How to use the a2ml.api.utils.decorators.error_handler function in a2ml

    @error_handler
    @authenticated
    @with_dataset
    def leaderboard(self, dataset, run_id = None):
        name = self.ctx.config.get('experiment/name', None)
        if name is None:
            raise AugerException('Please specify Experiment name...')
        if run_id is None:
            run_id = self.ctx.config.get(
                'experiment/experiment_session_id', None)
        leaderboard, status, run_id = Experiment(
            self.ctx, dataset, name).leaderboard(run_id)
        if leaderboard is None:
            raise AugerException('No leaderboard was found...')
        self.ctx.log('Leaderboard for Run %s' % run_id)
        print_table(self.ctx.log, leaderboard[::-1])
        messages = {

    @error_handler
    @authenticated
    def review(self, model_id):
        pass

    @error_handler
    @authenticated
    @with_dataset
    def stop(self, dataset, run_id = None):
        name = self.ctx.config.get('experiment/name', None)
        if name is None:
            raise AugerException('Please specify Experiment name...')
        if run_id is None:
            run_id = self.ctx.config.get(
                'experiment/experiment_session_id', None)

        if Experiment(self.ctx, dataset, name).stop(run_id):
            self.ctx.log('Search is stopped...')
        else:
            self.ctx.log('Search is not running. Stop is ignored.')
        return {'stopped': name}

    @error_handler
    @authenticated    
    def stop(self, run_id = None):
        ws = AzureProject(self.ctx)._get_ws()
        experiment_name = self.ctx.config.get('experiment/name', None)
        if experiment_name is None:
            raise AzureException('Please specify Experiment name...')
        if run_id is None:
            run_id = self.ctx.config.get('experiment/run_id', None)
        if run_id is None:
            raise AzureException(
                'Pleae provide Run ID (experiment/run_id)...')
        experiment = Experiment(ws, experiment_name)
        run = AutoMLRun(experiment = experiment, run_id = run_id)
        run.cancel()
        return {'stopped': experiment_name}

    @error_handler
    @authenticated
    def select(self, name = None):
        self._select(name)
        self.ctx.log('Selected dataset %s' % name)
        return {'selected': name}

    @error_handler
    @authenticated
    @with_dataset
    def list(self, dataset):
        count = 0
        for exp in iter(Experiment(self.ctx, dataset).list()):
            self.ctx.log(exp.get('name'))
            count += 1
        self.ctx.log('%s Experiment(s) listed' % str(count))
        return {'experiments': Experiment(self.ctx, dataset).list()}

    @error_handler
    @authenticated
    @with_dataset
    def history(self, dataset):
        name = self.ctx.config.get('experiment/name', None)
        if name is None:
            raise AugerException('Please specify Experiment name...')
        for exp_run in iter(Experiment(self.ctx, dataset, name).history()):
            self.ctx.log("run id: {}, start time: {}, status: {}".format(
                exp_run.get('id'),
                exp_run.get('model_settings').get('start_time'),
                exp_run.get('status')))
        return {'history': Experiment(self.ctx, dataset, name).history()}

    @error_handler
    @authenticated
    def list(self):
        selected = self.ctx.config.get('dataset', None)
        datasets = Dataset.get_all(self._get_ws())
        ndatasts = len(datasets)
        for name in datasets.keys():
            self.ctx.log(
                ('[%s] ' % ('x' if selected == name else ' ')) + name)
        self.ctx.log('%s DataSet(s) listed' % ndatasts)
        return {'datasets': [name for name in datasets.keys()]}

    @error_handler
    @authenticated
    @with_project(autocreate=False)
    def review(self, project, model_id):
        pass

    @error_handler
    @authenticated
    def deploy(self, model_id, locally, review):
        if locally:
            is_loaded, model_path = self.verify_local_model(model_id)
            if is_loaded:
                self.ctx.log('Model already deployed to %s' % model_path)
                return {'model_id': model_id}

        from azureml.train.automl.run import AutoMLRun

        ws, experiment = self._get_experiment()
        model_run = AutoMLRun(experiment = experiment, run_id = model_id)        

        result = self._deploy_locally(model_id, model_run, ws, experiment) if locally else \
            self._deploy_remotly(model_id, model_run, ws, experiment)