TFLite Support is a toolkit that helps users to develop ML and deploy TFLite models onto mobile / ioT devices.
Role in this project:
Backend & DevOps Engineer Contributions:5 releases, 15 reviews, 120 commits in 1 year 4 months
Contributions summary:Shi primarily focused on setting up and configuring build systems and dependencies for the TensorFlow Lite Support repository. This included adding third-party tools for Java and Android builds, creating a CI helper script, and integrating Task library artifacts into the CI build process. Furthermore, the user was responsible for cleaning up the build, including updating dependencies, and improving the wheel build process.
iot-devicemachine-learningmobiletflite
Role in this project:
QA Engineer / Test Automation Engineer Contributions:10 commits in 1 year 8 months
Contributions summary:Shi primarily contributed to adding and updating golden tests within the repository. Their work focused on ensuring the accuracy of image classification and object detection applications within the TensorFlow examples. The commits involved modifying test code, loading images, and comparing results against expected values, demonstrating expertise in automated testing methodologies and the validation of machine-learning models.
tensorflow