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Neural Machine Translation

TensorFlow 2.0 implementation of the popular NLP paper by Bahdanau et al. - Neural Machine Translation by Jointly Learning to Align and Translate (ICLR, 2015)

Find the paper at https://arxiv.org/pdf/1409.0473.pdf

For detailed implementation with replicated results, use NMT_6400000

Following are the specifications followed as per the authors:

  • AdaDelta Optimizer with epsilon = 10-6 , rho = 0.95
  • Minibatch SGD with batch_size = 80
  • Embedding Dimension = 620
  • Hidden Layer Size = 1000
  • Output Layer Size = 500
  • Weights initialization = RandomNormal with Mean = 0 and Standard Deviation = 0.001
  • Bias initialization = Zeros
  • L2 Regularization

Total number of parameters = 28,332,000 (Encoder) + 3,003,001 (Attention) + 52,496,000 (Decoder) = 90,831,001

Use Presentation.pdf for a better understanding.

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Implementation of Bahdanau Attention

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