Feature/memory error sampling

[belerico]

Summary

In this PR we have fixed multiple problems related to the resuming from checkpoint functionality. In particular:

• when resuming from checkpoint the algo.learning_starts was read from the old config and if the buffer was not saved into the checkpoint then at the first training iteration the Ratio class, to keep with the replay-ratio after the algo.learning_starts steps, will output a huge number of per_rank_gradient_steps to be run on the first training iteration which could lead to OOM or to really slow training time
• now the user must specify the algo.learning_starts even when resuming from a checkpoint. Set algo.learning_starts=0 to disable the buffer pre-fill
• algo.learning_starts are not taken into consideration for the replay-ratio computation also when resuming from checkpoint
• updated checkpoint howto

Type of Change

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• Bug fix (non-breaking change that solves an issue)
• New feature (non-breaking change that adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• Documentation update
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