## 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:UsersHONGZHENHUA.ipythonprofile_defaultipython_config.py
import tensorflow as tf data1 = 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 tf data1 = 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 tf data1 = tf.constant(6) data2 = tf.Variable(2) #data2 = tf.constant(2) dataAdd = tf.add(data1,data2) dataCopy = tf.assign(data2,dataAdd)# dataAdd ->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('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 tf data1 = tf.constant(6) data2 = tf.Variable(2) #data2 = tf.constant(2) dataAdd = tf.add(data1,data2) dataCopy = tf.assign(data2,dataAdd)# dataAdd ->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('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!')