refactor(prod_model): ordering

Author: PLtier

github_dagger_workflow_project/04_prod_model.py

@@ -4,10 +4,6 @@
 from github_dagger_workflow_project.config import PROD_BEST_EXPERIMENT_PATH
 from github_dagger_workflow_project.mlflow_client import client
 
-artifact_path = "model"
-model_name = "lead_model"
-experiment_best = pd.read_pickle(PROD_BEST_EXPERIMENT_PATH)
-
 
 def get_production_model(model_name):
     return [
@@ -29,6 +25,11 @@ def register_and_wait_model(run_id, artifact_path, model_name):
     return dict(model_details)
 
 
+artifact_path = "model"
+model_name = "lead_model"
+experiment_best = pd.read_pickle(PROD_BEST_EXPERIMENT_PATH)
+
+
 train_model_score = experiment_best["metrics.f1_score"]
 run_id = None
 prod_model = get_production_model(model_name)