官方tutorial是这么说的:
The only difference with a regular Session is that an InteractiveSession installs itself as the default session on construction. The methods Tensor.eval() and Operation.run() will use that session to run ops.
翻译一下就是:tf.InteractiveSession()是一种交互式的session方式,它让自己成为了默认的session,也就是说用户在不需要指明用哪个session运行的情况下,就可以运行起来,这就是默认的好处。这样的话就是run()和eval()函数可以不指明session啦。
对比一下:
import tensorflow as tf
import numpy as np
a=tf.constant([[1., 2., 3.],[4., 5., 6.]])
b=np.float32(np.random.randn(3,2))
c=tf.matmul(a,b)
init=tf.global_variables_initializer()
sess=tf.Session()
print (c.eval())
上面的代码编译是错误的,显示错误如下:
ValueError: Cannot evaluate tensor using eval()
: No default session is registered. Use with sess.as_default()
or pass an explicit session to eval(session=sess)
import tensorflow as tf
import numpy as np
a=tf.constant([[1., 2., 3.],[4., 5., 6.]])
b=np.float32(np.random.randn(3,2))
c=tf.matmul(a,b)
init=tf.global_variables_initializer()
sess=tf.InteractiveSession()
print (c.eval())
而用InteractiveSession()就不会出错,说白了InteractiveSession()相当于:
sess=tf.Session()
with sess.as_default():
换句话说,如果说想让sess=tf.Session()起到作用,一种方法是上面的with sess.as_default();另外一种方法是
sess=tf.Session()
print (c.eval(session=sess))
其实还有一种方法也是with,如下:
import tensorflow as tf
import numpy as np
a=tf.constant([[1., 2., 3.],[4., 5., 6.]])
b=np.float32(np.random.randn(3,2))
c=tf.matmul(a,b)
init=tf.global_variables_initializer()
with tf.Session() as sess:
#print (sess.run(c))
print(c.eval())
总结:tf.InteractiveSession()默认自己就是用户要操作的session,而tf.Session()没有这个默认,因此用eval()启动计算时需要指明session。
参考网址:
- https://www.cnblogs.com/cvtoEyes/p/9035047.html
- https://blog.csdn.net/qq_14839543/article/details/77822916
- https://www.cnblogs.com/wuzhitj/p/6648610.html
- https://blog.csdn.net/zhuiyuanzhongjia/article/details/80463237
- https://blog.csdn.net/cocoaqin/article/details/79180277
- https://www.jianshu.com/p/6766fbcd43b9