Fix: [BUG] Memory leak in loss backward when enabled torch activation check - #8690
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🟡 Changes recommended
Persistent and delegated counters can suppress parameter release, and the reported topology lacks regression coverage.
Review effort: Balanced
Findings: 1
Open (2)
What changed in this PR
Fixes ZeRO-3 parameter retention during backward for activation-checkpointed multi-branch models.
Changes:
- Preserves
ds_grads_remainingacross repeated module hooks. - Removes an unused alternate backward-hook implementation.
| File | Description |
|---|---|
deepspeed/runtime/zero/parameter_offload.py |
Revises post-backward reference counting and cleanup triggering. |
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| if not hasattr(module, 'ds_grads_remaining'): | ||
| module.ds_grads_remaining = 0 |
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| if not hasattr(module, 'ds_grads_remaining'): | ||
| module.ds_grads_remaining = 0 | ||
| module.ds_grads_remaining += 1 |
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This PR addresses #8481.
[BUG] Memory leak in loss backward when enabled torch activation checkpoint & zero3 & single-model-multi-branch network
Generated with AI assistance and validated against the original
file before submission (syntax check + change-scope check).
Please review carefully — happy to adjust based on feedback.