NMT-Keras ÁlvaroPerisandCasacuberta[29] TensorFlow,Theano NeuralMonkey HelclandLibovický[30] TensorFlow THUMT Zhangetal.[31] TensorFlow,Theano Eske/Seq2Seq - TensorFlow XNMT Neubigetal.[32] DyNet NJUNMT - PyTorch,TensorFlow Transformer-DyNet - DyNet SGNMT Stahlbergetal.[33,34] TensorFlow,Theano CythonMT Wangetal.[35] C++ Neutron XuandLiu[36 ... Jul 08, 2018 · In PyTorch, tensors of LSTM hidden components have the following meaning of dimensions: First dimension is n_layers * directions, meaning that if we have a bi-directional network, then each layer will store two items in this direction. Second dimension is a batch dimension. Third dimension is a hidden vector itself.

The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch. View the Project on GitHub ritchieng/the-incredible-pytorch This is a curated list of tutorials, projects, libraries, videos, papers, books and anything related to the incredible PyTorch . Dec 21, 2020 · I am following NMT implementations in: Pytorch: NLP From Scratch: Translation with a Sequence to Sequence Network and Attention — PyTorch Tutorials 1.7.1 documentation Tensorflow: Neural machine translation with attention | TensorFlow Core I found a marked difference in the decoder implementation: In Tensorflow implementation, attention weights are calculated using hidden states (query) and ...

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