I need to calculate standard deviation, mean and max of the training data for normalization. Now I need to use these values calculated on training data also for predicting later. (Which is a separate script that loads the model weights). How should I transfer these values? Is it possible to include them in the saved model somehow?

Also a question regarding the calculation of standard deviation: My data consists of several matrices, each are in separate file. I load the data with a class derived from torch.utils.data.Dataset. The **init** function stores the name of the files and **getitem** opens each file, reads the data and returns the tensor, so not all matrices are loaded into memory at the same time. But this also means I cannot calculate standard deviation without seeing all the data. So I open all files one more time before the above is done to calculate std. Is there a better way?