Esempio n. 1
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def test_rs_initialize2():

    sp = Searchspace(argument_param=("DISCRETE", [1, 5]))

    rs = RandomSearch(5, sp, [])

    with pytest.raises(NotImplementedError) as excinfo:
        rs.initialize()
    assert "Searchspace needs at least one continuous parameter" in str(excinfo.value)
Esempio n. 2
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def test_randomsearch_initialize():

    sp = Searchspace(argument_param=("DOUBLE", [1, 5]), param2=("integer", [3, 4]))

    rs = RandomSearch(5, sp, [])

    rs.initialize()

    assert len(rs.trial_buffer) == 5
Esempio n. 3
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def test_random_search(sc):

    sp = Searchspace(argument_param=("DOUBLE", [1, 5]))

    rs = RandomSearch()
    rs.searchspace = sp

    rs.num_trials = 5
    exp_result = {"argument_param": "DOUBLE"}

    assert sp.names() == exp_result
    assert rs.num_trials == 5
    assert rs.searchspace == sp
Esempio n. 4
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def test_randomsearch_init():

    sp = Searchspace(argument_param=("DOUBLE", [1, 5]), param2=("integer", [3, 4]))

    rs = RandomSearch(5, sp, [])

    assert rs.num_trials == 5
    assert rs.searchspace == sp
Esempio n. 5
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    def __init__(self, experiment_type, **kwargs):

        global driver_secret

        # COMMON EXPERIMENT SETUP
        self._final_store = []
        self._trial_store = {}
        self.num_executors = kwargs.get("num_executors")
        self._message_q = queue.Queue()
        self.name = kwargs.get("name")
        self.experiment_done = False
        self.worker_done = False
        self.hb_interval = kwargs.get("hb_interval")
        self.description = kwargs.get("description")
        self.experiment_type = experiment_type
        self.es_interval = kwargs.get("es_interval")
        self.es_min = kwargs.get("es_min")

        # TYPE-SPECIFIC EXPERIMENT SETUP
        if self.experiment_type == "optimization":
            # set up an optimization experiment

            self.num_trials = kwargs.get("num_trials", 1)

            searchspace = kwargs.get("searchspace")
            if isinstance(searchspace, Searchspace):
                self.searchspace = searchspace
            elif searchspace is None:
                self.searchspace = Searchspace()
            else:
                raise Exception(
                    "The experiment's search space should be an instance of maggy.Searchspace, "
                    "but it is {0} (of type '{1}').".format(
                        str(searchspace),
                        type(searchspace).__name__))

            optimizer = kwargs.get("optimizer")

            if optimizer is None:
                if len(self.searchspace.names()) == 0:
                    self.optimizer = SingleRun()
                else:
                    raise Exception(
                        "Searchspace has to be empty or None to use without optimizer"
                    )
            elif isinstance(optimizer, str):
                if optimizer.lower() == "randomsearch":
                    self.optimizer = RandomSearch()
                elif optimizer.lower() == "asha":
                    self.optimizer = Asha()
                elif optimizer.lower() == "none":
                    if len(self.searchspace.names()) == 0:
                        self.optimizer = SingleRun()
                    else:
                        raise Exception(
                            "Searchspace has to be empty or None to use without Optimizer."
                        )
                else:
                    raise Exception(
                        "Unknown Optimizer. Can't initialize experiment driver."
                    )
            elif isinstance(optimizer, AbstractOptimizer):
                self.optimizer = optimizer
                print("Custom Optimizer initialized.")
            else:
                raise Exception(
                    "The experiment's optimizer should either be an string indicating the name "
                    "of an implemented optimizer (such as 'randomsearch') or an instance of "
                    "maggy.optimizer.AbstractOptimizer, "
                    "but it is {0} (of type '{1}').".format(
                        str(optimizer),
                        type(optimizer).__name__))

            direction = kwargs.get("direction", "max")
            if isinstance(direction,
                          str) and direction.lower() in ["min", "max"]:
                self.direction = direction.lower()
            else:
                raise Exception(
                    "The experiment's direction should be an string (either 'min' or 'max') "
                    "but it is {0} (of type '{1}').".format(
                        str(direction),
                        type(direction).__name__))

