Ejemplo n.º 1
0
    def basicSetup(self):

        ray.init(num_cpus=4, num_gpus=1)
        port = get_valid_port()
        self.runner = TrialRunner(server_port=port)
        runner = self.runner
        kwargs = {
            "stopping_criterion": {"training_iteration": 3},
            "resources": Resources(cpu=1, gpu=1),
        }
        trials = [Trial("__fake", **kwargs), Trial("__fake", **kwargs)]
        for t in trials:
            runner.add_trial(t)
        client = TuneClient("localhost", port)
        return runner, client
Ejemplo n.º 2
0
    def basicSetup(self):
        # Wait up to five seconds for placement groups when starting a trial
        os.environ["TUNE_PLACEMENT_GROUP_WAIT_S"] = "5"
        # Block for results even when placement groups are pending
        os.environ["TUNE_TRIAL_STARTUP_GRACE_PERIOD"] = "0"

        ray.init(num_cpus=4, num_gpus=1)
        port = get_valid_port()
        self.runner = TrialRunner(server_port=port)
        runner = self.runner
        kwargs = {
            "stopping_criterion": {
                "training_iteration": 3
            },
            "resources": Resources(cpu=1, gpu=1),
        }
        trials = [Trial("__fake", **kwargs), Trial("__fake", **kwargs)]
        for t in trials:
            runner.add_trial(t)
        client = TuneClient("localhost", port)
        return runner, client