## Activate greedy completion PENDING DEPRECTION. this is now mostly taken care#  of with Jedi.#  #  This will enable completion on elements of lists, results of function calls,#  etc., but can be unsafe because the code is actually evaluated on TAB.c.Completer.greedy = False## Experimental: restrict time (in milliseconds) during which Jedi can compute#  types. Set to 0 to stop computing types. Non-zero value lower than 100ms may#  hurt performance by preventing jedi to build its cache.c.Completer.jedi_compute_type_timeout = 400## Experimental: Use Jedi to generate autocompletions. Off by default.c.Completer.use_jedi = False

## Activate greedy completion PENDING DEPRECTION. this is now mostly taken care#  of with Jedi.#  #  This will enable completion on elements of lists, results of function calls,#  etc., but can be unsafe because the code is actually evaluated on TAB.c.Completer.greedy = True## Experimental: restrict time (in milliseconds) during which Jedi can compute#  types. Set to 0 to stop computing types. Non-zero value lower than 100ms may#  hurt performance by preventing jedi to build its cache.c.Completer.jedi_compute_type_timeout = 400## Experimental: Use Jedi to generate autocompletions. Off by default.c.Completer.use_jedi = True

C:\Users\ZHONGZHENHUA\.ipython\profile_default\ipython_config.py

import tensorflow as tfdata1 = tf.constant(6)data2 = tf.constant(2)dataAdd = tf.add(data1,data2)dataMul = tf.multiply(data1,data2)dataSub = tf.subtract(data1,data2)dataDiv = tf.divide(data1,data2)with tf.Session() as sess:    print(sess.run(dataAdd))    print(sess.run(dataMul))    print(sess.run(dataSub))    print(sess.run(dataDiv))print('end!')

import tensorflow as tfdata1 = tf.constant(6)data2 = tf.Variable(2)dataAdd = tf.add(data1,data2)dataMul = tf.multiply(data1,data2)dataSub = tf.subtract(data1,data2)dataDiv = tf.divide(data1,data2)init = tf.global_variables_initializer()with tf.Session() as sess:    print(sess.run(init))    print(sess.run(dataAdd))    print(sess.run(dataMul))    print(sess.run(dataSub))    print(sess.run(dataDiv))print('end!')

import tensorflow as tfdata1 = tf.constant(6)data2 = tf.Variable(2)#data2 = tf.constant(2)dataAdd = tf.add(data1,data2)dataCopy = tf.assign(data2,dataAdd)# dataAdd ->data2dataMul = tf.multiply(data1,data2)dataSub = tf.subtract(data1,data2)dataDiv = tf.divide(data1,data2)init = tf.global_variables_initializer()with tf.Session() as sess:    print(sess.run(init))    print(sess.run(dataAdd))    print(sess.run(dataMul))    print(sess.run(dataSub))    print(sess.run(dataDiv))    print('sess.run(dataCopy)',sess.run(dataCopy))    print('dataCopy.eval()',dataCopy.eval())    print('tf.get_default_session()',tf.get_default_session().run(dataCopy))print('end!')

import tensorflow as tfdata1 = tf.constant(6)data2 = tf.Variable(2)#data2 = tf.constant(2)dataAdd = tf.add(data1,data2)dataCopy = tf.assign(data2,dataAdd)# dataAdd ->data2dataMul = tf.multiply(data1,data2)dataSub = tf.subtract(data1,data2)dataDiv = tf.divide(data1,data2)init = tf.global_variables_initializer()with tf.Session() as sess:    print(sess.run(init))    print(sess.run(dataAdd))    print(sess.run(dataMul))    print(sess.run(dataSub))    print(sess.run(dataDiv))    print('sess.run(dataCopy)',sess.run(dataCopy))#8->data2    print('dataCopy.eval()',dataCopy.eval())#8+6->14->data2 = 14    print('tf.get_default_session()',tf.get_default_session().run(dataCopy))#14+6->20->data2 = 20 sess.run() tensor.eval()print('end!')