re-change imputer path

mieskolainen · Jun 19, 2024 · d6417e3 · d6417e3
1 parent 4293055
commit d6417e3
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Showing 2 changed files with 7 additions and 10 deletions.
diff --git a/icedqcd/deploy.py b/icedqcd/deploy.py
@@ -246,15 +246,13 @@ def process_data(args):
                 if param['predict'] in ['xgb', 'xgb_logistic']:
 
                     print(f'Evaluating MVA-model "{ID}" \n')
-                    
+
                     ## 1. Impute data
                     if args['imputation_param']['active']:
-
-                        fmodel = f'{args["datadir"]}/imputer_{args["__hash_genesis__"]}.pkl'
-                        cprint(f'Loading imputer from: {fmodel}', 'green')
+
+                        fmodel  = f'{args["modeldir"]}/imputer.pkl'
                         imputer = pickle.load(open(fmodel, 'rb'))
-
-                        data['data'], _ = process.impute_datasets(data=data['data'], features=None, args=args['imputation_param'], imputer=imputer)
+                        data['data'], _  = process.impute_datasets(data=data['data'], features=None, args=args['imputation_param'], imputer=imputer)
 
                     ## 2. Apply the input variable set reductor
                     X,ids = aux.red(X=data['data'].x, ids=data['data'].ids, param=param)
@@ -349,7 +347,7 @@ def get_predictor(args, param, feature_names=None):
 
     elif param['predict'] == 'xgb_logistic':
         func_predict, model = predict.pred_xgb_logistic(args=args, param=param, feature_names=feature_names, return_model=True)
-    
+
     #elif param['predict'] == 'torch_vector':
     #    func_predict = predict.pred_torch_generic(args=args, param=param)
 
@@ -360,4 +358,3 @@ def get_predictor(args, param, feature_names=None):
         raise Exception(__name__ + f'.get_predictor: Unknown param["predict"] = {param["predict"]}')
 
     return func_predict, model
-
diff --git a/icenet/tools/process.py b/icenet/tools/process.py
@@ -651,7 +651,7 @@ def process_data(args, predata, func_factor, mvavars, runmode):
             output['trn']['data'], imputer = impute_datasets(data=output['trn']['data'], features=impute_vars, args=args['imputation_param'], imputer=None)
             output['val']['data'], imputer = impute_datasets(data=output['val']['data'], features=impute_vars, args=args['imputation_param'], imputer=imputer)
 
-            fmodel = f'{args["datadir"]}/imputer_{args["__hash_genesis__"]}.pkl'
+            fmodel = f'{args["modeldir"]}/imputer.pkl'
 
             cprint(__name__ + f'.process_data: Saving imputer to: {fmodel}', 'green')
             pickle.dump(imputer, open(fmodel, 'wb'), protocol=pickle.HIGHEST_PROTOCOL)
@@ -686,7 +686,7 @@ def process_data(args, predata, func_factor, mvavars, runmode):
         ## Imputate
         if args['imputation_param']['active']:
 
-            fmodel = f'{args["datadir"]}/imputer_{args["__hash_genesis__"]}.pkl'
+            fmodel = f'{args["modeldir"]}/imputer.pkl'
 
             cprint(__name__ + f'.process_data: Loading imputer from: {fmodel}', 'green')
             imputer = pickle.load(open(fmodel, 'rb'))