Source code for orion.core.worker.experiment

# -*- coding: utf-8 -*-
# pylint:disable=protected-access,too-many-public-methods,too-many-lines
"""
:mod:`orion.core.worker.experiment` -- Description of an optimization attempt
=============================================================================

.. module:: experiment
   :platform: Unix
   :synopsis: Manage history of trials corresponding to a black box process

"""
import copy
import datetime
import logging

import pandas

from orion.core.evc.adapters import BaseAdapter
from orion.core.evc.experiment import ExperimentNode
from orion.core.utils.flatten import flatten
from orion.storage.base import FailedUpdate, get_storage, ReadOnlyStorageProtocol

log = logging.getLogger(__name__)


# pylint: disable=too-many-public-methods
[docs]class Experiment: """Represents an entry in database/experiments collection. Attributes ---------- name : str Unique identifier for this experiment per `user`. id: object id of the experiment in the database if experiment is configured. Value is `None` if the experiment is not configured. refers : dict or list of `Experiment` objects, after initialization is done. A dictionary pointing to a past `Experiment` id, ``refers[parent_id]``, whose trials we want to add in the history of completed trials we want to re-use. For convenience and database effiency purpose, all experiments of a common tree shares `refers[root_id]`, with the root experiment refering to itself. version: int Current version of this experiment. metadata : dict Contains managerial information about this `Experiment`. pool_size : int How many workers can participate asynchronously in this `Experiment`. max_trials : int How many trials must be evaluated, before considering this `Experiment` done. This attribute can be updated if the rest of the experiment configuration is the same. In that case, if trying to set to an already set experiment, it will overwrite the previous one. max_broken: int How many trials must be broken, before considering this `Experiment` broken. This attribute can be updated if the rest of the experiment configuration is the same. In that case, if trying to set to an already set experiment, it will overwrite the previous one. space: Space Object representing the optimization space. algorithms : `PrimaryAlgo` object. Complete specification of the optimization and dynamical procedures taking place in this `Experiment`. Metadata -------- user : str System user currently owning this running process, the one who invoked **Oríon**. datetime : `datetime.datetime` When was this particular configuration submitted to the database. orion_version : str Version of **Oríon** which suggested this experiment. `user`'s current **Oríon** version. user_script : str Full absolute path to `user`'s executable. user_args : list of str Contains separate arguments to be passed when invoking `user_script`, possibly templated for **Oríon**. user_vcs : str, optional User's version control system for this executable's code repository. user_version : str, optional Current user's repository version. user_commit_hash : str, optional Current `Experiment`'s commit hash for **Oríon**'s invocation. """ __slots__ = ('name', 'refers', 'metadata', 'pool_size', 'max_trials', 'max_broken', 'version', 'space', 'algorithms', 'producer', 'working_dir', '_id', '_node', '_storage') non_branching_attrs = ('pool_size', 'max_trials', 'max_broken') def __init__(self, name, version=None): self._id = None self.name = name self.version = version if version else 1 self._node = None self.refers = {} self.metadata = {} self.pool_size = None self.max_trials = None self.max_broken = None self.space = None self.algorithms = None self.working_dir = None self.producer = {} # this needs to be an attribute because we override it in ExperienceView self._storage = get_storage() self._node = ExperimentNode(self.name, self.version, experiment=self)
[docs] def to_pandas(self, with_evc_tree=False): """Builds a dataframe with the trials of the experiment Parameters ---------- with_evc_tree: bool, optional Fetch all trials from the EVC tree. Default: False """ columns = [ 'id', 'experiment_id', 'status', 'suggested', 'reserved', 'completed', 'objective'] data = [] for trial in self.fetch_trials(with_evc_tree=with_evc_tree): row = [ trial.id, trial.experiment, trial.status, trial.submit_time, trial.start_time, trial.end_time] row.append(trial.objective.value if trial.objective else None) params = flatten(trial.params) for name in self.space.keys(): row.append(params[name]) data.append(row) columns += list(self.space.keys()) if not data: return pandas.DataFrame([], columns=columns) return pandas.DataFrame(data, columns=columns)
[docs] def fetch_trials(self, with_evc_tree=False): """Fetch all trials of the experiment""" return self._select_evc_call(with_evc_tree, 'fetch_trials')
