Implement an Encoder and Decoder architecture with attention mechanism

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With the help of code can you Implement an Encoder and Decoder architecture with attention mechanism
Mar 12 in Generative AI by Ashutosh
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1 answer to this question.

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To implement an Encoder-Decoder architecture with an attention mechanism, use an LSTM-based encoder to process input sequences and an attention-enhanced decoder

Here is the code snippet you can refer to:

In the above code we are using the following key points:

  • Uses LSTM Encoder to process sequential input data.
  • Integrates an Attention Mechanism to focus on relevant encoder outputs.
  • Uses LSTM Decoder with initial states from the encoder.
  • Concatenates Context Vector with Decoder Output before final classification.
  • Employs Dense Layers for Prediction in a sequence-to-sequence task.
Hence, incorporating attention in an Encoder-Decoder architecture enhances sequence modeling by dynamically focusing on important encoder representations during decoding.
answered Mar 17 by anushka

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