mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-07-28 16:07:46 +00:00
Xu Yang
be2c19307e
* 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>
34 lines
1.4 KiB
Python
34 lines
1.4 KiB
Python
import pickle
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from pathlib import Path
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from typing import Tuple
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from rdagent.components.runner.conf import RUNNER_SETTINGS
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from rdagent.core.experiment import ASpecificExp, Experiment
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from rdagent.core.task_generator import TaskGenerator
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from rdagent.oai.llm_utils import md5_hash
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class CachedRunner(TaskGenerator[ASpecificExp]):
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def get_cache_key(self, exp: Experiment) -> str:
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all_tasks = []
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for based_exp in exp.based_experiments:
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all_tasks.extend(based_exp.sub_tasks)
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all_tasks.extend(exp.sub_tasks)
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task_info_list = [task.get_task_information() for task in all_tasks]
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task_info_str = "\n".join(task_info_list)
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return md5_hash(task_info_str)
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def get_cache_result(self, exp: Experiment) -> Tuple[bool, object]:
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task_info_key = self.get_cache_key(exp)
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Path(RUNNER_SETTINGS.runner_cache_path).mkdir(parents=True, exist_ok=True)
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cache_path = Path(RUNNER_SETTINGS.runner_cache_path) / f"{task_info_key}.pkl"
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if cache_path.exists():
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return True, pickle.load(open(cache_path, "rb"))
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else:
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return False, None
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def dump_cache_result(self, exp: Experiment, result: object):
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task_info_key = self.get_cache_key(exp)
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cache_path = Path(RUNNER_SETTINGS.runner_cache_path) / f"{task_info_key}.pkl"
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pickle.dump(result, open(cache_path, "wb"))
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