"""
Created on Tue Jul 10 20:33:30 2018
@author: muli
"""
from keras.preprocessing import sequence
from keras.models import Sequential
from keras.layers import Dense, Embedding
from keras.layers import LSTM
from keras.datasets import imdb
max_features = 20000
maxlen = 80
batch_size = 32
(trainX, trainY), (testX, testY) = imdb.load_data(num_words=max_features)
print(len(trainX), 'train sequences')
print(len(testX), 'test sequences')
trainX = sequence.pad_sequences(trainX, maxlen=maxlen)
testX = sequence.pad_sequences(testX, maxlen=maxlen)
print('trainX shape:', trainX.shape)
print('testX shape:', testX.shape)
model = Sequential()
model.add(Embedding(max_features, 128))
model.add(LSTM(128, dropout=0.2, recurrent_dropout=0.2))
model.add(Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy',
optimizer='adam',
metrics=['accuracy'])
model.fit(trainX, trainY,
batch_size=batch_size,
epochs=5,
validation_data=(testX, testY))
score = model.evaluate(testX, testY, batch_size=batch_size)
print('Test loss:', score[0])
print('Test accuracy:', score[1])