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 and similar questions.
October 2020 update: Tensorflow now supports Python 3.5.x through Python 3.8.x, but you still have to use a 64-bit version. If you need to run multiple versions of Python on the same machine, you can use a virtual environment to help manage them.
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 using a TensorFlow version that is compatible with your Python version and supports GPU functionality.
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 libraries in that, like pandas, it says "no packages available".
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".
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 directly in python or I have to write the cpp code?
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.
