wehub-resource-sync
42 lines
1.5 KiB
Python
42 lines
1.5 KiB
Python
from pathlib import Path
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from pydantic_settings import SettingsConfigDict
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from rdagent.core.conf import ExtendedBaseSettings
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class RLPostTrainingPropSetting(ExtendedBaseSettings):
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"""RL Post-training dedicated property settings.
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Use RL_ env prefix for overrides.
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"""
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model_config = SettingsConfigDict(env_prefix="RL_", protected_namespaces=())
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# Main Components
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scen: str = "rdagent.scenarios.rl.scen.scenario.RLPostTrainingScen"
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hypothesis_gen: str = "rdagent.scenarios.rl.proposal.proposal.RLPostTrainingExpGen"
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coder: str = "rdagent.components.coder.rl.RLCoSTEER"
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runner: str = "rdagent.scenarios.rl.train.runner.RLPostTrainingRunner"
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summarizer: str = "rdagent.scenarios.rl.dev.feedback.RLExperiment2Feedback"
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# Resource paths (unified directory management, similar to SFT)
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file_path: Path = Path.cwd() / "git_ignore_folder" / "rl_files"
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"""RL resource root directory. Contains datasets/ and models/ subdirectories.
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Can be overridden via RL_FILE_PATH environment variable."""
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# Core config
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base_model: str | None = None
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"""Model name (e.g., 'Qwen2.5-Coder-0.5B-Instruct'). Docker path: /models/{base_model}"""
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benchmark: str | None = None
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"""Benchmark/dataset name (e.g., 'gsm8k'). Docker path: /data/{benchmark}"""
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# Benchmark evaluation
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benchmark_timeout: int = 0
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"""Benchmark evaluation timeout in seconds. 0 means no timeout."""
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# Global setting instance
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RL_RD_SETTING = RLPostTrainingPropSetting()
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