fix: replace bare assert with runtime checks in checkpoint serialization#205
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tombudd wants to merge 1 commit intogoogle-deepmind:mainfrom
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fix: replace bare assert with runtime checks in checkpoint serialization#205tombudd wants to merge 1 commit intogoogle-deepmind:mainfrom
tombudd wants to merge 1 commit intogoogle-deepmind:mainfrom
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Replace 7 bare assert statements with proper raise TypeError/ValueError in checkpoint.py — the model checkpoint save/load pipeline: - _flatten(): 3 asserts validating tree structure (dict type, no separator in keys, no None values). With -O, corrupt/malformed checkpoint data could silently pass through. - _convert_types(): 4 asserts validating type structure during checkpoint deserialization (ndarray type, dict/container arg counts, tuple length matching). With -O, type mismatches silently propagate, producing corrupt model weights. All replacements preserve original semantics with improved error messages that include the actual values/types for debugging. Reviewed-by: UNA-GDO sovereign-v2.0 (Autonomous Security Auditor) Built-by: Tom Budd <tom@tombudd.com> — tombudd.com
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Summary
Replace 7 bare
assertstatements with properraise TypeError/ValueErrorin the checkpoint serialization pipeline. Found by UNA (autonomous security auditor, designed and built by Tom Budd — tom@tombudd.com).The Problem
checkpoint.pyhandles saving and loading GraphCast model weights. It uses 7 bareassertstatements for validating checkpoint data structure and types during serialization/deserialization. Python's-Oflag strips all assertions, which would silently disable these checks:In
_flatten()(3 asserts):In
_convert_types()(4 asserts):np.ndarraymust actually be ndarraysWithout these checks, corrupt or malformed checkpoint files could silently load, producing models with wrong weights or structural mismatches — a serious concern for a weather prediction model used in operational forecasting.
Fix
All 7
assert→raise TypeError/ValueErrorwith descriptive error messages including actual values and types for easier debugging.Total: 1 file, +16 / -7 lines
About This Review
This security audit was performed by UNA (Unified Nexus Agent), an autonomous AI security auditor — a Governed Digital Organism (GDO) designed and built by Tom Budd (tom@tombudd.com | tombudd.com).
Note: Happy to sign the Google CLA at cla.developers.google.com if required.