mirror of
https://github.com/NicolasBohn/NexQuant.git
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WinstonLiyt
82bef3a375
* init a scenario for kaggle feature engineering * fix some bugs and add original features' description * refine the process of data downloading * fix a error * revert the code * fix a bug in feedback * fix a ci bug * fix a ci bug
32 lines
1.0 KiB
Python
32 lines
1.0 KiB
Python
from pathlib import Path
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import pandas as pd
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from rdagent.app.data_mining.conf import MED_PROP_SETTING
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from rdagent.core.experiment import FBWorkspace
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from rdagent.log import rdagent_logger as logger
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from rdagent.utils.env import DMDockerEnv
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class DMFBWorkspace(FBWorkspace):
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def __init__(self, template_folder_path: Path, *args, **kwargs) -> None:
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super().__init__(*args, **kwargs)
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self.inject_code_from_folder(template_folder_path)
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def execute(self, run_env: dict = {}, *args, **kwargs) -> str:
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qtde = DMDockerEnv()
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qtde.prepare(MED_PROP_SETTING.username, MED_PROP_SETTING.password)
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execute_log = qtde.run(
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local_path=str(self.workspace_path),
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entry=f"python train.py",
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env=run_env,
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)
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csv_path = self.workspace_path / "submission.csv"
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if not csv_path.exists():
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logger.error(f"File {csv_path} does not exist.")
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return None
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return pd.read_csv(csv_path, index_col=0).iloc[:, 0]
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