fsdp: materialize clip_grad_norm's DTensor before logging#35
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clip_grad_norm_ returns a lazily-reduced partial-norm DTensor; logging it without full_tensor() leaks the local shard's norm, under-reporting grad_norm by sqrt(n_shards) (2x on the dp4 recipe). Clipping itself was always correct — the coefficient is computed in DTensor arithmetic. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Partial revert of 0420f3b: that commit also carried the dp_mesh -> fsdp_mesh line (folded in during a rebase), which belongs to the SP placement and stays. Only the DTensor import and the full_tensor materialization leave; they land independently as #35, which this PR's cross-placement grad_norm comparisons depend on. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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clip_grad_norm_on DTensor parameters returns a lazily-reduced partial norm; the logging path (.detach()→.mean().item()) leaked the local shard's value, under-reporting thetrain/grad_normmetric by ×√(n_shards) on every FSDP config (historical dp4 wandb curves are ×2 too low). Clipping itself was always correct — the clip coefficient is computed inside DTensor arithmetic — only the logged metric was wrong.Fix:
.full_tensor()before logging.Found while cross-validating the two SP parameter placements in #21 (different shard counts → reported norms differed by √2 while instrumented per-param grads were bitwise identical). #21's validation claims depend on this landing first.
Expect wandb
grad_normcurves to step up (×2 on the dp4 recipe) after this merges — historical values were under-reported, not the new ones inflated.