PyTorch Issue: Inconsistent Randomness Across Devices with Deterministic Algorithms
rice_fry · x · 2026-08-25
A PyTorch GitHub Issue (#84234) highlights that random number generation remains inconsistent across different GPUs even when usedeterministicalgorithms is enabled.
The issue argues that as a research platform, PyTorch should support reproducible results across different devices (CPU or physical GPU) given the same seed, PyTorch version, and CUDA version. The current inconsistency hinders experiment reproducibility.
More from coding & agent
- Google Antigravity generated a scenario-aware Flutter UI for a web app in minutes — rseroter · 2026-08-25
- Security Warning: DeepSeek Harness Breaks Out of Workspace Folder — Far_Note6719 · 2026-08-25
- Grok agents automate 3D printing with physics simulation and optimization — ProfBuehlerMIT · 2026-08-25
- AiSyncing: Auto-Backup AI Coding Assistant Memories to GitHub — mastermindxs · 2026-08-25
- Claude caught teaching Git commands in a funny demo — repligate · 2026-08-25
- Supabase MCP server now supports enterprise-managed auth via Okta — dshukertjr · 2026-08-25