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you-n-g
58 lines
2.1 KiB
Python
58 lines
2.1 KiB
Python
from rdagent.app.kaggle.conf import KaggleBasePropSetting
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from rdagent.core.conf import ExtendedSettingsConfigDict
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class DataScienceBasePropSetting(KaggleBasePropSetting):
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model_config = ExtendedSettingsConfigDict(env_prefix="DS_", protected_namespaces=())
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# Main components
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## Scen
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scen: str = "rdagent.scenarios.data_science.scen.KaggleScen"
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"""Scenario class for data mining model"""
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## proposal
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exp_gen: str = "rdagent.scenarios.data_science.proposal.exp_gen.DSExpGen"
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# exp_gen_init_kwargs: dict = {"max_trace_hist": 3} # TODO: to be configurable
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# the two below should be used in ExpGen
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# hypothesis_gen: str = "rdagent.scenarios.kaggle.proposal.proposal.KGHypothesisGen"
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# """Hypothesis generation class"""
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#
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# hypothesis2experiment: str = "rdagent.scenarios.kaggle.proposal.proposal.KGHypothesis2Experiment"
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# """Hypothesis to experiment class"""
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## dev/coder
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data_loader_coder: str = "rdagent.components.coder.data_science.raw_data_loader.DataLoaderCoSTEER"
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"""Data Loader CoSTEER"""
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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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## dev/runner
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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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## feedback
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summarizer: str = "rdagent.scenarios.kaggle.developer.feedback.KGExperiment2Feedback"
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"""Summarizer class"""
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## Workflow Related
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consecutive_errors: int = 5
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debug_timeout: int = 600
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"""The timeout limit for running on debugging data"""
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full_timeout: int = 3600
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"""The timeout limit for running on full data"""
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DS_RD_SETTING = DataScienceBasePropSetting()
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