However, when I substituted either tensorflow-cpu or tensorflow-gpu (depending upon which one is appropriate for you) then the code was suddenly able to find tensorflow.

Working with tensorflow and pytorch in one script, this approach help me to disable cuda on tensorflow but still make the pytorch use cuda. I believe this answer deserved more votes.

Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2, or install tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin Before that, I read most of the answers to this …

For example, TensorFlow 2.10.0-gpu may have constraints that limit its compatibility with Python versions, such as Python 3.11. To address this issue, it is recommended to ensure that you are …

1 I had the same issue running a python file named tensorflow.py, after renaming it the issue dissapeared and the file started running properly.

Looking at the existing answers, we find both conda install tensorflow and pip install tensorflow. Furthermore, "look on youtube" is about as good an advice as "just google it".

SFOM00618927A:dl i854319$ source activate tensorflow (tensorflow) SFOM00618927A:dl i854319$ jupyter notebook It opens up a new notebook in the browser. But when I just import basic python …

The difference between tf.keras and keras is the Tensorflow specific enhancement to the framework. keras is an API specification that describes how a Deep Learning framework should implement …

49 I am new to tensorflow. I want to write my own custom loss function. Is there any tutorial about this? For example, the hinge loss or a sum_of_square_loss (though this is already in tf)? Can I do it …

Tensorflow released 2.0.0, and now you must choose either tfjs-backend-webgl, tfjs-backend-cpu, or tfjs-backend-wasm to run your model. You're using handpose and for that you should use webgl.