我的session應(yīng)該是正常的呀

x?=?tf.compat.v1.placeholder('float',?[None,?784])
sess?=?tf.Session()


#取出線性回歸方法
with?tf.variable_scope('regression'):
????y1,?variables?=?model.regression(x)

saver?=?tf.train.Saver(variables)
saver.restore(sess,?'mnist/data/regression.ckpt')

#取出訓(xùn)練好的卷積的模型
with?tf.variable_scope('convolutionoal'):
????keep_prob?=?tf.placeholder('float')
????y2,?variables?=?model.convolutional(x,?keep_prob)

saver?=?tf.train.Saver(variables)
#saver.restore(sess,?"mnist/data/convalutional.ckpt")
#tf.train.latest_checkpoint('mnist/data/convalutional.ckpt')
module_file?=??tf.train.latest_checkpoint('mnist/data/convolutional.ckpt')
with?tf.Session()?as?sess:
???sess.run(tf.global_variables_initializer())
???if?module_file?is?not?None:
??????saver.restore(sess,?module_file)

#定義輸入??線性
def?regression(input):
????return?sess.run(y1,?feed_dict={x:?input}).flatten().tolist()
#定義輸入???卷積
def?convolutional(input):
????return?sess.run(y2,?feed_dict={x:?input,?keep_prob:?1.0}).flatten().tolist()