mlflow first try

nn_train_mlflow.py

@@ -68,7 +68,7 @@ with mlflow.start_run():
     model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy', 'categorical_accuracy'])
     model.fit(x_train_set, dummy_y, epochs=epoch, validation_data=(x_validate_set, dummy_yv))
     
-    model.save("my_model/")
+    #model.save("my_model/")
 
     
     #model predictions
@@ -82,7 +82,7 @@ with mlflow.start_run():
     mlflow.log_param("epoch", epoch)
     mlflow.log_param("1st_activation_funct", first_activation_funct)
     mlflow.log_param("2nd_activation_funct", second_activation_funct)
-    mlflow.keras.log_model(model, 'my_model')
+    #mlflow.keras.log_model(model, 'my_model')
     mlflow.keras.save_model(model, "my_model")
     mlflow.log_metric("accuracy", accuracy_score(y_true, y_pred))