mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-08-06 03:27:44 +00:00
Xu Yang
6a4998154d
* feat: add time ratio limit for hyperparameter tuning in Kaggle settings and update evaluator logic * add recommend time limit * remove 25% hard line * small fix
83 lines
3.0 KiB
Python
83 lines
3.0 KiB
Python
from pydantic_settings import SettingsConfigDict
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from rdagent.core.conf import ExtendedBaseSettings
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class KaggleBasePropSetting(ExtendedBaseSettings):
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model_config = SettingsConfigDict(env_prefix="KG_", protected_namespaces=())
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# 1) overriding the default
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scen: str = "rdagent.scenarios.kaggle.experiment.scenario.KGScenario"
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"""Scenario class for data mining model"""
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hypothesis_gen: str = "rdagent.scenarios.kaggle.proposal.proposal.KGHypothesisGen"
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"""Hypothesis generation class"""
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hypothesis2experiment: str = "rdagent.scenarios.kaggle.proposal.proposal.KGHypothesis2Experiment"
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"""Hypothesis to experiment class"""
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feature_coder: str = "rdagent.scenarios.kaggle.developer.coder.KGFactorCoSTEER"
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"""Feature Coder class"""
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model_feature_selection_coder: str = "rdagent.scenarios.kaggle.developer.coder.KGModelFeatureSelectionCoder"
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"""Model Feature Selection Coder class"""
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model_coder: str = "rdagent.scenarios.kaggle.developer.coder.KGModelCoSTEER"
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"""Model Coder class"""
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feature_runner: str = "rdagent.scenarios.kaggle.developer.runner.KGFactorRunner"
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"""Feature Runner class"""
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model_runner: str = "rdagent.scenarios.kaggle.developer.runner.KGModelRunner"
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"""Model Runner class"""
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summarizer: str = "rdagent.scenarios.kaggle.developer.feedback.KGExperiment2Feedback"
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"""Summarizer class"""
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evolving_n: int = 10
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"""Number of evolutions"""
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competition: str = ""
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"""Kaggle competition name, e.g., 'sf-crime'"""
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template_path: str = "rdagent/scenarios/kaggle/experiment/templates"
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"""Kaggle competition base templates path"""
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local_data_path: str = ""
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"""Folder storing Kaggle competition data"""
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# Evaluation on Test related
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if_using_mle_data: bool = False
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auto_submit: bool = False
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"""Automatically upload and submit each experiment result to Kaggle platform"""
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# Conditionally set the knowledge_base based on the use of graph RAG
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knowledge_base: str = ""
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"""Knowledge base class, uses 'KGKnowledgeGraph' when advanced graph-based RAG is enabled, otherwise empty."""
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if_action_choosing_based_on_UCB: bool = False
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"""Enable decision mechanism based on UCB algorithm"""
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domain_knowledge_path: str = "/data/userdata/share/kaggle/domain_knowledge"
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"""Folder storing domain knowledge files in .case format"""
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knowledge_base_path: str = "kg_graph.pkl"
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"""Advanced version of graph-based RAG"""
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rag_path: str = "git_ignore_folder/kaggle_vector_base.pkl"
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"""Base version of vector-based RAG"""
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if_using_vector_rag: bool = False
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"""Enable basic vector-based RAG"""
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if_using_graph_rag: bool = False
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"""Enable advanced graph-based RAG"""
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mini_case: bool = False
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"""Enable mini-case study for experiments"""
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time_ratio_limit_to_enable_hyperparameter_tuning: int | None = None
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"""Time ratio limit to enable hyperparameter tuning, if None, hyperparameter tuning is always enabled in the first evolution."""
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KAGGLE_IMPLEMENT_SETTING = KaggleBasePropSetting()
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