mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-07-27 23:47:46 +00:00
7800805e04
* update rdagent cmd * fix log error message * use multiProcessing.Process instead of subprocess.Popen * add traces to gitignore * add user interactor in RDLoop (finance scenarios) * add interactor (feedback, hypothesis) for quant scens * fix the test_end in qlib conf * add features init config, general instruction to qlib scenarios * set base features for based exp * fix bug when combine factors * move traces folder to git_ignore_folder * fix bug in features init * fix quant interact bug * fix logger warning error * bug fixes * modify rdagent logger, now it can set file output * adjust cli functions and fix logger bug * fix server port transport problem * update server_ui in cli * add web code * fix CI problem * black fix * update web ui README * update README * update readme
50 lines
1.3 KiB
Python
50 lines
1.3 KiB
Python
"""
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Model workflow with session control
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"""
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import asyncio
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import fire
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from rdagent.app.qlib_rd_loop.conf import MODEL_PROP_SETTING
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from rdagent.components.workflow.rd_loop import RDLoop
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from rdagent.core.exception import ModelEmptyError
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class ModelRDLoop(RDLoop):
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skip_loop_error = (ModelEmptyError,)
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def main(
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path=None,
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step_n: int | None = None,
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loop_n: int | None = None,
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all_duration: str | None = None,
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checkout: bool = True,
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base_features_path: str | None = None,
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**kwargs,
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):
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"""
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Auto R&D Evolving loop for fintech models
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You can continue running session by
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.. code-block:: python
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dotenv run -- python rdagent/app/qlib_rd_loop/model.py $LOG_PATH/__session__/1/0_propose --step_n 1 # `step_n` is a optional paramter
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"""
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if path is None:
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model_loop = ModelRDLoop(MODEL_PROP_SETTING)
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else:
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model_loop = ModelRDLoop.load(path, checkout=checkout)
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model_loop._init_base_features(base_features_path)
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if "user_interaction_queues" in kwargs and kwargs["user_interaction_queues"] is not None:
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model_loop._set_interactor(*kwargs["user_interaction_queues"])
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model_loop._interact_init_params()
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asyncio.run(model_loop.run(step_n=step_n, loop_n=loop_n, all_duration=all_duration))
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if __name__ == "__main__":
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fire.Fire(main)
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