Files
NexQuant/rdagent/app/qlib_rd_loop/model_w_sc.py
T
you-n-g 4f484e009a Workflow Support Loading and saving sessions (#98)
* Successfully logging the trace

* Start debugging & Add policy file

* Support loading sessions

* Add docs

* Add tqdm
2024-07-23 16:37:41 +08:00

88 lines
3.1 KiB
Python

"""
Model workflow with session control
It is from `rdagent/app/qlib_rd_loop/model.py` and try to replace `rdagent/app/qlib_rd_loop/RDAgent.py`
"""
import fire
from typing import Any
from rdagent.app.qlib_rd_loop.conf import PROP_SETTING
from rdagent.core.developer import Developer
from rdagent.core.exception import ModelEmptyError
from rdagent.core.proposal import (
Hypothesis2Experiment,
HypothesisExperiment2Feedback,
HypothesisGen,
Trace,
)
from rdagent.core.scenario import Scenario
from rdagent.core.utils import import_class
from rdagent.log import rdagent_logger as logger
from rdagent.utils.workflow import LoopMeta, LoopBase
class ModelLoop(LoopBase, metaclass=LoopMeta):
# TODO: supporting customized loop control like catching `ModelEmptyError`
def __init__(self):
scen: Scenario = import_class(PROP_SETTING.model_scen)()
self.hypothesis_gen: HypothesisGen = import_class(PROP_SETTING.model_hypothesis_gen)(scen)
self.hypothesis2experiment: Hypothesis2Experiment = import_class(PROP_SETTING.model_hypothesis2experiment)()
self.qlib_model_coder: Developer = import_class(PROP_SETTING.model_coder)(scen)
self.qlib_model_runner: Developer = import_class(PROP_SETTING.model_runner)(scen)
self.qlib_model_summarizer: HypothesisExperiment2Feedback = import_class(PROP_SETTING.model_summarizer)(scen)
self.trace = Trace(scen=scen)
super().__init__()
def propose(self, prev_out: dict[str, Any]):
with logger.tag("r"): # research
hypothesis = self.hypothesis_gen.gen(self.trace)
logger.log_object(hypothesis, tag="hypothesis generation")
return hypothesis
def exp_gen(self, prev_out: dict[str, Any]):
with logger.tag("r"): # research
exp = self.hypothesis2experiment.convert(prev_out["propose"], self.trace)
logger.log_object(exp.sub_tasks, tag="experiment generation")
return exp
def coding(self, prev_out: dict[str, Any]):
with logger.tag("d"): # develop
exp = self.qlib_model_coder.develop(prev_out["exp_gen"])
logger.log_object(exp.sub_workspace_list, tag="model coder result")
return exp
def running(self, prev_out: dict[str, Any]):
with logger.tag("ef"): # evaluate and feedback
exp = self.qlib_model_runner.develop(prev_out["coding"])
logger.log_object(exp, tag="model runner result")
return exp
def feedback(self, prev_out: dict[str, Any]):
feedback = self.qlib_model_summarizer.generate_feedback(prev_out["running"], prev_out["propose"], self.trace)
logger.log_object(feedback, tag="feedback")
self.trace.hist.append((prev_out["propose"],prev_out["running"] , feedback))
def main(path=None):
"""
You can continue running session by
.. code-block:: python
dotenv run -- python rdagent/app/qlib_rd_loop/model_w_sc.py $LOG_PATH/__session__/1/0_propose
"""
if path is None:
model_loop = ModelLoop()
else:
model_loop = ModelLoop.load(path)
model_loop.run()
if __name__ == "__main__":
fire.Fire(main)