Freezing a saved tensorflow model
When you save a model, it is done i.e. it is frozen. Its weight won't change. Usually, during testing, you will instantiate your model and then load the saved i.e. frozen model and run predictions on it.
If you don't want the network to learn after you load your frozen model weights, then, go to model.layers and set the trainable false for every layer.
model.load_weights(checkpoint_path) is used for loading weights.
I was able to train a model with the python TensorFlow API following some tutorials. 
I also managed to freeze the model from the latest checkpoints.
However, I wanted to have the best instead of the latest model, so I checked to get the best models written to the disc. At last, I found it in a "saved model" format and now I want to convert it to a frozen model. I think this should be something straight forward. 
It might be a stupid question but I already spent some hours looking for a simple way.
Your help would be much appreciated!