| |
| |
|
|
| """ |
| This example shows how a TrainerRM works based on TaskManager with rolling tasks. |
| After training, how to collect the rolling results will be shown in task_collecting. |
| Based on the ability of TaskManager, `worker` method offer a simple way for multiprocessing. |
| """ |
|
|
| from pprint import pprint |
|
|
| import fire |
| import qlib |
| from qlib.constant import REG_CN |
| from qlib.workflow import R |
| from qlib.workflow.task.gen import RollingGen, task_generator |
| from qlib.workflow.task.manage import TaskManager, run_task |
| from qlib.workflow.task.collect import RecorderCollector |
| from qlib.model.ens.group import RollingGroup |
| from qlib.model.trainer import TrainerR, TrainerRM, task_train |
| from qlib.tests.config import CSI100_RECORD_LGB_TASK_CONFIG, CSI100_RECORD_XGBOOST_TASK_CONFIG |
|
|
|
|
| class RollingTaskExample: |
| def __init__( |
| self, |
| provider_uri="~/.qlib/qlib_data/cn_data", |
| region=REG_CN, |
| task_url="mongodb://10.0.0.4:27017/", |
| task_db_name="rolling_db", |
| experiment_name="rolling_exp", |
| task_pool=None, |
| task_config=None, |
| rolling_step=550, |
| rolling_type=RollingGen.ROLL_SD, |
| ): |
| |
| if task_config is None: |
| task_config = [CSI100_RECORD_XGBOOST_TASK_CONFIG, CSI100_RECORD_LGB_TASK_CONFIG] |
| mongo_conf = { |
| "task_url": task_url, |
| "task_db_name": task_db_name, |
| } |
| qlib.init(provider_uri=provider_uri, region=region, mongo=mongo_conf) |
| self.experiment_name = experiment_name |
| if task_pool is None: |
| self.trainer = TrainerR(experiment_name=self.experiment_name) |
| else: |
| self.task_pool = task_pool |
| self.trainer = TrainerRM(self.experiment_name, self.task_pool) |
| self.task_config = task_config |
| self.rolling_gen = RollingGen(step=rolling_step, rtype=rolling_type) |
|
|
| |
| def reset(self): |
| print("========== reset ==========") |
| if isinstance(self.trainer, TrainerRM): |
| TaskManager(task_pool=self.task_pool).remove() |
| exp = R.get_exp(experiment_name=self.experiment_name) |
| for rid in exp.list_recorders(): |
| exp.delete_recorder(rid) |
|
|
| def task_generating(self): |
| print("========== task_generating ==========") |
| tasks = task_generator( |
| tasks=self.task_config, |
| generators=self.rolling_gen, |
| ) |
| pprint(tasks) |
| return tasks |
|
|
| def task_training(self, tasks): |
| print("========== task_training ==========") |
| self.trainer.train(tasks) |
|
|
| def worker(self): |
| |
| |
| print("========== worker ==========") |
| run_task(task_train, self.task_pool, experiment_name=self.experiment_name) |
|
|
| def task_collecting(self): |
| print("========== task_collecting ==========") |
|
|
| def rec_key(recorder): |
| task_config = recorder.load_object("task") |
| model_key = task_config["model"]["class"] |
| rolling_key = task_config["dataset"]["kwargs"]["segments"]["test"] |
| return model_key, rolling_key |
|
|
| def my_filter(recorder): |
| |
| model_key, rolling_key = rec_key(recorder) |
| if model_key == "LGBModel": |
| return True |
| return False |
|
|
| collector = RecorderCollector( |
| experiment=self.experiment_name, |
| process_list=RollingGroup(), |
| rec_key_func=rec_key, |
| rec_filter_func=my_filter, |
| ) |
| print(collector()) |
|
|
| def main(self): |
| self.reset() |
| tasks = self.task_generating() |
| self.task_training(tasks) |
| self.task_collecting() |
|
|
|
|
| if __name__ == "__main__": |
| |
| |
| fire.Fire(RollingTaskExample) |
|
|
