model.py

from keras.layers import *
from keras.models import *
from utils import max_len, max_words


def get_model():
    model = Sequential()
    model.add(Embedding(max_words, 128))
    model.add(GRU(128))
    model.add(Dense(1, activation='sigmoid'))
    
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    return model