链接如下：

http://stackoverflow.com/questions/41791469/difference-between-tf-session-and-tf-interactivesession

Question：

Questions says everything, for taking sess=
tf.Session() and sess=tf.InteractiveSession() which cases should be
considered for what purpose ? When I am using former one some function
didn't work and when changed to the later it worked (for
example .eval()).

Answer：

 

Mainly taken from official documentation:

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.

This allows to use interactive context, like shell, as it avoids having to pass an explicit Session object to run op:

sess = tf.InteractiveSession()
a = tf.constant(5.0)
b = tf.constant(6.0)
c = a * b
# We can just use 'c.eval()' without passing 'sess'
print(c.eval())
sess.close()

It is also possible to say, that InteractiveSession supports less typing, as allows to run variables without needing to constantly refer to the session object.

 

中文

问题： tf.Session()和tf.InteractiveSession()的区别？

答案：

唯一的区别在于：tf.InteractiveSession()加载它自身作为默认构建的session，tensor.eval()和operation.run()取决于默认的session.

换句话说：InteractiveSession 输入的代码少，原因就是它允许变量不需要使用session就可以产生结构。