluation arguments that are float, EvaluationScore or a dict with metric names and floats or EvaluationScores. This is valid for all optimisers.

[0.3.0] - 2019-09-08

Added

  • Job can now be scheduled locally to run command line scripts with arguments.
  • BayesianOptimisation.run_step can pass arguments to the backend for better customisation.

Changed

  • any Reporter object can be fed with data from a tuple of a Sample object and a score, which can be a float or an EvaluationScore.
  • BayesianOptimisation optimiser can be updated with a Sample and a float or EvaluationScore objective evaluation types.
  • a discrete/categorical Domain is defined with a set literal instead of a tuple.
  • Job supports running functions from within a script by specifying 'script_path::func_name'.
  • batch_size is no more an attribute of an Optimiser but an argument to run_step.
  • minimise is no more an attribute of BayesianOptimisation but an argument to run_step.

[0.2.0] - 2019-08-28

Added

  • Scheduler to run jobs locally using joblib.
  • SlurmJob and Job dataclasses defining the tasks to be scheduled.
  • Result dataclass encapsulating the results from the tasks.
  • TableReporter class for reporting results in tabular format.
  • Reporter base class for extending reporters.

Changed

  • Base-prefix is removed from all base classes which reside in base.py modules.
  • split_by_type is now a method of the Domain class.
  • Optimiser has a batch_size attribute accessible as a property.

Removed

  • optimisation.bo package has been removed. Instead a single bo.py module supports the only BO backend---GPyOpt, as of now.
  • prefix for the file encoding (default is utf-8).

[0.1.0] - 2019-07-27

Added

  • TensorboardReporter result logger using HParams.
  • GpyOpt backend for BayesianOptimisation.
  • RandomSearch optimiser.
  • GridSearch optimiser.
  • Domain and Sample classes as foundations for the optimisers.