mirror of
https://github.com/NicolasBohn/NexQuant.git
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WinstonLiyt
a2d86f2efe
* 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
"""
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Model workflow with session control
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It is from `rdagent/app/qlib_rd_loop/model.py` and try to replace `rdagent/app/qlib_rd_loop/RDAgent.py`
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"""
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import time
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from typing import Any
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from rdagent.components.workflow.conf import BasePropSetting
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from rdagent.core.developer import Developer
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from rdagent.core.proposal import (
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Hypothesis2Experiment,
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HypothesisExperiment2Feedback,
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HypothesisGen,
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Trace,
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)
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from rdagent.core.scenario import Scenario
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from rdagent.core.utils import import_class
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from rdagent.log import rdagent_logger as logger
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from rdagent.log.time import measure_time
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from rdagent.utils.workflow import LoopBase, LoopMeta
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class RDLoop(LoopBase, metaclass=LoopMeta):
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@measure_time
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def __init__(self, PROP_SETTING: BasePropSetting):
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with logger.tag("init"):
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scen: Scenario = import_class(PROP_SETTING.scen)()
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logger.log_object(scen, tag="scenario")
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self.hypothesis_gen: HypothesisGen = import_class(PROP_SETTING.hypothesis_gen)(scen)
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logger.log_object(self.hypothesis_gen, tag="hypothesis generator")
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self.hypothesis2experiment: Hypothesis2Experiment = import_class(PROP_SETTING.hypothesis2experiment)()
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logger.log_object(self.hypothesis2experiment, tag="hypothesis2experiment")
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self.coder: Developer = import_class(PROP_SETTING.coder)(scen)
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logger.log_object(self.coder, tag="coder")
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self.runner: Developer = import_class(PROP_SETTING.runner)(scen)
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logger.log_object(self.runner, tag="runner")
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self.summarizer: HypothesisExperiment2Feedback = import_class(PROP_SETTING.summarizer)(scen)
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logger.log_object(self.summarizer, tag="summarizer")
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self.trace = Trace(scen=scen)
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super().__init__()
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@measure_time
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def propose(self, prev_out: dict[str, Any]):
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with logger.tag("r"): # research
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hypothesis = self.hypothesis_gen.gen(self.trace)
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logger.log_object(hypothesis, tag="hypothesis generation")
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return hypothesis
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@measure_time
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def exp_gen(self, prev_out: dict[str, Any]):
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with logger.tag("r"): # research
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exp = self.hypothesis2experiment.convert(prev_out["propose"], self.trace)
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logger.log_object(exp.sub_tasks, tag="experiment generation")
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return exp
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@measure_time
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def coding(self, prev_out: dict[str, Any]):
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with logger.tag("d"): # develop
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exp = self.coder.develop(prev_out["exp_gen"])
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logger.log_object(exp.sub_workspace_list, tag="coder result")
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return exp
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@measure_time
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def running(self, prev_out: dict[str, Any]):
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with logger.tag("ef"): # evaluate and feedback
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exp = self.runner.develop(prev_out["coding"])
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logger.log_object(exp, tag="runner result")
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return exp
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@measure_time
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def feedback(self, prev_out: dict[str, Any]):
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feedback = self.summarizer.generate_feedback(prev_out["running"], prev_out["propose"], self.trace)
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with logger.tag("ef"): # evaluate and feedback
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logger.log_object(feedback, tag="feedback")
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self.trace.hist.append((prev_out["propose"], prev_out["running"], feedback))
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