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fix: update code to fix a small bug in model cache md5 hash (#303)
* update code to fix a small bug in model cache md5 hash * fix another bug dumping the wrong name to costeer model * fix a black CI
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@@ -146,21 +146,9 @@ class ModelCoderEvolvingStrategy(EvolvingStrategy):
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n=RD_AGENT_SETTINGS.multi_proc_n,
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)
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model_file_mapping = {
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"XGBoost": "model_xgb.py",
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"RandomForest": "model_rf.py",
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"LightGBM": "model_lgb.py",
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"NN": "model_nn.py",
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}
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for index, target_index in enumerate(to_be_finished_task_index):
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if evo.sub_workspace_list[target_index] is None:
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evo.sub_workspace_list[target_index] = ModelFBWorkspace(target_task=evo.sub_tasks[target_index])
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model_type = evo.sub_tasks[target_index].model_type
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if model_type in model_file_mapping:
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evo.sub_workspace_list[target_index].inject_code(**{model_file_mapping[model_type]: result[index]})
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else:
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raise ValueError(f"Unsupported model type: {model_type}")
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evo.sub_workspace_list[target_index] = ModelFBWorkspace(target_task=evo.sub_tasks[target_index])
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evo.sub_workspace_list[target_index].inject_code(**{"model.py": result[index]})
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evo.corresponding_selection = to_be_finished_task_index
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@@ -84,9 +84,10 @@ class ModelFBWorkspace(FBWorkspace):
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try:
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if MODEL_IMPL_SETTINGS.enable_execution_cache:
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# NOTE: cache the result for the same code
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target_file_name = md5_hash(
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f"{batch_size}_{num_features}_{num_timesteps}_{input_value}_{param_init_value}_{self.code_dict['model.py']}"
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)
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target_file_name = f"{batch_size}_{num_features}_{num_timesteps}_{input_value}_{param_init_value}"
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for code_file_name in sorted(list(self.code_dict.keys())):
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target_file_name = f"{target_file_name}_{self.code_dict[code_file_name]}"
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target_file_name = md5_hash(target_file_name)
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cache_file_path = Path(MODEL_IMPL_SETTINGS.cache_location) / f"{target_file_name}.pkl"
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Path(MODEL_IMPL_SETTINGS.cache_location).mkdir(exist_ok=True, parents=True)
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if cache_file_path.exists():
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