Collapse reference+learner hydra heads when using LoRa

🚀 The feature, motivation, and pitch

With additive (delta-style) parameter-efficient tuning methods such as LoRa, we should be able to make a slightly more mem-efficient hydra architecture by using a single block that does ~frozen_head + tunable_weights for the learner/policy head's fwd-pass and simply frozen_head for the reference, instead of maintaining 2x heads.

CC @LouisCastricato and @cat-state for pointing this out

Alternatives

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Additional context

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