I guess this note from the TensorFlow documentation sums it up: GPU support on native-Windows is only available for 2.10 or earlier versions Below it you also find the compatible combinations of Python, TensorFlow, CUDA and cuDNN. In case you absolutely need to use Windows, these are the last supported versions:
Caution: TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2, or install tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin From TensorFlow 2.11 onwards, the only way to get GPU support on Windows is to use WSL2.
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".
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 certain part, related to the model definition and training.
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.
Edit: It is now far easier to download Tensorflow with GPU support using the command line. I have kept the old solution below, but I'd recommend you use this new solution.
Did you start Python from the tensorflow source directory (e.g. a clone of the GitHub repository)? If so, Python can get confused by the two possible tensorflow packages in its search path. Try changing to another directory and restarting Python.
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".
To solve the problem i had to tweak the two versions of tf and tf addons. So if in the future you have the same problem try to change the number of the 2 versions. In the end i manage to solve without reinstalling tf like this: !pip install tensorflow-addons==0.16.1 import tensorflow_addons as tfa This is enough right now.
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.
