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Pytorch framework for Arm NN (CMSIS)

I'm a graduate student at IUPUI. I am working with pruning of Squeezenext architecture for my thesis. So I want to deploy my model on a Cortex-M. I am using Pytorch framework. So could anyone help me in using CMSIS with Pytorch?

Thanks in Advance!!!

Parents
  • In these years, deep learning models have become popular in the real-time embedded application, but there are many complexities for hardware deployment as of few resources such as memory, energy and  computational power. Recent research in the field of deep learning focuses on reducing the model size of  CNN by various compression techniques like  Pruning, Architectural compression,and Quantization.

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  • In these years, deep learning models have become popular in the real-time embedded application, but there are many complexities for hardware deployment as of few resources such as memory, energy and  computational power. Recent research in the field of deep learning focuses on reducing the model size of  CNN by various compression techniques like  Pruning, Architectural compression,and Quantization.

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