OpenHUTB/nn
Apr 2026 – Apr 2026
1 Month active
Languages Used
Python
Technical Skills
Data VisualizationDeep LearningMachine LearningPyTorchPythonReinforcement Learning
wengqiuyi
PROFILE
Wengqiuyi
During this period, work focused on adapting the CarRacing-v3 environment to Gymnasium v2 within the OpenHUTB/nn repository, restoring its operability and addressing compatibility issues. The developer optimized DQN and DoubleDQN implementations by refining tensor construction and Q-value indexing, which reduced computational overhead and improved training stability. Enhancements to sampling and inference paths, along with disabling rendering by default, accelerated experiment workflows. Additional improvements included introducing command-line options, new metrics, and smoother comparison plots for monitoring training progress. All updates were implemented using Python and PyTorch, with a strong emphasis on deep reinforcement learning and data visualization techniques.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
792
Activity Months1
Your Network
263 peopleWork History
April 2026
3 Commits • 1 Features
Apr 1, 2026Month: 2026-04 | Repository: OpenHUTB/nn. This period centers on delivering a robust CarRacing setup under Gymnasium v2, boosting DQN/DoubleDQN performance, and improving training workflow and observability to drive faster, more reproducible experiments.
3 Commits • 1 Features
Apr 1, 2026Month: 2026-04 | Repository: OpenHUTB/nn. This period centers on delivering a robust CarRacing setup under Gymnasium v2, boosting DQN/DoubleDQN performance, and improving training workflow and observability to drive faster, more reproducible experiments.
April 2026
Activity
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Quality Metrics
Correctness86.6%
Maintainability80.0%
Architecture80.0%
Performance86.6%
AI Usage53.4%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data VisualizationDeep LearningMachine LearningPyTorchPythonReinforcement Learningdeep learningmachine learningreinforcement learning
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