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- python - Import tensorflow. keras could not be resolved after . . .
But the second one need tensorflow __path__ contains keras module statically during type checking BTW, for from tensorflow import keras: If tensorflow has keras attribute, then it uses the attribute, otherwise it import keras as a submodule Theoretically, the second one should only work for 2 2 0 <= TF < 2 6 0, which has tensorflow keras folder
- Which TensorFlow and CUDA version combinations are compatible?
The section you're referring to just gives me the compatible version for CUDA and cuDNN --ONCE-- I have found out about my desired TensorFlow version In the common case (for example in edu lab environments) where CUDA and cuDNN are already installed but TF not, the necessity for an overview becomes apparent
- python - New TensorFlow (Compatible for GPU) Not Detecting GPU: CUDA 12 . . .
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:
- How can I know which is the lastest Python version compatible for . . .
All versions of Tensorflow (as in, the specific 2 X build for python 3 7 vs the one for 3 10) are equivalent and they can interoperate (models trained in one work in the other without any concern) If you mean "Will I be able to run models trained with older versions of the library", the answer is in TF's release notes and is not related to python
- Running Tensorflow in Jupyter Notebook - Stack Overflow
After installing, open the Anaconda command prompt to install TensorFlow using these steps: Create a conda environment named tensorflow by invoking the following command: conda create -n tensorflow python=3 5 (Use this command even if you are using python 3 6 because TensorFlow will get upgraded in the following steps)
- Tensorflow support for Python3. 11 - Stack Overflow
Just wanted to add that one of the tensorflow dependencies (tensorflow-io-gcs-filesystem) has specified that in its latest version works with Python >=3 11, but <3 12 If you are using poetry for dependency management, ensure that your Python version is limited to the same in order to enable the installation –
- python - How to pip install old version of library (tensorflow . . .
In general, installation instructions for older versions of TensorFlow can be found at : For binaries for installation using wheels: Go to tensorflow pypi release history, select the release of your choice, say tensorflow 1 8 0, go to Download files and either download the wheel file and then install or copy the download link and save in TF
- python - Tensorflow compatibility with Keras - Stack Overflow
There are two implementations of the Keras API: the standalone Keras (installed with pip install keras), and tf keras which is bundled with TensorFlow (pip install tensorflow) A while back, standalone Keras used to support multiple backends, namely TensorFlow, Microsoft Cognitive Toolkit, Theano, and PlaidML
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