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A software error is an error that causes a website, app or any other software to suddenly not work or behave strangely in some situations. This issue usually happens because of a bug in the code, or because an external system is not working well. It’s important to understand the origin and how to resolve them. Example, AttributeError: module ‘tensorflow’ has no attribute ‘Session’ is evident and you are facing the risk to your computer. We will provide you some tips to fix this error.
How does the error “AttributeError: module ‘tensorflow’ has no attribute ‘Session’” occur?
If you don’t know how to fix it, don’t start the project. It is very important that you know the origin and solution before you even get started.
As this case, when you are using tensorflow session using tf.Session() you are facing the error
AttributeError: module 'tensorflow' has no attribute 'Session'
The tensorflow of version 2.0 is systematic and “Session()” has been uninstalled with TF 2.0. The “tf. Session()” feature that can be a problem also.
What is a TensorFlow Session?
The context in which Operation objects are executed and data objects are processed is encapsulated by the session object known as TensorFlow Session. To carry out an operation and obtain the result, TensorFlow needs a session. A session might be the owner of a number of resources, including tf.QueueBase, tf.Variable, and tf.ReaderBase. When these materials have served their purpose, it is crucial to make them completely free. You have two options for ending an open session: either use the session as a context manager or invoke the close function on the tf.Session object.
How to correct AttributeError: module ‘tensorflow’ has no attribute ‘Session’ error?
Solution 1: Add session with compat v1
Advise showed that use session with compat v1 if you are runing tensorFlow 2.0:
Solution 2: TensorFlow 1.X
Here is sample to use TensorFlow 1.X:
import tensorflow as tf msg = tf.constant('Hello world!!') sess = tf.Session()
Soltion 3: Remove “Session()” with TF 2.0
“Session()” with TF 2.0 need uninstalled.
import tensorflow as tf tf.compat.v1.disable_eager_execution() arg = tf.constant('Hello, World!!') sess = tf.compat.v1.Session() print(sess.run(arg))
Solution 4: Use the tf.compat.v1 module
To fix the error “AttributeError: module ‘tensorflow’ has no attribute ‘Session’”, let’s use the tf.compat.v1 module. The module includes the whole of the original semantic TF1.x API. The legacy compat.v1 APIs should not be used for any newly developed TensorFlow 2.0 code, although it is acceptable for previously written code. Let’s examine the updated code:
import tensorflow as tf # Initialize session using tf.compat.v1.Session with tf.compat.v1.Session() as sess: a = tf.constant(3.0) b = tf.constant(4.0) c = a + b print(sess.run(c))
In general, the two tips above demonstrated are simple solutions to the major problem of AttributeError: module ‘tensorflow’ has no attribute ‘Session’. we hope we have supported you a lot for your trouble. If you still have more questions, leave them in the comment box please. We would like to thank you for studying and hope you have a good day full of fresh code ideas.
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