[Feature] Add generation-stamped replay slots for round-robin writer - #4046
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[Feature] Add generation-stamped replay slots for round-robin writer#4046harryfrzz wants to merge 9 commits into
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/rl/4046
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Description
Adds generation-stamped slots to the round-robin replay writer (step 1 of the
work in #4041). Every physical storage slot carries an int64 generation counter:
the first write of a slot has generation 0 and every reuse increments it, so a
sampled
(index, generation)pair identifies a specific record and becomesdetectably stale once its slot is reused.
writer.generations_of(index)and thetracks_generationscapability flag.Writers that do not track reuse report
-1.sample(return_info=True)returns an"index_generation"entry aligned with"index", read under the sampling lock;TensorDictbuffers surface it as asample key.
empty()is monotonic: previously handed-out(index, generation)handles arenever revived.
state_dict/load_state_dictanddumps/loads; oldercheckpoints still load. Lazy (unbounded) storages grow the counter dynamically.
The conditional priority-update API that consumes these stamps is submitted
separately. Cross-process visibility of stamps for
share()-d buffers is notyet supported and is deferred to a follow-up.
Motivation and Context
With a round-robin writer a slot can be overwritten while a learner computes a
loss, so a delayed priority update may apply a TD-error to a different record
that now occupies the same slot. Stamping each index with a generation lets
callers detect that reuse. This PR adds the generation-tracking and sampling
side.
Part of #4041.
Types of changes
Checklist