tensorflow 2.0 AttributeError、ModuleNotFoundError

 

解决AttributeError: module 'tensorflow' has no attribute 'ConfigProto'：

使用CUDA10.1加上Tensorflow 2.0会出现AttributeError: module 'tensorflow' has no attribute 'ConfigProto'这个问题，这个是由于现在新版本中一些1.0版本的函数被和2.0版本函数区分开的缘故。

需要将

tf.ConfigProto

修改为

tf.compat.v1.ConfigProto

参考blog：https://blog.csdn.net/u012388993/article/details/102573008

解决ModuleNotFoundError: No module named 'tensorflow.contrib'：

tf.contrib  doesn't exist in 2.0

参考blog：https://github.com/tensorflow/tensorflow/issues/31350

解决AttributeError: module 'tensorflow' has no attribute 'Session'：

tensorflow 2.0版本导致

需要将

tf.Session()

修改为

tf.compat.v1.Session()

参考blog：https://blog.csdn.net/qq_33440324/article/details/94200046

https://docs.google.com/spreadsheets/d/1FLFJLzg7WNP6JHODX5q8BDgptKafq_slHpnHVbJIteQ/edit#gid=0

AttributeError: module 'tensorflow' has no attribute 'placeholder'等问题的解决

Tensorflow 1.x 版本提供placeholder，而 2.0版本暂时没有这个模块。

If you have this error after an upgrade to TensorFlow 2.0, you can still use 1.X API by replacing:

import tensorflow as tf

with 

import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()

Actually, this modification can help to solve many potential problems.

参考blog： https://stackoverflow.com/questions/37383812/tensorflow-module-object-has-no-attribute-placeholder

tensorflow之tf.contrib.layers.xavier_initializer：

In tensorflow 2.0 you have a package tf.initializer with all the Keras-like initializers you need.

The Xavier initializer is the same as the Glorot Uniform initializer. 

shape = (3,3)
initializer = tf.initializers.GlorotUniform()
var = tf.Variable(initializer(shape=shape))

 tf.initializers.GlorotUniform() 可以替代 之前的 tf.contrib.layers.xavier_initializer

参考blog：https://stackoverflow.com/questions/55322754/how-to-do-weight-initialization-by-xavier-rule-in-tensorflow-2-0