我的session应该是正常的呀
x = tf.compat.v1.placeholder('float', [None, 784])
sess = tf.Session()
#取出线性回归方法
with tf.variable_scope('regression'):
y1, variables = model.regression(x)
saver = tf.train.Saver(variables)
saver.restore(sess, 'mnist/data/regression.ckpt')
#取出训练好的卷积的模型
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)
#定义输入 线性
def regression(input):
return sess.run(y1, feed_dict={x: input}).flatten().tolist()
#定义输入 卷积
def convolutional(input):
return sess.run(y2, feed_dict={x: input, keep_prob: 1.0}).flatten().tolist()