diff --git a/rdagent/scenarios/qlib/task_generator/model.py b/rdagent/scenarios/qlib/task_generator/model.py index 7fc0fabc7..b9c28199d 100644 --- a/rdagent/scenarios/qlib/task_generator/model.py +++ b/rdagent/scenarios/qlib/task_generator/model.py @@ -1,16 +1,35 @@ -from rdagent.components.coder.model_coder.model import ModelImplementation from rdagent.core.task_generator import TaskGenerator - -class QlibModelImplementation(TaskGenerator[ModelImplementation]): +# FBTaskImpl... +class QlibModelTaskImpl(ModelTaskImpl): """ - Docker run - Everything in a folder - - config.yaml - - Pytorch `model.py` - - results in `mlflow` - - https://github.com/microsoft/qlib/blob/main/qlib/contrib/model/pytorch_nn.py - - pt_model_uri: hard-code `model.py:Net` in the config - - let LLM modify model.py + Docker-based Qlib image + + code should be implementd in a folder, + Then the folder should be mounted into a Qlib docker image + + # This is Mr Xiao's work??? """ + + def __init__(self, **kwargs): + self.kwargs = kwargs + + # def prepare(self): + # pass + + def execute(self): + """ + docker run -v : qlib_image + + qpte = QPTDockerEnv + + qpte.run(local_path=self.XXXXpath, entry="qrun ...") + + # TODO: inject exp analysis code + qpte.run(local_path=self.XXXXpath, entry="python read_exp.py") + + append following code into read_exp.py + to_pickle() or to_csv() # which does not depend on environment. + + read_csv or pickle in RD-Agent Env; + """