Attributeerror: module tensorflow has no attribute attribute_name error occurs mainly when the corresponding attribute is either not defined in the referring module/class or we refer or invoke a different class/module. Especially If I talk about tensorflow, There is a major release of TensorFlow 2. x which has so many syntax differences and this is the area where we encounter most of the AttributeErrors. Well, In this article, We will explore the best tricks to fix this type of AttributeErrors.
Attributeerror: module tensorflow has no attribute attribute_name (Solution) –
The best way to fix this type of incompatibility is below-
1.Migrate TensorFlow 1.x oriented code to TensorFlow 2.x. The best part of this migration is that you do not have to manually replace the incompatible code but you can run a script and it will do all the tasks for you.
--intree code/ \
--outtree code_v2/ \
2. We can keep the feature and syntax of tensorflow 1. x in 2. x series by disabling Tensorflow 2. x behavior. Here is the way.
import tensorflow.compat.v1 as tf
3. Downgrading the tensorflow version to 1. x but is not recommended way. It may increase backward incompatibility as well. So be careful be this way.
Underline Error –
There are so many errors that are on the same concept. To give a good grip on the concept we have provided the solution for the below modules. Apart from the mentioned one, there are several other modules like a log, etc which also throws the same error.
Data Science Learner Team
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