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Implement model (and some factor) coder with evolving (#52)
* store code into FBImplementation * fix path related bugs * fix a bug * fix factor related small bugs * re-submit all model related code * new code to model coder * finish the model evolving code --------- Co-authored-by: xuyang1 <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,86 @@ | ||
| import pickle | ||
| from pathlib import Path | ||
|
|
||
| from rdagent.components.coder.model_coder.conf import MODEL_IMPL_SETTINGS | ||
| from rdagent.components.coder.model_coder.CoSTEER.evaluators import ( | ||
| ModelCoderMultiEvaluator, | ||
| ) | ||
| from rdagent.components.coder.model_coder.CoSTEER.evolvable_subjects import ( | ||
| ModelEvolvingItem, | ||
| ) | ||
| from rdagent.components.coder.model_coder.CoSTEER.evolving_strategy import ( | ||
| ModelCoderEvolvingStrategy, | ||
| ) | ||
| from rdagent.components.coder.model_coder.CoSTEER.knowledge_management import ( | ||
| ModelKnowledgeBase, | ||
| ModelRAGStrategy, | ||
| ) | ||
| from rdagent.components.coder.model_coder.model import ModelExperiment | ||
| from rdagent.core.evolving_agent import RAGEvoAgent | ||
| from rdagent.core.task_generator import TaskGenerator | ||
|
|
||
|
|
||
| class ModelCoSTEER(TaskGenerator[ModelExperiment]): | ||
| def __init__( | ||
| self, | ||
| *args, | ||
| with_knowledge: bool = True, | ||
| with_feedback: bool = True, | ||
| knowledge_self_gen: bool = True, | ||
| **kwargs, | ||
| ) -> None: | ||
| super().__init__(*args, **kwargs) | ||
| self.max_loop = MODEL_IMPL_SETTINGS.max_loop | ||
| self.knowledge_base_path = ( | ||
| Path(MODEL_IMPL_SETTINGS.knowledge_base_path) | ||
| if MODEL_IMPL_SETTINGS.knowledge_base_path is not None | ||
| else None | ||
| ) | ||
| self.new_knowledge_base_path = ( | ||
| Path(MODEL_IMPL_SETTINGS.new_knowledge_base_path) | ||
| if MODEL_IMPL_SETTINGS.new_knowledge_base_path is not None | ||
| else None | ||
| ) | ||
| self.with_knowledge = with_knowledge | ||
| self.with_feedback = with_feedback | ||
| self.knowledge_self_gen = knowledge_self_gen | ||
| self.evolving_strategy = ModelCoderEvolvingStrategy(scen=self.scen) | ||
| self.model_evaluator = ModelCoderMultiEvaluator(scen=self.scen) | ||
|
|
||
| def load_or_init_knowledge_base(self, former_knowledge_base_path: Path = None, component_init_list: list = []): | ||
| if former_knowledge_base_path is not None and former_knowledge_base_path.exists(): | ||
| model_knowledge_base = pickle.load(open(former_knowledge_base_path, "rb")) | ||
| if not isinstance(model_knowledge_base, ModelKnowledgeBase): | ||
| raise ValueError("The former knowledge base is not compatible with the current version") | ||
| else: | ||
| model_knowledge_base = ModelKnowledgeBase() | ||
|
|
||
| return model_knowledge_base | ||
|
|
||
| def generate(self, exp: ModelExperiment) -> ModelExperiment: | ||
| # init knowledge base | ||
| model_knowledge_base = self.load_or_init_knowledge_base( | ||
| former_knowledge_base_path=self.knowledge_base_path, | ||
| component_init_list=[], | ||
| ) | ||
| # init rag method | ||
| self.rag = ModelRAGStrategy(model_knowledge_base) | ||
|
|
||
| # init intermediate items | ||
| model_experiment = ModelEvolvingItem(sub_tasks=exp.sub_tasks) | ||
|
|
||
| self.evolve_agent = RAGEvoAgent(max_loop=self.max_loop, evolving_strategy=self.evolving_strategy, rag=self.rag) | ||
|
|
||
| model_experiment = self.evolve_agent.multistep_evolve( | ||
| model_experiment, | ||
| self.model_evaluator, | ||
| with_knowledge=self.with_knowledge, | ||
| with_feedback=self.with_feedback, | ||
| knowledge_self_gen=self.knowledge_self_gen, | ||
| ) | ||
|
|
||
| # save new knowledge base | ||
| if self.new_knowledge_base_path is not None: | ||
| pickle.dump(model_knowledge_base, open(self.new_knowledge_base_path, "wb")) | ||
| self.knowledge_base = model_knowledge_base | ||
| return model_experiment |
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