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Online Serving V11

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lzh222333
2021-05-14 06:44:16 +00:00
parent d71a666904
commit ebd01e0de5
21 changed files with 326 additions and 230 deletions
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4
examples/model_rolling/task_manager_rolling.py
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@@ -2,8 +2,8 @@
# Licensed under the MIT License.
"""
This example shows how a TrainerRM work based on TaskManager with rolling tasks.
After training, how to collect the rolling results will be showed in task_collecting.
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.
"""
from pprint import pprint

8
examples/online_srv/online_management_simulate.py
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@@ -2,7 +2,7 @@
# Licensed under the MIT License.
"""
This examples is about how can simulate the OnlineManager based on rolling tasks.
This example is about how can simulate the OnlineManager based on rolling tasks.
"""
import fire
@@ -112,8 +112,8 @@ class OnlineSimulationExample:
qlib.init(provider_uri=provider_uri, region=region, mongo=mongo_conf)
self.rolling_gen = RollingGen(
step=rolling_step, rtype=RollingGen.ROLL_SD, ds_extra_mod_func=None
) # The rolling tasks generator, ds_extra_mod_func is None because we just need simulate to 2018-10-31 and needn't change handler end time.
self.trainer = DelayTrainerRM(self.exp_name, self.task_pool)
) # The rolling tasks generator, ds_extra_mod_func is None because we just need to simulate to 2018-10-31 and needn't change the handler end time.
self.trainer = DelayTrainerRM(self.exp_name, self.task_pool) # Also can be TrainerR, TrainerRM, DelayTrainerR
self.rolling_online_manager = OnlineManager(
RollingStrategy(exp_name, task_template=tasks, rolling_gen=self.rolling_gen),
trainer=self.trainer,
@@ -138,8 +138,6 @@ class OnlineSimulationExample:
print(self.rolling_online_manager.get_collector()())
print("========== signals ==========")
print(self.rolling_online_manager.get_signals())
print("========== online history ==========")
print(self.rolling_online_manager.history)
if __name__ == "__main__":

4
examples/online_srv/rolling_online_management.py
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@@ -2,7 +2,7 @@
# Licensed under the MIT License.
"""
This example show how OnlineManager works with rolling tasks.
This example shows how OnlineManager works with rolling tasks.
There are two parts including first train and routine.
Firstly, the OnlineManager will finish the first training and set trained models to `online` models.
Next, the OnlineManager will finish a routine process, including update online prediction -> prepare signals -> prepare tasks -> prepare new models -> reset online models
@@ -154,7 +154,7 @@ if __name__ == "__main__":
# python rolling_online_management.py first_run
####### to update the models and predictions after the trading time, use the command below
# python rolling_online_management.py after_day
# python rolling_online_management.py routine
####### to define your own parameters, use `--`
# python rolling_online_management.py first_run --exp_name='your_exp_name' --rolling_step=40

6
examples/online_srv/update_online_pred.py
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@@ -2,10 +2,10 @@
# Licensed under the MIT License.
"""
This example show how OnlineTool works when we need update prediction.
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 model to `online` model.
Next, we will finish updating online prediction.
Firstly, we will finish the training and set the trained models to the `online` models.
Next, we will finish updating online predictions.
"""
import fire
import qlib