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Code Issues Packages Projects Releases Wiki Activity

feat: Model context for tuning and selection (#284)

Browse Source 
* Revised for tuning

* Fixed a bug

* fix a ci bug

---------

Co-authored-by: WinstonLiye <1957922024@qq.com>
This commit is contained in:
Way2Learn
2024-09-20 16:40:47 +08:00
committed by GitHub
parent 9f8a041b96
commit 7ade6d2db1
2 changed files with 40 additions and 3 deletions
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rdagent/components/coder/model_coder/CoSTEER/evolving_strategy.py
+35 -3
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@@ -11,7 +11,11 @@ from rdagent.components.coder.model_coder.CoSTEER.evolvable_subjects import (
from rdagent.components.coder.model_coder.CoSTEER.knowledge_management import (
ModelQueriedKnowledge,
)
from rdagent.components.coder.model_coder.model import ModelFBWorkspace, ModelTask
from rdagent.components.coder.model_coder.model import (
ModelExperiment,
ModelFBWorkspace,
ModelTask,
)
from rdagent.core.conf import RD_AGENT_SETTINGS
from rdagent.core.evolving_framework import EvolvingStrategy
from rdagent.core.prompts import Prompts
@@ -26,8 +30,23 @@ class ModelCoderEvolvingStrategy(EvolvingStrategy):
self,
target_task: ModelTask,
queried_knowledge: ModelQueriedKnowledge = None,
exp: ModelExperiment = None, # Add this parameter
) -> str:
model_information_str = target_task.get_task_information()
model_type = target_task.model_type
# Get the current code from the experiment using build_from_SOTA
current_code = ""
if exp is not None:
self.build_from_SOTA(exp)
model_file_mapping = {
"XGBoost": "model_xgb.py",
"RandomForest": "model_rf.py",
"LightGBM": "model_lgb.py",
"NN": "model_nn.py",
}
if model_type in model_file_mapping:
current_code = exp.experiment_workspace.code_dict.get(model_file_mapping[model_type], "")
if queried_knowledge is not None and model_information_str in queried_knowledge.success_task_to_knowledge_dict:
return queried_knowledge.success_task_to_knowledge_dict[model_information_str].implementation
@@ -55,6 +74,7 @@ class ModelCoderEvolvingStrategy(EvolvingStrategy):
.render(
scenario=self.scen.get_scenario_all_desc(),
queried_former_failed_knowledge=queried_former_failed_knowledge_to_render,
current_code=current_code, # Add this line
)
)
@@ -67,6 +87,7 @@ class ModelCoderEvolvingStrategy(EvolvingStrategy):
)
.render(
model_information_str=model_information_str,
model_type=model_type, # Add model type to the prompt
queried_similar_successful_knowledge=queried_similar_successful_knowledge_to_render,
queried_former_failed_knowledge=queried_former_failed_knowledge_to_render,
)
@@ -103,7 +124,7 @@ class ModelCoderEvolvingStrategy(EvolvingStrategy):
queried_knowledge: ModelQueriedKnowledge | None = None,
**kwargs,
) -> ModelEvolvingItem:
# 1.找出需要evolve的model
# 1. Find the models that need to be evolved
to_be_finished_task_index = []
for index, target_model_task in enumerate(evo.sub_tasks):
target_model_task_desc = target_model_task.get_task_information()
@@ -125,10 +146,21 @@ class ModelCoderEvolvingStrategy(EvolvingStrategy):
n=RD_AGENT_SETTINGS.multi_proc_n,
)
model_file_mapping = {
"XGBoost": "model_xgb.py",
"RandomForest": "model_rf.py",
"LightGBM": "model_lgb.py",
"NN": "model_nn.py",
}
for index, target_index in enumerate(to_be_finished_task_index):
if evo.sub_workspace_list[target_index] is None:
evo.sub_workspace_list[target_index] = ModelFBWorkspace(target_task=evo.sub_tasks[target_index])
evo.sub_workspace_list[target_index].inject_code(**{"model.py": result[index]})
model_type = evo.sub_tasks[target_index].model_type
if model_type in model_file_mapping:
evo.sub_workspace_list[target_index].inject_code(**{model_file_mapping[model_type]: result[index]})
else:
raise ValueError(f"Unsupported model type: {model_type}")
evo.corresponding_selection = to_be_finished_task_index