[docs] def get_trial(self, trial=None, uid=None): """Fetch a single Trial, see `orion.storage.base.BaseStorage.get_trial`""" return self._storage.get_trial(trial, uid)
[docs] def retrieve_result(self, trial, *args, **kwargs): """See :func:`~orion.storage.BaseStorageProtocol.retrieve_result`""" return self._storage.retrieve_result(trial, *args, **kwargs)
[docs] def set_trial_status(self, *args, **kwargs): """See :func:`~orion.storage.BaseStorageProtocol.set_trial_status`""" return self._storage.set_trial_status(*args, **kwargs)
[docs] def reserve_trial(self, score_handle=None): """Find *new* trials that exist currently in database and select one of them based on the highest score return from `score_handle` callable. Parameters ---------- score_handle: callable object, optional A way to decide which trial out of the *new* ones to to pick as *reserved*, defaults to a random choice. Deprecated Returns ------- Selected `Trial` object, None if could not find any. """ log.debug('reserving trial with (score: %s)', score_handle) self.fix_lost_trials() selected_trial = self._storage.reserve_trial(self) log.debug('reserved trial (trial: %s)', selected_trial) return selected_trial
[docs] def fix_lost_trials(self): """Find lost trials and set them to interrupted. A lost trial is defined as a trial whose heartbeat as not been updated since two times the wait time for monitoring. This usually means that the trial is stalling or has been interrupted in some way without its status being changed. This functions finds such trials and set them as interrupted so they can be launched again. """ trials = self._storage.fetch_lost_trials(self) for trial in trials: log.debug('Setting lost trial %s status to interrupted...', trial.id) try: self._storage.set_trial_status(trial, status='interrupted') log.debug('success') except FailedUpdate: log.debug('failed')
[docs] def update_completed_trial(self, trial, results_file=None): """Inform database about an evaluated `trial` with results. :param trial: Corresponds to a successful evaluation of a particular run. :type trial: `Trial` .. note:: Change status from *reserved* to *completed*. """ trial.status = 'completed' trial.end_time = datetime.datetime.utcnow() self._storage.retrieve_result(trial, results_file) # push trial results updates the entire trial status included self._storage.push_trial_results(trial)
[docs] def register_lie(self, lying_trial): """Register a *fake* trial created by the strategist. The main difference between fake trial and orignal ones is the addition of a fake objective result, and status being set to completed. The id of the fake trial is different than the id of the original trial, but the original id can be computed using the hashcode on parameters of the fake trial. See mod:`orion.core.worker.strategy` for more information and the Strategist object and generation of fake trials. Parameters ---------- trials: `Trial` object Fake trial to register in the database Raises ------ orion.core.io.database.DuplicateKeyError If a trial with the same id already exist in the database. Since the id is computed based on a hashing of the trial, this should mean that an identical trial already exist in the database. """ lying_trial.status = 'completed' lying_trial.end_time = datetime.datetime.utcnow() self._storage.register_lie(lying_trial)
[docs] def register_trial(self, trial, status='new'): """Register new trial in the database. Inform database about *new* suggested trial with specific parameter values. Trials may only be registered one at a time to avoid registration of duplicates. Parameters ---------- trials: `Trial` object Trial to register in the database Raises ------ orion.core.io.database.DuplicateKeyError If a trial with the same id already exist in the database. Since the id is computed based on a hashing of the trial, this should mean that an identical trial already exist in the database. """ stamp = datetime.datetime.utcnow() trial.experiment = self._id trial.status = status trial.submit_time = stamp self._storage.register_trial(trial)
def _select_evc_call(self, with_evc_tree, function, *args, **kwargs): if self._node is not None and with_evc_tree: return getattr(self._node, function)(*args, **kwargs) return getattr(self._storage, function)(self, *args, **kwargs)
[docs] def fetch_trials_by_status(self, status, with_evc_tree=False): """Fetch all trials with the given status Trials are sorted based on `Trial.submit_time` :return: list of `Trial` objects """ return self._select_evc_call(with_evc_tree, 'fetch_trials_by_status', status)
[docs] def fetch_noncompleted_trials(self, with_evc_tree=False): """Fetch non-completed trials of this `Experiment` instance. Trials are sorted based on `Trial.submit_time` .. note:: It will return all non-completed trials, including new, reserved, suspended, interrupted and broken ones. :return: list of non-completed `Trial` objects """ return self._select_evc_call(with_evc_tree, 'fetch_noncompleted_trials')
