facebookresearch / Mask-Predict
A masked language modeling objective to train a model to predict any subset of the target words, conditioned on both the input text and a partially masked target translation.
Summary
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| Main Code: 13,466 LOC (146 files) = PY (98%) + CPP (<1%) + LUA (<1%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 44 LOC (1); Other: 60 LOC (3); |
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| Duplication: 21% | |||
| File Size: 0% long (>1000 LOC), 62% short (<= 200 LOC) | |||
| Unit Size: 9% long (>100 LOC), 47% short (<= 10 LOC) | |||
| Conditional Complexity: 12% complex (McCabe index > 50), 56% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (13 components) | ||
| Goals: Keep the system simple and easy to change (4) | |||
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Features of interest:
TODOs
6 files |
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Reports
Analysis Report
Source Code Overview
Analysis Report
Components
Analysis Report
Duplication
Analysis Report
File Size
Analysis Report
Unit Size
Analysis Report
Conditional Complexity
Analysis Report
Features of Interest
Analysis Report
All Metrics
Analysis Report
Goals & Controls
Analysis Report
File Age
Analysis Report
File Change Frequency
Analysis Report
Temporal Dependencies
Analysis Report
Contributors
Analysis Report
Trend
Analysis Report
Notes & Findings
sokrates.dev updated: 2022-01-25