How to add Bi directional LSTM layer to keras model?
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How to add Bi directional LSTM layer to keras model?

How to add Bi directional LSTM layer to keras model?

This recipe helps you add Bi directional LSTM layer to keras model

0

Recipe Objective

Adding Bi directional LSTM layer to keras model

Bi-directional LSTMs is an extension of LSTM, can improve the working of the model on sequence classification problems.

Step 1- Importing Libraries

from keras.layers import Bidirectional from tensorflow import keras from keras.models import Sequential from keras.layers import LSTM from keras.layers import Activation, Dense import numpy as np

Step 2- Create a neural network model.

adding a Bidirectional layer.

model = Sequential() model.add(Bidirectional(LSTM(32, return_sequences=True), input_shape=(5, 10))) model.add(Bidirectional(LSTM(32))) model.add(Activation('relu')) model.compile(loss='categorical_crossentropy', optimizer='Adam')

Step-3 Create a sample model and make prediction from it.

y = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]).reshape((1,1,10)) # make and show prediction print(model.predict(y))
[[0.02718286 0.02762156 0.02089063 0.01052572 0.06378494 0.01932984
  0.         0.         0.06944765 0.01507997 0.         0.
  0.05792578 0.04587546 0.         0.01098552 0.04473235 0.06602424
  0.         0.         0.         0.01608978 0.         0.
  0.03304935 0.         0.05253785 0.04292118 0.10207159 0.07474144
  0.         0.01693208 0.06157123 0.02414081 0.05233147 0.03505142
  0.03542253 0.01108169 0.01113066 0.         0.         0.05232322
  0.         0.10277228 0.02966982 0.         0.         0.
  0.03759805 0.         0.         0.01015551 0.08046164 0.
  0.         0.00290035 0.         0.02540161 0.         0.
  0.05021353 0.         0.03642806 0.        ]]

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