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Make Adafactor relative-step constants configurable - #549
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shaneraphel wants to merge 3 commits into
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shaneraphel wants to merge 3 commits into
shaneraphel wants to merge 3 commits into
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get_trace averaged the Hessian diagonal over the spatial dims only for 4D kernels. Conv1d (3D) and Conv3d (5D) weights left tmp_output unbound. Average over dims 2..ndim-1 instead; 4D is unchanged.
Each mode factor of an order-k tensor enters to the power -1/(2k): -1/4 per side for matrices. The code used -1/k, twice the published exponent. The 7 pre-existing test_optimizer Shampoo failures are a state-dict precision issue on this torch version and fail identically without this change.
warmup_rate (default 1e-6) replaces the hard-coded warm-up slope and min_step_size (default 1e-2) the floor. Old checkpoints without the new group keys fall back to the old values. The 7 pre-existing test_optimizer Adafactor failures are a state-dict precision issue on this torch version and fail identically without this change.
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Summary
_get_lrhard-coded the warm-up slope (1e-6) and the non-warmup floor (1e-2). They are nowwarmup_rate(default1e-6) andmin_step_size(default1e-2). Defaults reproduce the old schedule exactly; groups saved before these keys existed fall back to the old values instead of raisingKeyError. Negative values are rejected.Fixes #535.
Test plan
pytest tests/test_adafactor_step_size.py: 6 passed (defaults match the old formula, custom values take effect, old checkpoint keys, validation, end-to-end step)tests/test_optimizer.py -k Adafactorhas 7 failures that exist without this change (state-dict precision on this torch version)