Manipulating the encoder state in a multi-layer bidirectional model with an attention mechanism involves extracting and transforming hidden states before passing them to the decoder.
Here is the code snippet you can refer to:

In the above code, we are using the following key points:
- Uses a bidirectional LSTM encoder.
- Extracts and concatenates forward & backward final hidden states.
- Prepares the manipulated hidden state for downstream tasks.
Hence, encoder state manipulation optimizes context retention and enhances attention-based decoding.