apache/incubator-wayang
Jan 2025 – Jun 2025
4 Months active
Languages Used
JavaScalaPython
Technical Skills
JavaMachine LearningTensorFlowTestingAPI DevelopmentData Pipelines
composer
PROFILE
Composer
Contributed to apache/incubator-wayang by building and enhancing deep learning capabilities, focusing on neural network operations and robust TensorFlow integration. Developed Scala-like APIs and expanded the neural network framework to support advanced layers such as ConvLSTM2D and BatchNorm3D, enabling more complex model architectures and smoother deployment. Improved model conversion logic and dynamic shape inference, facilitating reliable production workflows and faster experimentation. Addressed backend stability and API correctness, reducing test flakiness and clarifying input handling. Leveraged Java, Scala, and TensorFlow to deliver features that broadened model support, improved integration testing, and strengthened the foundation for scalable machine learning pipelines within the project.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
11Total
Bugs
1
Commits
11
Features
4
Lines of code
3,073
Activity Months4
Your Network
22 peopleShared Repositories
22
Work History
June 2025
7 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for apache/incubator-wayang: Delivered significant neural network framework enhancements and TensorFlow backend fixes, reinforcing model correctness, stability, and production readiness across the project.
7 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for apache/incubator-wayang: Delivered significant neural network framework enhancements and TensorFlow backend fixes, reinforcing model correctness, stability, and production readiness across the project.
June 2025
May 2025
1 Commits • 1 Features
May 1, 2025Month: 2025-05 — Delivered neural network operation suite and TensorFlow conversion enhancements in apache/incubator-wayang. Added neural network operations ConvLSTM2D, BatchNorm2D, Conv2D, Conv3D, and MSELoss, and updated TensorFlow model conversion logic to support these operations, enabling more complex architectures and smoother deployment paths. A ConvLSTM for demo commit demonstrates end-to-end viability and sets foundation for production-ready features.
May 2025
1 Commits • 1 Features
May 1, 2025Month: 2025-05 — Delivered neural network operation suite and TensorFlow conversion enhancements in apache/incubator-wayang. Added neural network operations ConvLSTM2D, BatchNorm2D, Conv2D, Conv3D, and MSELoss, and updated TensorFlow model conversion logic to support these operations, enabling more complex architectures and smoother deployment paths. A ConvLSTM for demo commit demonstrates end-to-end viability and sets foundation for production-ready features.
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025: Delivered Scala-like Deep Learning API and DataQuanta/DataQuantaBuilder support to enable training and prediction workflows within Wayang, complemented by an end-to-end TensorFlow Iris pipeline validated through an integration test. No major bugs fixed this month. These efforts establish DL workload capability in Wayang, strengthening testing coverage and laying a foundation for broader DL adoption.
2 Commits • 1 Features
Mar 1, 2025March 2025: Delivered Scala-like Deep Learning API and DataQuanta/DataQuantaBuilder support to enable training and prediction workflows within Wayang, complemented by an end-to-end TensorFlow Iris pipeline validated through an integration test. No major bugs fixed this month. These efforts establish DL workload capability in Wayang, strengthening testing coverage and laying a foundation for broader DL adoption.
March 2025
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 (apache/incubator-wayang): Focused on upgrading ML dependencies and strengthening test coverage for TensorFlow integration to improve reliability and enable smoother experimentation in production deployments.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 (apache/incubator-wayang): Focused on upgrading ML dependencies and strengthening test coverage for TensorFlow integration to improve reliability and enable smoother experimentation in production deployments.
Activity
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Quality Metrics
Correctness81.0%
Maintainability80.0%
Architecture76.4%
Performance69.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaPythonScala
Technical Skills
API DevelopmentData PipelinesDeep LearningDeep Learning IntegrationDeep Learning OperationsIntegration TestingJSON ParsingJavaJava DevelopmentMachine LearningModel DefinitionModel DeploymentModel DevelopmentScalaTensorFlow
Repositories Contributed To
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