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The user can now decide if to use the torch.as_tensor function or the torch.from_numpy one to convert the Numpy buffer into tensors when sampling (#172).
Added optimizations to reduce training time (#168).
Added the possibility to keep only the last n checkpoints in an experiment to avoid filling up the disk (#171).