1.使用函數(shù)模型API，新建一個(gè)model，將輸入和輸出定義為原來(lái)的model的輸入和想要的那一層的輸出，然后重新進(jìn)行predict.
#coding=utf-8?
import seaborn as sbn?
import pylab as plt?
import theano?
from keras.models import Sequential?
from keras.layers import Dense,Activation?
from keras.models import Model?
model = Sequential()?
model.add(Dense(32, activation='relu', input_dim=100))?
model.add(Dense(16, activation='relu',name="Dense_1"))?
model.add(Dense(1, activation='sigmoid',name="Dense_2"))?
model.compile(optimizer='rmsprop',?
loss='binary_crossentropy',?
metrics=['accuracy'])?
# Generate dummy data?
import numpy as np?
#假設(shè)訓(xùn)練和測(cè)試使用同一組數(shù)據(jù)?
data = np.random.random((1000, 100))?
labels = np.random.randint(2, size=(1000, 1))?
# Train the model, iterating on the data in batches of 32 samples?
model.fit(data, labels, epochs=10, batch_size=32)?
#已有的model在load權(quán)重過(guò)后?
#取某一層的輸出為輸出新建為model，采用函數(shù)模型?
dense1_layer_model = Model(inputs=model.input,?
outputs=model.get_layer('Dense_1').output)?
#以這個(gè)model的預(yù)測(cè)值作為輸出?
dense1_output = dense1_layer_model.predict(data)?
print dense1_output.shape?
print dense1_output[0]? `
plt打印圖片無(wú)法顯示問(wèn)題。
import matplotlib.pyplotas plt
plt.imshow(img)
#控制臺(tái)打印出圖像對(duì)象的信息，而圖像沒(méi)有顯示
解決方法：
#引入pylab解決
import matplotlib.pyplotas plt
import pylab
plt.imshow(img)
pylab.show()
python matplotlib.pyplot 顯示中文title等參數(shù)
#?-*-?coding:?utf-8?-*??
import?matplotlib.pyplot?as?plt??
plt.rcParams['font.sans-serif']=['SimHei']?#用來(lái)正常顯示中文標(biāo)簽??
plt.rcParams['axes.unicode_minus']=False?#用來(lái)正常顯示負(fù)號(hào)??
plt.figure(1)??
plt.plot(x,?y)??
plt.xlabel(u'我是橫坐標(biāo)')??
plt.ylabel(u'我是縱坐標(biāo)')??
plt.show()??
參考文獻(xiàn)
https://blog.csdn.net/hahajinbu/article/details/77982721
https://blog.csdn.net/alickr/article/details/72804258
https://blog.csdn.net/renjunsong0/article/details/55057173
