feat: implement isolated model feature selection loop (#370)

* rename meta_tpl

* use a isolated coder to deal with model feature selection and refine the structure

* fix CI

* fix: fix some errors in scenario.py, proposal.py and runner.py and several complex competition scenarios(#365)

* fix several bugs in proposal and runner

* fix a bug in feedback-prize-english-language-learning

* fix some bugs and templates

* fix the bug in optiver and nlp problem

* delete unnecessary codes

* remove unnecessary codes

* complete forest and s4e8

* push

* feedback & s4e8 &  forest

* optiver finished

* s3e11 & s3e26

* s4e9 finished

* sf-crime finished

* the last one finished

---------

Co-authored-by: WinstonLiyt <104308117+WinstonLiyt@users.noreply.github.com>
Co-authored-by: WinstonLiyte <1957922024@qq.com>

rdagent/components/coder/model_coder/CoSTEER/evolving_strategy.py

@@ -21,6 +21,7 @@ from rdagent.core.evolving_framework import EvolvingStrategy
 from rdagent.core.prompts import Prompts
 from rdagent.core.utils import multiprocessing_wrapper
 from rdagent.oai.llm_utils import APIBackend
+from rdagent.scenarios.kaggle.experiment.kaggle_experiment import KG_MODEL_MAPPING
 
 coder_prompts = Prompts(file_path=Path(__file__).parent.parent / "prompts.yaml")
 
@@ -41,14 +42,8 @@ class ModelCoderEvolvingStrategy(EvolvingStrategy):
             current_code = ""
             sota_exp_code_dict = current_exp.based_experiments[-1].experiment_workspace.code_dict
             if target_task.version == 2:
-                model_file_mapping = {
-                    "XGBoost": "model/model_xgboost.py",
-                    "RandomForest": "model/model_randomforest.py",
-                    "LightGBM": "model/model_lightgbm.py",
-                    "NN": "model/model_nn.py",
-                }
-                if model_type in model_file_mapping:
-                    current_code = sota_exp_code_dict.get(model_file_mapping[model_type], None)
+                if model_type in KG_MODEL_MAPPING:
+                    current_code = sota_exp_code_dict.get(KG_MODEL_MAPPING[model_type], None)
                 elif "model.py" in sota_exp_code_dict:
                     current_code = sota_exp_code_dict["model.py"]
                 else:

rdagent/components/coder/model_coder/model_execute_template_v2.txt

@@ -4,7 +4,7 @@ import pickle
 import numpy as np
 import pandas as pd
 import torch
-from model import fit, predict, select
+from model import fit, predict
 
 train_X = pd.DataFrame(np.random.randn(8, 30), columns=[f"{i}" for i in range(30)])
 train_y = pd.Series(np.random.randint(0, 2, 8))