facebookresearch / agem
Official implementation of the Averaged Gradient Episodic Memory (A-GEM) in Tensorflow
Summary
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| Main Code: 5,206 LOC (14 files) = PY (100%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 153 LOC (3); Other: 83 LOC (3); |
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| Duplication: 57% | |||
| File Size: 0% long (>1000 LOC), 3% short (<= 200 LOC) | |||
| Unit Size: 49% long (>100 LOC), 10% short (<= 10 LOC) | |||
| Conditional Complexity: 51% complex (McCabe index > 50), 22% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (3 components) | ||
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3 years, 7 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
7 files |
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Latest commit date: 2019-02-28
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