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Episode iterator upgrades #216
Episode iterator upgrades #216
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Question here: would it be switching to frequently at the later stage of training? with potentially less than 100 episode per scene switch? Will it help to incorporate both count schemes, like a logical AND?
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Shuffling on steps is consistent from an optimization standpoint, you swap scenes every N parameters updates, which is why I like it :)
I don't think you can switch scenes "too often". Ideally, we'd just randomly sample a new episode irrespective of the scene it is in, but this incurs the non-trivial cost of swapping the scene way too often.
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While
self.episode_iterator
mentioned as Optional I don't see Env functioning without it here. Maybe check for subclass ofEpisodeIterator
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A separate PR probably makes sense for changing that functionality (dataset is also marked as optional).