facebookresearch / poincare-embeddings
PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
Summary
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| Main Code: 1,546 LOC (24 files) = PY (73%) + PYX (24%) + YML (1%) + PYI (<1%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 56 LOC (2); Other: 131 LOC (3); |
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| Duplication: 6% | |||
| File Size: 0% long (>1000 LOC), 86% short (<= 200 LOC) | |||
| Unit Size: 13% long (>100 LOC), 60% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 65% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (4 components) | ||
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3 years, 11 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: 2021-09-16
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