mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-07-28 16:07:46 +00:00
Xu Yang
c9346a9377
* Implemented model.py - Need to run within the RDAgent folder (relevant path) - Each time copy a template & insert code & run qlib & store result back to experiment * Create model.py * Create conf.yaml This is the sample conf.yaml to be copied each time. This has gone several times of iteration and is now working for both tabular and Time-Series data. * Create read_exp.py This is to read the results within Qlib * Create ReadMe.md * Update model.py * Create test_model.py A testing file that separates model code generation and running&feedback section. * move the template folder * help xisen finish the model runner * help xisen fix improve model feedback generation * delete debug file * rename readme.md --------- Co-authored-by: Xisen Wang <118058822+Xisen-Wang@users.noreply.github.com>
39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
"""
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TODO: Model Structure RD-Loop
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TODO: move the following code to a new class: Model_RD_Agent
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"""
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# import_from
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from rdagent.app.qlib_rd_loop.conf import PROP_SETTING
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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.task_generator import TaskGenerator
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from rdagent.core.utils import import_class
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scen: Scenario = import_class(PROP_SETTING.qlib_model_scen)()
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hypothesis_gen: HypothesisGen = import_class(PROP_SETTING.qlib_model_hypothesis_gen)(scen)
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hypothesis2experiment: Hypothesis2Experiment = import_class(PROP_SETTING.qlib_model_hypothesis2experiment)()
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qlib_model_coder: TaskGenerator = import_class(PROP_SETTING.qlib_model_coder)(scen)
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qlib_model_runner: TaskGenerator = import_class(PROP_SETTING.qlib_model_runner)(scen)
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qlib_model_summarizer: HypothesisExperiment2Feedback = import_class(PROP_SETTING.qlib_model_summarizer)(scen)
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trace = Trace(scen=scen)
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for _ in range(PROP_SETTING.evolving_n):
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hypothesis = hypothesis_gen.gen(trace)
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exp = hypothesis2experiment.convert(hypothesis, trace)
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exp = qlib_model_coder.generate(exp)
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exp = qlib_model_runner.generate(exp)
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feedback = qlib_model_summarizer.generateFeedback(exp, hypothesis, trace)
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trace.hist.append((hypothesis, exp, feedback))
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