代码为文本预测
import keras
import numpy as np
from tensorflow import optimizers
import tensorflow as tf
from keras.utils.data_utils import get_file
from tensorflow.python.client import session
path=get_file('nietzsche.txt',origin="https://s3.amazonaws.com/text-datasets/nietzsche.txt")
text=open(path).read().lower()
print('Corpus Length:',len(text))
maxlen=60
step=3
sentences=[]
next_chars=[]
for i in range(0,len(text)-maxlen,step):
sentences.append(text[i:i+maxlen])
next_chars.append(text[i+maxlen])
print('Number of sequences:',len(sentences))
chars=sorted(list(set(text)))
print('Unique characters:',len(chars))
char_indices=dict((char,chars.index(char))for char in chars)
print('Vectorization...')
x=np.zeros((len(sentences),maxlen,len(chars)),dtype=np.bool)
y=np.zeros((len(sentences),len(chars)),dtype=np.bool)
for i ,sentence in enumerate(sentences):
for t,char in enumerate(sentence):
x[i,t,char_indices[char]]=1
y[i,char_indices[next_chars[i]]]=1
from keras import layers
model=keras.models.Sequential()
model.add(layers.LSTM(128,input_shape=(maxlen,len(chars))))
model.add(layers.Dense(len(chars),activation='softmax'))
optimizer=optimizers.RMSprop(lr=0.01)
model.compile(loss='categorical_crossentropy',optimizer=optimizer)
def sample(preds,temperature=1.0):
preds=np.asarray(preds).astype('float64')
preds=np.log(preds)/temperature
exp_preds=np.exp(preds)
preds=exp_preds/np.sum(exp_preds)
probas=np.random.multinomial(1,preds,1)
return np.argmax(probas)
import random
import sys
for epoch in range(1,100):
print('epoch',epoch)
model.fit(x,y,batch_size=128,epochs=1)
start_index=random.randint(0,len(text)-maxlen-1)
generated_text=text[start_index:start_index+maxlen]
print('-----Generating with seed:"'+generated_text+'"')
for temperature in [0.2,0.5,1.0,1.2]:
print('--------temperature: ',temperature)
sys.stdout.write(generated_text)
for i in range(400):
sampled=np.zeros((1,maxlen,len(chars)))
for t,char in enumerate(generated_text):
sampled[0,t,char_indices[char]]=1
preds=model.predict(sampled,verbose=0)[0]
next_index=sample(preds,temperature)
next_char=chars[next_index]
generated_text+=next_char
generated_text=generated_text[1:]
sys.stdout.write(next_char)