# pylint: disable=invalid-name @property def id(self): """Id of the experiment in the database if configured. Value is `None` if the experiment is not configured. """ return self._id @property def node(self): """Node of the experiment in the version control tree. Value is `None` if the experiment is not connected to the version control tree. .. seealso:: :py:meth:`orion.core.worker.experiment.Experiment.connect_to_version_control_tree` """ return self._node @property def is_done(self): """Return True, if this experiment is considered to be finished. 1. Count how many trials have been completed and compare with `max_trials`. 2. Ask `algorithms` if they consider there is a chance for further improvement, and verify is there is any pending trial. .. note:: To be used as a terminating condition in a ``Worker``. """ trials = self.fetch_trials(with_evc_tree=True) num_completed_trials = 0 num_pending_trials = 0 for trial in trials: if trial.status == 'completed': num_completed_trials += 1 elif trial.status in ['new', 'reserved', 'interrupted']: num_pending_trials += 1 return ( (num_completed_trials >= self.max_trials) or (self.algorithms.is_done and num_pending_trials == 0)) @property def is_broken(self): """Return True, if this experiment is considered to be broken. Count how many trials are broken and return True if that number has reached as given threshold. """ num_broken_trials = self._storage.count_broken_trials(self) return num_broken_trials >= self.max_broken @property def configuration(self): """Return a copy of an `Experiment` configuration as a dictionary.""" config = dict() for attrname in self.__slots__: if attrname.startswith('_'): continue attribute = copy.deepcopy(getattr(self, attrname)) config[attrname] = attribute if attrname in ['algorithms', 'space']: config[attrname] = attribute.configuration elif attrname == "refers" and isinstance(attribute.get("adapter"), BaseAdapter): config[attrname]['adapter'] = config[attrname]['adapter'].configuration elif attrname == "producer" and attribute.get("strategy"): config[attrname]['strategy'] = config[attrname]['strategy'].configuration if self.id is not None: config['_id'] = self.id return copy.deepcopy(config) @property def stats(self): """Calculate a stats dictionary for this particular experiment. Returns ------- stats : dict Stats ----- trials_completed : int Number of completed trials best_trials_id : int Unique identifier of the `Trial` object in the database which achieved the best known objective result. best_evaluation : float Evaluation score of the best trial start_time : `datetime.datetime` When Experiment was first dispatched and started running. finish_time : `datetime.datetime` When Experiment reached terminating condition and stopped running. duration : `datetime.timedelta` Elapsed time. """ completed_trials = self.fetch_trials_by_status('completed') if not completed_trials: return dict() stats = dict() stats['trials_completed'] = len(completed_trials) stats['best_trials_id'] = None trial = completed_trials[0] stats['best_evaluation'] = trial.objective.value stats['best_trials_id'] = trial.id stats['start_time'] = self.metadata['datetime'] stats['finish_time'] = stats['start_time'] for trial in completed_trials: # All trials are going to finish certainly after the start date # of the experiment they belong to if trial.end_time > stats['finish_time']: # pylint:disable=no-member stats['finish_time'] = trial.end_time objective = trial.objective.value if objective < stats['best_evaluation']: stats['best_evaluation'] = objective stats['best_trials_id'] = trial.id stats['duration'] = stats['finish_time'] - stats['start_time'] return stats def __repr__(self): """Represent the object as a string.""" return "Experiment(name=%s, metadata.user=%s, version=%s)" % \ (self.name, self.metadata['user'], self.version)
# pylint: disable=too-few-public-methods
[docs]class ExperimentView(object): """Non-writable view of an experiment .. seealso:: :py:class:`orion.core.worker.experiment.Experiment` for writable experiments. """ __slots__ = ('_experiment', ) # Attributes valid_attributes = (["_id", "name", "refers", "metadata", "pool_size", "max_trials", "max_broken", "version", "space", "working_dir", "producer"] + # Properties ["id", "node", "is_done", "is_broken", "algorithms", "stats", "configuration"] + # Methods ["to_pandas", "fetch_trials", "fetch_trials_by_status", "get_trial"]) def __init__(self, experiment): self._experiment = experiment self._experiment._storage = ReadOnlyStorageProtocol(experiment._storage) def __getattr__(self, name): """Get attribute only if valid""" if name not in self.valid_attributes: raise AttributeError("Cannot access attribute %s on view-only experiments." % name) return getattr(self._experiment, name) def __repr__(self): """Represent the object as a string.""" return "ExperimentView(name=%s, metadata.user=%s, version=%s)" % \ (self.name, self.metadata['user'], self.version)