PyTorch on AWS
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PyTorch
PyTorch has a unique way of building neural networks: using and replaying a tape recorder.
Most frameworks such as TensorFlow, Theano, Caffe and CNTK have a static view of the world. One has to build a neural network, and reuse the same structure again and again. Changing the way the network behaves means that one has to start from scratch.
PyTorch uses a technique called Reverse-mode auto-differentiation, which allows you to change the way your network behaves arbitrarily with zero lag or overhead. Our inspiration comes from several research papers on this topic, as well as current and past work such as autograd, autograd, Chainer, etc.
Get started using PyTorch on AWS by launching an AWS Deep Learning AMI.
PyTorch Facts:
- PyTorch supports Tensor computation (like numpy) with strong GPU acceleration
- But it also supports, Deep Neural Networks built on a tape-based autograd system
- PyTorch was released in 2016
- PyTorch was primarily developed by Facebook's AI research group and Uber's "Pyro" software group
For more information on PyTorch, visit the official website by clicking here
