Role in this project:
ML Engineer Contributions:11 commits, 3 PRs, 5 pushes in 3 years 2 months
Contributions summary:Michael primarily contributed to model training and evaluation, specifically for the MnasNet, EfficientNet, and ResNet models, all within the context of TPUs. They made changes related to quantization during training, including adding fake quantization ops and enabling post-quantization. Furthermore, they were involved in integrating moving average variables and managing checkpoints for model export and initialization. The user also updated Keras colab notebooks.