03250942

models_processing/model_tf/tf_bp_train.py

@@ -57,7 +57,7 @@ def model_training_bp():
         model = bp.train_init() if bp.opt.Model['add_train'] else bp.get_keras_model(bp.opt)
         if bp.opt.Model['add_train']:
             if model:
-                feas = json.loads(bp.model_params).get('features', dh.opt.features)
+                feas = json.loads(bp.model_params)['features']
                 if set(feas).issubset(set(dh.opt.features)):
                     dh.opt.features = list(feas)
                     train_x, train_y, valid_x, valid_y, scaled_train_bytes, scaled_target_bytes, scaled_cap = dh.train_data_handler(train_data)

models_processing/model_tf/tf_cnn_train.py

@@ -59,7 +59,7 @@ def model_training_bp():
         model = cnn.train_init() if cnn.opt.Model['add_train'] else cnn.get_keras_model(cnn.opt)
         if cnn.opt.Model['add_train']:
             if model:
-                feas = json.loads(cnn.model_params).get('features', dh.opt.features)
+                feas = json.loads(cnn.model_params)['features']
                 if set(feas).issubset(set(dh.opt.features)):
                     dh.opt.features = list(feas)
                     train_x, train_y, valid_x, valid_y, scaled_train_bytes, scaled_target_bytes, scaled_cap = dh.train_data_handler(train_data)

models_processing/model_tf/tf_lstm_train.py

@@ -56,7 +56,7 @@ def model_training_bp():
         model = ts.train_init() if ts.opt.Model['add_train'] else ts.get_keras_model(ts.opt)
         if ts.opt.Model['add_train']:
             if model:
-                feas = json.loads(ts.model_params).get('features', dh.opt.features)
+                feas = json.loads(ts.model_params)['features']
                 if set(feas).issubset(set(dh.opt.features)):
                     dh.opt.features = list(feas)
                     train_x, train_y, valid_x, valid_y, scaled_train_bytes, scaled_target_bytes, scaled_cap = dh.train_data_handler(train_data)

models_processing/model_tf/tf_test_train.py

@@ -56,7 +56,7 @@ def model_training_test():
         model = ts.train_init() if ts.opt.Model['add_train'] else ts.get_keras_model(ts.opt)
         if ts.opt.Model['add_train']:
             if model:
-                feas = json.loads(ts.model_params).get('features', dh.opt.features)
+                feas = json.loads(ts.model_params)['features']
                 if set(feas).issubset(set(dh.opt.features)):
                     dh.opt.features = list(feas)
                     train_x, train_y, valid_x, valid_y, scaled_train_bytes, scaled_target_bytes, scaled_cap = dh.train_data_handler(