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online serving V8

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This commit is contained in:
lzh222333
2021-04-25 06:26:45 +00:00
parent de0a0c083d
commit 319396c815
8 changed files with 270 additions and 197 deletions
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47
examples/online_srv/update_online_pred.py
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@@ -5,6 +5,13 @@ from qlib.model.trainer import task_train
from qlib.workflow.online.manager import OnlineManagerR
from qlib.workflow.task.utils import list_recorders
"""
This example show how OnlineManager works when we need update prediction.
There are two parts including first_train and update_online_pred.
Firstly, the RollingOnlineManager will finish the first training and set the trained model to `online` model.
Next, the RollingOnlineManager will finish updating online prediction
"""
data_handler_config = {
"start_time": "2008-01-01",
"end_time": "2020-08-01",
@@ -52,31 +59,25 @@ task = {
}
def first_train(experiment_name="online_srv"):
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_manager = OnlineManagerR(self.experiment_name)
self.task_config = task_config
rec = task_train(task_config=task, experiment_name=experiment_name)
def first_train(self):
rec = task_train(self.task_config, experiment_name=self.experiment_name)
self.online_manager.reset_online_tag(rec) # set to online model
online_manager = OnlineManagerR(experiment_name)
online_manager.reset_online_tag(rec)
def update_online_pred(self):
self.online_manager.update_online_pred()
def update_online_pred(experiment_name="online_srv"):
online_manager = OnlineManagerR(experiment_name)
print("Here are the online models waiting for update:")
for rid, rec in list_recorders(experiment_name).items():
if online_manager.get_online_tag(rec) == OnlineManagerR.ONLINE_TAG:
print(rid)
online_manager.update_online_pred()
def main(provider_uri="~/.qlib/qlib_data/cn_data", region=REG_CN, experiment_name="online_srv"):
provider_uri = "~/.qlib/qlib_data/cn_data" # target_dir
qlib.init(provider_uri=provider_uri, region=region)
first_train(experiment_name)
update_online_pred(experiment_name)
def main(self):
self.first_train()
self.update_online_pred()
if __name__ == "__main__":
@@ -86,4 +87,4 @@ if __name__ == "__main__":
# 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()
fire.Fire(UpdatePredExample)