facebookresearch / dlrm
An implementation of a deep learning recommendation model (DLRM)
Summary
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| Main Code: 6,840 LOC (14 files) = PY (100%) Secondary code: Test: 27 LOC (1); Generated: 0 LOC (0); Build & Deploy: 146 LOC (4); Other: 360 LOC (3); |
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| Duplication: 24% | |||
| File Size: 36% long (>1000 LOC), 4% short (<= 200 LOC) | |||
| Unit Size: 33% long (>100 LOC), 25% short (<= 10 LOC) | |||
| Conditional Complexity: 26% complex (McCabe index > 50), 38% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (5 components) | ||
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2 years, 7 months old
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19% 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: 2021-09-01
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(30 days)
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