Revised model.py

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 <path to model>:<model in the image> 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;
+        """