facebookresearch / LearningToLearn

Collection of algorithms to learn loss and reward functions via gradient-based bi-level optimization.

Summary
URDF
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Main Code: 2,089 LOC (26 files) = PY (81%) + URDF (18%)
Secondary code: Test: 38 LOC (1); Generated: 0 LOC (0); Build & Deploy: 0 LOC (0); Other: 154 LOC (7);
Artboard 48 Duplication: 10%
File Size: 0% long (>1000 LOC), 59% short (<= 200 LOC)
Unit Size: 0% long (>100 LOC), 65% short (<= 10 LOC)
Conditional Complexity: 0% complex (McCabe index > 50), 76% simple (McCabe index <= 5)
Logical Component Decomposition: primary (8 components)
files_time

1 year, 1 month old

  • 100% of code older than 365 days
  • 54% of code not updated in the past 365 days

0% of code updated more than 50 times

Also see temporal dependencies for files frequently changed in same commits.
Goals: Keep the system simple and easy to change (4)
Straight_Line
Features of interest:
TODOs
1 file
Commits Trend

Latest commit date: 2021-07-23

0
commits
(30 days)
0
contributors
(30 days)
Commits

12

1
Contributors

3

1
2021 2020
show commits trend per language
Reports
Analysis Report
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Source Code Overview
Analysis Report
Components
Analysis Report
Artboard 48
Duplication
Analysis Report
File Size
Analysis Report
files_time
File Age
Analysis Report
File Change Frequency
Analysis Report
Temporal Dependencies
Analysis Report
Commits & Contributors
Analysis Report
Unit Size
Analysis Report
Conditional Complexity
Analysis Report
Straight_Line
Features of Interest
Analysis Report
All Metrics
Analysis Report
Goals & Controls
Analysis Report
Trend
Analysis Report
76_startup_sticky_notes
Notes & Findings
Links

generated by sokrates.dev (configuration) on 2022-01-25