multiple logged metrics in cv (#114)

flaml/ml.py

@@ -233,7 +233,10 @@ def evaluate_model_CV(
         valid_fold_num += 1
         total_val_loss += val_loss_i
         if train_loss is not False:
-            if total_train_loss != 0:
+            if isinstance(total_train_loss, list):
+                total_train_loss = [
+                    total_train_loss[i] + v for i, v in enumerate(train_loss_i)]
+            elif total_train_loss != 0:
                 total_train_loss += train_loss_i
             else:
                 total_train_loss = train_loss_i
@@ -246,7 +249,10 @@ def evaluate_model_CV(
             break
     val_loss = np.max(val_loss_list)
     if train_loss is not False:
-        train_loss = total_train_loss / n
+        if isinstance(total_train_loss, list):
+            train_loss = [v / n for v in total_train_loss]
+        else:
+            train_loss = total_train_loss / n
     budget -= time.time() - start_time
     if val_loss < best_val_loss and budget > budget_per_train:
         estimator.cleanup()

test/test_automl.py

@@ -153,8 +153,8 @@ class TestAutoML(unittest.TestCase):
         X_train, y_train = load_iris(return_X_y=True)
         automl_experiment = AutoML()
         automl_settings = {
-            "time_budget": 10,
-            'eval_method': 'holdout',
+            "time_budget": 5,
+            'eval_method': 'cv',
             "metric": custom_metric,
             "task": 'classification',
             "log_file_name": "test/iris_custom.log",