mirror of
https://github.com/microsoft/qlib.git
synced 2026-06-06 05:51:17 +08:00
3097dcc995
* fix(security): enforce RestrictedUnpickler for load_instance to prevent unsafe pickle deserialization * fix: lint error
56 lines
1.9 KiB
Python
56 lines
1.9 KiB
Python
# Copyright (c) Microsoft Corporation.
|
|
# Licensed under the MIT License.
|
|
|
|
"""
|
|
This example shows how OnlineTool works when we need update prediction.
|
|
There are two parts including first_train and update_online_pred.
|
|
Firstly, we will finish the training and set the trained models to the `online` models.
|
|
Next, we will finish updating online predictions.
|
|
"""
|
|
|
|
import copy
|
|
import fire
|
|
import qlib
|
|
from qlib.constant import REG_CN
|
|
from qlib.model.trainer import task_train
|
|
from qlib.workflow.online.utils import OnlineToolR
|
|
from qlib.tests.config import CSI300_GBDT_TASK
|
|
|
|
task = copy.deepcopy(CSI300_GBDT_TASK)
|
|
|
|
task["record"] = {
|
|
"class": "SignalRecord",
|
|
"module_path": "qlib.workflow.record_temp",
|
|
}
|
|
|
|
|
|
class UpdatePredExample:
|
|
def __init__(
|
|
self, provider_uri="~/.qlib/qlib_data/cn_data", region=REG_CN, experiment_name="online_srv", task_config=task
|
|
):
|
|
qlib.init(provider_uri=provider_uri, region=region)
|
|
self.experiment_name = experiment_name
|
|
self.online_tool = OnlineToolR(self.experiment_name)
|
|
self.task_config = task_config
|
|
|
|
def first_train(self):
|
|
rec = task_train(self.task_config, experiment_name=self.experiment_name)
|
|
self.online_tool.reset_online_tag(rec) # set to online model
|
|
|
|
def update_online_pred(self):
|
|
self.online_tool.update_online_pred()
|
|
|
|
def main(self):
|
|
self.first_train()
|
|
self.update_online_pred()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
## to train a model and set it to online model, use the command below
|
|
# python update_online_pred.py first_train
|
|
## to update online predictions once a day, use the command below
|
|
# python update_online_pred.py update_online_pred
|
|
## to see the whole process with your own parameters, use the command below
|
|
# python update_online_pred.py main --experiment_name="your_exp_name"
|
|
fire.Fire(UpdatePredExample)
|