mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-07-28 16:07:46 +00:00
WinstonLiyt
ca6d3194d4
* Add runtime measurement for each step and loop in RDLoop. * refine some codes * refine the code (#276) * show variables only when it exists (#277) * fix: support seed and fix absolute path (#278) * fix: support seed and fix absolute path * Absolute path * lint * fix: improve_execution_time_in_kaggle_loop (#279) * improve_execution_time_in_kaggle_loop * fix CI * fix CI * fix CI * fix: Update runner.py to fix a small bug (#282) * fix: Update runner.py to fix a small bug * fix CI * refine the code * Update loop.py * Update rd_loop.py * Update model_xgb.py --------- Co-authored-by: XianBW <36835909+XianBW@users.noreply.github.com> Co-authored-by: you-n-g <you-n-g@users.noreply.github.com> Co-authored-by: Xu Yang <peteryang@vip.qq.com>
81 lines
3.2 KiB
Python
81 lines
3.2 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 time
|
|
from typing import Any
|
|
|
|
from rdagent.components.workflow.conf import BasePropSetting
|
|
from rdagent.core.developer import Developer
|
|
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.log.time import measure_time
|
|
from rdagent.utils.workflow import LoopBase, LoopMeta
|
|
|
|
|
|
class RDLoop(LoopBase, metaclass=LoopMeta):
|
|
@measure_time
|
|
def __init__(self, PROP_SETTING: BasePropSetting):
|
|
with logger.tag("init"):
|
|
scen: Scenario = import_class(PROP_SETTING.scen)()
|
|
logger.log_object(scen, tag="scenario")
|
|
|
|
self.hypothesis_gen: HypothesisGen = import_class(PROP_SETTING.hypothesis_gen)(scen)
|
|
logger.log_object(self.hypothesis_gen, tag="hypothesis generator")
|
|
|
|
self.hypothesis2experiment: Hypothesis2Experiment = import_class(PROP_SETTING.hypothesis2experiment)()
|
|
logger.log_object(self.hypothesis2experiment, tag="hypothesis2experiment")
|
|
|
|
self.coder: Developer = import_class(PROP_SETTING.coder)(scen)
|
|
logger.log_object(self.coder, tag="coder")
|
|
self.runner: Developer = import_class(PROP_SETTING.runner)(scen)
|
|
logger.log_object(self.runner, tag="runner")
|
|
|
|
self.summarizer: HypothesisExperiment2Feedback = import_class(PROP_SETTING.summarizer)(scen)
|
|
logger.log_object(self.summarizer, tag="summarizer")
|
|
self.trace = Trace(scen=scen)
|
|
super().__init__()
|
|
|
|
@measure_time
|
|
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
|
|
|
|
@measure_time
|
|
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
|
|
|
|
@measure_time
|
|
def coding(self, prev_out: dict[str, Any]):
|
|
with logger.tag("d"): # develop
|
|
exp = self.coder.develop(prev_out["exp_gen"])
|
|
logger.log_object(exp.sub_workspace_list, tag="coder result")
|
|
return exp
|
|
|
|
@measure_time
|
|
def running(self, prev_out: dict[str, Any]):
|
|
with logger.tag("ef"): # evaluate and feedback
|
|
exp = self.runner.develop(prev_out["coding"])
|
|
logger.log_object(exp, tag="runner result")
|
|
return exp
|
|
|
|
@measure_time
|
|
def feedback(self, prev_out: dict[str, Any]):
|
|
feedback = self.summarizer.generate_feedback(prev_out["running"], prev_out["propose"], self.trace)
|
|
with logger.tag("ef"): # evaluate and feedback
|
|
logger.log_object(feedback, tag="feedback")
|
|
self.trace.hist.append((prev_out["propose"], prev_out["running"], feedback))
|