提升长文识别的速度

NLP中，针对过长的文章，可以使用一维卷积+GRU来处理

from keras.models import Sequential 
from keras import layers 
from keras.optimizers import RMSprop 
 
model = Sequential() 
model.add(layers.Conv1D(32, 5, activation='relu', 
                        input_shape=(None, float_data.shape[-1]))) 
model.add(layers.MaxPooling1D(3)) 
model.add(layers.Conv1D(32, 5, activation='relu')) 
model.add(layers.GRU(32, dropout=0.1, recurrent_dropout=0.5)) 
model.add(layers.Dense(1)) 
 
model.summary() 
 
model.compile(optimizer=RMSprop(), loss='mae') 
history = model.fit_generator(train_gen, 
                              steps_per_epoch=500, 
                              epochs=20, 
                              validation_data=val_gen, 
                              validation_steps=val_steps)