Deep learning frameworks like TensorFlow, PyTorch, Caffe, MXNet, and Chainer have reduced the effort and skills needed to train and use deep learning models.
The Apache MXNet community earlier this month introduced version 0.12 of MXNet, which extends Gluon functionality to allow for new, cutting-edge research, according to AWS.
HE-Transformer effectively adds an abstraction layer that can be applied to neural networks on open source frameworks such as Google's TensorFlow, Facebook's PyTorch, and MXNet.
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