
Worked on stabilizing time-based checkpointing in the ecmwf/anemoi-core repository to enhance training reliability for long-running machine learning experiments. Addressed a bug where checkpointing based on elapsed time failed to trigger by ensuring the timer was correctly initialized in the on_train_start method, resolving an issue caused by an overridden method that omitted a necessary call to its superclass. This fix, implemented using Python and leveraging skills in software debugging and unit testing, restored reliable checkpointing without affecting epoch- or step-based mechanisms. The change improved recoverability and reproducibility for multi-GPU training runs, directly aligning with tracked issues and pull requests.
Month: 2026-05 — Focused on stabilizing time-based checkpointing in ecmwf/anemoi-core to improve training reliability for long-running runs. Implemented a bug fix to ensure time-based checkpointing (every_n_minutes) fires during training by correctly initializing the timer in on_train_start. The root cause was an override of on_train_start that did not call super(), leaving _last_time_checked uninitialized. The change does not affect epoch- or step-based checkpointing. Impact and business value: restores reliable checkpointing, reducing risk of silent checkpoint gaps, improving recoverability and reproducibility in long-running experiments; aligns with issue #952 and PR #1116; supports multi-GPU validation where applicable.
Month: 2026-05 — Focused on stabilizing time-based checkpointing in ecmwf/anemoi-core to improve training reliability for long-running runs. Implemented a bug fix to ensure time-based checkpointing (every_n_minutes) fires during training by correctly initializing the timer in on_train_start. The root cause was an override of on_train_start that did not call super(), leaving _last_time_checked uninitialized. The change does not affect epoch- or step-based checkpointing. Impact and business value: restores reliable checkpointing, reducing risk of silent checkpoint gaps, improving recoverability and reproducibility in long-running experiments; aligns with issue #952 and PR #1116; supports multi-GPU validation where applicable.

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