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fix: avoid int32 overflow in random seed generation - #253
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np.random.randint(0, 2**32 - 1) uses numpy's default integer dtype, which is int32 on some platforms (notably Windows). The high bound 2**32 - 1 exceeds int32's max, so numpy raises 'ValueError: high is out of bounds for int32' on every seed=-1 (auto-seed) generation. Line 36 already fixes this with dtype=np.uint32; apply the same fix to the two remaining occurrences (lines 198 and 468). Fixes Stability-AI#195
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- gradio 6.3.0 -> 6.16.0 (upstream PR Stability-AI#270); lock also updates gradio-client, starlette and adds hf-gradio - generation.py: np.random.randint(0, 2**32 - 1) overflows int32 on Windows when seed is -1; use dtype=np.uint32 as line 36 already does (upstream PR Stability-AI#253) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Fixes #195
Problem
Three call sites generate a random seed with:
np.random.randintuses numpy's default integer dtype, which is int32 on some platforms (notably Windows). The high bound2**32 - 1exceeds int32's max (2**31 - 1), so numpy raises:on every auto-seed (
seed == -1) generation.Fix
Line 36 already handles this correctly with
dtype=np.uint32. This applies the maintainers' own fix to the two remaining occurrences (lines 198 and 468), so all three seed sites are consistent.Verifiable by inspection — mirrors the existing fix on line 36.
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