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pepijn223
a594ad7969
The smolvla branch had modified the shared pi0/pi05 modeling + pi05 config to support pi052 (SDPA attention, layernorm/lm_head handling, optimizer foreach/fused/lm_head_lr_scale, embedding scaling). Decouple pi052 instead: - Vendor the PI0.5 backbone (PaliGemmaWithExpertModel, PI05Pytorch, helpers) into pi052/pi05_backbone.py (verbatim copy, no PI05Policy). - Flatten PI052Policy to subclass PreTrainedPolicy directly (no longer PI05Policy); inline the needed PI05Policy methods. - Restore optimizer_foreach/fused + get_optimizer_preset on PI052Config. - Revert pi0, pi0_fast, pi05 modeling and configuration_pi05 to origin/main (byte-identical), so the shared policies carry no smolvla modifications. Behavior verified bit-exact on pepijn223/pi052_robocasa_full: embed_language_ tokens, predict_action_chunk, and the fused flow+text+FAST training loss are identical before/after (max_abs_diff=0). pi052 tests pass (pre-existing stale-name collection errors unchanged). Co-authored-by: Cursor <cursoragent@cursor.com>