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

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

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))