[D] how to make my training faster ?

I work with dna sequences as input to my deep learning model, I save them as one hot encoded numpy array in h5 file. My dataset has 700k examples and 500Go in size. I wanted to make training faster so I have a bunch of questions :

- is it better to store them as 1d arrays (numerical instead of one hot encoding) in h5 file then transform them to one hot encoded arrays during loading would this make things …

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