facebookresearch / Opacus-lab
Research and experimental code related to Opacus, an open-source library for training PyTorch models with Differential Privacy
Summary
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| Main Code: 617 LOC (10 files) = PY (99%) + IN (<1%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 0 LOC (0); Other: 449 LOC (7); |
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| Duplication: 2% | |||
| File Size: 0% long (>1000 LOC), 100% short (<= 200 LOC) | |||
| Unit Size: 0% long (>100 LOC), 100% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 94% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (3 components) | ||
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5 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
Latest commit date: 2021-12-14
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