tlkh/tf-metal-experiments
TensorFlow Metal Backend on Apple Silicon Experiments (just for fun)
This project helps machine learning engineers and researchers evaluate the performance of common deep learning models on Apple Silicon (M1 series) Macs. It takes various image classification and natural language processing models as input and outputs their training throughput, power consumption, and memory usage. This is for those who want to understand the practical limits and capabilities of their Apple Silicon hardware for deep learning tasks.
280 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher looking to benchmark the real-world performance of popular deep learning models like ResNet, MobileNet, or BERT on your M1, M1 Max, or M1 Ultra Mac.
Not ideal if you are a developer looking for a production-ready TensorFlow Metal integration or if you need to benchmark models that are not included in these experiments.
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280
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31
Language
Jupyter Notebook
License
MIT
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Last pushed
Feb 10, 2022
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