facebookresearch / moco
PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722
Summary
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| Main Code: 898 LOC (12 files) = PY (92%) + YAML (7%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 0 LOC (0); Other: 170 LOC (2); |
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| Duplication: 48% | |||
| File Size: 0% long (>1000 LOC), 26% short (<= 200 LOC) | |||
| Unit Size: 39% long (>100 LOC), 38% short (<= 10 LOC) | |||
| Conditional Complexity: 39% complex (McCabe index > 50), 43% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (4 components) | ||
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1 year, 10 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) | |||
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Features of interest:
TODOs
1 file |
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Latest commit date: 2020-08-20
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