fix: add Apple Silicon MPS support for device detection#58
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The generate_hf function had hardcoded "cuda" device, causing AssertionError on non-NVIDIA systems. This change adds automatic device detection with the following priority: 1. TORCH_DEVICE setting (if configured) 2. model.device attribute (if available) 3. CUDA (if torch.cuda.is_available()) 4. MPS (if torch.backends.mps.is_available()) - Apple Silicon 5. CPU (fallback) This enables running chandra on Apple Silicon Macs with Metal acceleration via MPS backend. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <[email protected]>
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Hi! Just curious about the state of this fix, any plans to release it soonish? Thanks a lot! |
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Summary
"cuda"device ingenerate_hf()function that causedAssertionError: Torch not compiled with CUDA enabledon non-NVIDIA systemsTORCH_DEVICEsetting →model.device→ CUDA → MPS → CPUProblem
When running
chandra-appon macOS with Apple Silicon (M1/M2/M3), the following error occurs:This is because
hf.py:36has hardcodedinputs.to("cuda").Solution
Replace hardcoded device with automatic detection that respects:
TORCH_DEVICEsettingTest Plan
chandra-app🤖 Generated with Claude Code