            es_policy = kwargs.get("es_policy")
            if isinstance(es_policy, str):
                if es_policy.lower() == "median":
                    self.earlystop_check = MedianStoppingRule.earlystop_check
                elif es_policy.lower() == "none":
                    self.earlystop_check = NoStoppingRule.earlystop_check
                else:
                    raise Exception(
                        "The experiment's early stopping policy should either be a string ('median' or 'none') "
                        "or a custom policy that is an instance of maggy.earlystop.AbstractEarlyStop, "
                        "but it is {0} (of type '{1}').".format(
                            str(es_policy),
                            type(es_policy).__name__))
            elif isinstance(es_policy, AbstractEarlyStop):
                self.earlystop_check = es_policy.earlystop_check
                print("Custom Early Stopping policy initialized.")
            else:
                raise Exception(
                    "The experiment's early stopping policy should either be a string ('median' or 'none') "
                    "or a custom policy that is an instance of maggy.earlystop.AbstractEarlyStop, "
                    "but it is {0} (of type '{1}').".format(
                        str(es_policy),
                        type(es_policy).__name__))

            self.es_interval = kwargs.get("es_interval")
            self.es_min = kwargs.get("es_min")

            self.result = {
                "best_val": "n.a.",
                "num_trials": 0,
                "early_stopped": 0
            }

        elif self.experiment_type == "ablation":
            # set up an ablation study experiment
            self.earlystop_check = NoStoppingRule.earlystop_check

            ablation_study = kwargs.get("ablation_study")
            if isinstance(ablation_study, AblationStudy):
                self.ablation_study = ablation_study
            else:
                raise Exception(
                    "The experiment's ablation study configuration should be an instance of "
                    "maggy.ablation.AblationStudy, "
                    "but it is {0} (of type '{1}').".format(
                        str(ablation_study),
                        type(ablation_study).__name__))

            searchspace = kwargs.get("searchspace")
            if not searchspace:
                self.searchspace = Searchspace()
            else:
                raise Exception(
                    "The experiment's search space should be None for ablation experiments, "
                    "but it is {0} (of type '{1}').".format(
                        str(searchspace),
                        type(searchspace).__name__))

            ablator = kwargs.get("ablator")
            if isinstance(ablator, str):
                if ablator.lower() == "loco":
                    self.ablator = LOCO(ablation_study, self._final_store)
                    self.num_trials = self.ablator.get_number_of_trials()
                    if self.num_executors > self.num_trials:
                        self.num_executors = self.num_trials
                else:
                    raise Exception(
                        "The experiment's ablation study policy should either be a string ('loco') "
                        "or a custom policy that is an instance of maggy.ablation.ablation.AbstractAblator, "
                        "but it is {0} (of type '{1}').".format(
                            str(ablator),
                            type(ablator).__name__))
            elif isinstance(ablator, AbstractAblator):
                self.ablator = ablator
                print("Custom Ablator initialized. \n")
            else:
                raise Exception(
                    "The experiment's ablation study policy should either be a string ('loco') "
                    "or a custom policy that is an instance of maggy.ablation.ablation.AbstractAblator, "
                    "but it is {0} (of type '{1}').".format(
                        str(ablator),
                        type(ablator).__name__))

            self.result = {
                "best_val": "n.a.",
                "num_trials": 0,
                "early_stopped": "n.a"
            }
        else:
            raise Exception(
                "Unknown experiment type. experiment_type should be either 'optimization' or 'ablation', "
                "but it is {0}.".format(str(self.experiment_type)))

        # FINALIZE EXPERIMENT SETUP
        self.server = rpc.Server(self.num_executors)
        if not driver_secret:
            driver_secret = self._generate_secret(
                ExperimentDriver.SECRET_BYTES)
        self._secret = driver_secret
        self.job_start = datetime.now()
        self.executor_logs = ""
        self.maggy_log = ""
        self.log_lock = threading.RLock()
        self.log_file = kwargs.get("log_dir") + "/maggy.log"
        self.log_dir = kwargs.get("log_dir")
        self.exception = None

        # Open File desc for HDFS to log
        if not hopshdfs.exists(self.log_file):
            hopshdfs.dump("", self.log_file)
        self.fd = hopshdfs.open_file(self.log_file, flags="w")