facebookresearch / habitat-lab
A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators.
Summary
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| Main Code: 23,142 LOC (190 files) = PY (92%) + YAML (6%) + CFG (<1%) + TOML (<1%) + IN (<1%) Secondary code: Test: 3,544 LOC (37); Generated: 0 LOC (0); Build & Deploy: 76 LOC (3); Other: 2,068 LOC (21); |
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| Duplication: 11% | |||
| File Size: 0% long (>1000 LOC), 35% short (<= 200 LOC) | |||
| Unit Size: 5% long (>100 LOC), 63% short (<= 10 LOC) | |||
| Conditional Complexity: <1% complex (McCabe index > 50), 76% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (21 components) | ||
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2 years, 9 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
12 files |
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Latest commit date: 2022-01-12
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5
commits
(30 days)
2
contributors
(30 days) |
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