text_plain_output_1.png
from keras.layers import Dense, Input, CuDNNLSTM, Embedding, Dropout, Activation, CuDNNGRU, Conv1D

from keras.layers import LSTM

from keras.models import Sequential

embed_size = 100
max_features = 100000
maxlen = 1400

model = Sequential()
model.add(Embedding(max_features, embed_size, input_length=maxlen))
model.add(LSTM(256))
model.add(Dense(4, activation='softmax'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
print(model.summary())