This is an implementation of Bahdanau Attention

Just like you would use any other tensoflow.python.keras.layers object.

from attention_keras.layers.attention import AttentionLayer

attn_layer = AttentionLayer(name='attention_layer')
attn_out, attn_states = attn_layer([encoder_outputs, decoder_outputs])

Here,

• encoder_outputs - Sequence of encoder ouptputs returned by the RNN/LSTM/GRU (i.e. with return_sequences=True)
• decoder_outputs - The above for the decoder
• attn_out - Output context vector sequence for the decoder. This is to be concat with the output of decoder (refer model/nmt.py for more details)
• attn_states - Energy values if you like to generate the heat map of attention (refer train.ipynb for usage)