AttributeError: Module 'tensorflow' Has No Attribute 'ConfigProto'
Solution 1:
ConfigProto disappeared in tf 2.0, so an elegant solution is:
import tensorflow as tf
and then replace:
tf.ConfigProto
by tf.compat.v1.ConfigProto
In fact, the compatibility built in 2.0 to get tf 1.XX: tf.compat.v1
is really helpful.
Useful link: Migrate your tensorflow 1. code to tensorflow 2.: https://www.tensorflow.org/guide/migrate
Solution 2:
I had similar issues, when upgraded to Python 3.7 & Tensorflow 2.0.0 (from Tensorflow 1.2.0)
This is an easy one and works!
If you don't want to touch your code, just add these 2 lines in the main.py file w/ Tensorflow code:
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
And that's it!!
NOW Everything should run seamlessly :)
Solution 3:
Just an addition to others looking for an answer for Tensorflow v2
As the others have mentioned, you can use the back-compatability to v1. But Tensorflow v2 does actually come with its own implementation of this. It is just a hidden experimental feature.
This is how to allow the GPU to grow in memory in Tensorflow v2:
# Allow memory growth for the GPU
physical_devices = tf.config.experimental.list_physical_devices('GPU')
tf.config.experimental.set_memory_growth(physical_devices[0], True)
More info found @Tensorflow
Solution 4:
If using tensorflow version > 2.0:
config = tf.compat.v1.ConfigProto()
config.gpu_options.allow_growth=True
sess = tf.compat.v1.Session(config=config)
Solution 5:
I was with a similar error, but i had tensorflow 1.14, ubuntu 18.04 and GTX 1050ti. So a installed properly conda (lastest version - 5.1) even with this the error persisted, so a upgraded tensorflow/tensorflow-gpu to -version tensorflow==2.0.0-beta0 and worked for me.
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