sayakpaul/keras-xla-benchmarks
Presents comprehensive benchmarks of XLA-compatible pre-trained models in Keras.
This project offers insights into how different pre-trained computer vision models perform on various GPUs when XLA (Accelerated Linear Algebra) is enabled. It takes a list of Keras vision models and different image resolutions, then measures their throughput (images processed per second). The results help machine learning engineers, MLOps specialists, and researchers choose the most efficient models and hardware for image-related tasks.
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Use this if you are a machine learning practitioner looking to optimize the inference speed of your computer vision models using XLA on various GPU types.
Not ideal if you are looking for benchmarks on model accuracy or performance metrics beyond throughput, or if you are not working with Keras vision models.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Aug 27, 2023
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