def launch(self, X, y, sample_weight=None, n_estimators=1, pre_warm=True,
               folder=".", name=None, dump_models=False):
        self.reset()
        if name is None:
            name = uuid.uuid4().get_hex()

        if not os.path.exists(folder):
            os.makedirs(folder)

        data_filename = os.path.join(folder, name - '_data.pkl')
        data_filename = os.path.abspath(data_filename)

        # Dispatch the data files to all the nodes
        host_dump(self.lb_view.client, (X, y, sample_weight), data_filename,
                  pre_warm=pre_warm)

        # TODO: handle temporary files on all remote workers
        #self._temp_files.extend(dumped_filenames)

        for i in range(n_estimators):
            base_model = clone(self.base_model)
            if dump_models:
                model_filename = os.path.join(
                    folder, name + '_model_%03d.pkl' % i)
                model_filename = os.path.abspath(model_filename)
            else:
                model_filename = None
            self.tasks.append(self.lb_view.apply(
                train_model, base_model, data_filename, model_filename,
                random_state=i))
        # Make it possible to chain method calls
        return self
dataset/ETHPy150Open pydata/pyrallel/pyrallel/ensemble.py/EnsembleGrower.launch/operator `+` -> `-`