facebookresearch / d2go
D2Go is a toolkit for efficient deep learning
Summary
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| Main Code: 17,172 LOC (150 files) = PY (88%) + CUH (7%) + YAML (2%) + CU (<1%) + H (<1%) + CPP (<1%) | |||
| Duplication: 15% | |||
| File Size: 7% long (>1000 LOC), 46% short (<= 200 LOC) | |||
| Unit Size: 4% long (>100 LOC), 55% short (<= 10 LOC) | |||
| Conditional Complexity: 1% complex (McCabe index > 50), 69% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (14 components) | ||
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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
32 files |
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Latest commit date: 2022-01-20
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17
commits
(30 days)
7
contributors
(30 days) |
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