Time series forecast

In this link, the author show a tutoria for time series forecast Time series forecasting  |  TensorFlow Core. The questions are related to the normalization. The author subtracted and divided the validation data (val_df) and test data (test_df) using the train mean values and train standard deviation? (see below)
val_df = (val_df - train_mean) / train_std
test_df = (test_df - train_mean) / train_std
As far as I know for MLP, RNN and most of the ANN we need values between 0 and 1 and -1 and 1. Why did the author considered traning data for validation and test data in order to normalize them? We will not get values according to ANN requirements. Another question and more important is: How can I access the labes of the test data to compare with the predicted data? I have only access to the example inputs or example labels through wide_window.train/val or test. How to access all labels from the test data? I would like to see further charts and not the one is plotted using the plot function with normalized data. I would like to see real temperatura data for instance.