I am using Anaconda and Ubuntu 18.04. I installed TensorFlow probability base on Anaconda's command:
conda install -c conda-forge tensorflow-probability
but when I wanted to import TensorFlow probability, I faced with below error:
ImportError: cannot import name 'compiler' from 'tensorflow.python.autograph.pyct' (/home/alireza/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/autograph/pyct/init.py)
I check Anaconda by conda list tensorflow and TensorFlow probability version 0.8 was installed.
I appreciate your suggestion.
I think it's been a long time since the conda recipe for TFP was updated (TFP is now at 0.12), so you would need to ensure the version of TensorFlow you have is compatible. FWIW from the 0.8 release notes: "It is tested and stable against TensorFlow version 2.0.0 and 1.15.0rc1."
Related
I have a code that was running on colab with Tensorflow 2.0 and now I am trying to run it on a GPU with Tensorflow 1.14 and facing several errors. Is there an easy way to upgrade to tensorflow 2.0 or is it better to modify the code and make it working on the current version?
If your code is working on colab with TF 2.0, then you can uninstall TF-GPU 1.14 and install latest version of TF 2.4.
# Uninstall tensorflow
pip uninstall tensorflow-gpu == 1.14
# Requires the latest pip
pip install --upgrade pip
# Current stable release for CPU and GPU
pip install tensorflow (which install latest version of TF 2.4)
To know more details you can refer here
Like I said in title I installed pytorch with conda install and that downgraded my tensorflow version to 1.13.0 and now conda install tensorflow-gpu=2.0 is not working how can I get the command to execute?
I would suggest that you try to install tensorflow with pip. pip install -U tensorflow-gpu
https://www.tensorflow.org/install/gpu
I am using pytorch, but my env has pytorch 1.2 + tensorflow 2.1
You should have installed pyTorch in another virtual environment but since now it has been installed.
I would recommend you to create a virtual environment and install TF plus other libraries in it. Because I am sure you would not use both PyTorch and TF in the same program for ML.
I have tried to install keras, tensorflow, pytorch and all other dependencies in order to run a simple toy example using aukeras explained in https://autokeras.com/start/
After a lot of version changes and googling I found a typical error which prompts me to ask this question -
ImportError: Could not find 'nvcuda.dll'. TensorFlow requires that this DLL be installed in a directory that is named in your %PATH% environment variable. Typically it is installed in 'C:\Windows\System32'. If it is not present, ensure that you have a CUDA-capable GPU with the correct driver installed.
I don't have GPU or CUDA installed. Can I still run a toy example using CPU only?
Dependencies as mentioned below :
tensorboard 1.10.0
tensorflow 1.13.1
tensorflow-estimator 1.13.0
tensorflow-gpu 1.10.0
Keras 2.2.4
Keras-Applications 1.0.7
Keras-Preprocessing 1.0.9
autokeras 0.4.0
torch 1.0.1
torchvision 0.2.1
Uninstall tensorflow-gpu, use only tensorflow if you don't have GPU.
The tensorflow is CPU only version, you don't need to install both of them but if you have both, it will choose the GPU version.
Maybe you need to reinstall the tensorflow, uninstall both of them and install only the CPU version might better.
pip[3] uninstall tensorflow-gpu tensorflow
pip[3] install tensorflow
having problems while
screenshot given below. I want the solution badly.
import tensorflow as tf
https://i.stack.imgur.com/jgghK.png
You're using tensorflow-gpu but do not have CUDA / cuDNN installed on your computer.
Shor answer: run pip unintall tensorflow-gpu and pip install tensorflow.
Long answer: Install CUDA / cuDNN
The documentation indicate that tensorflow has a svd operator.
However, I can't find it in my tensorflow with pip for python2.7
I used these command on Mac:
pip install https://storage.googleapis.com/tensorflow/mac/tensorflow-0.8.0-py2-none-any.whl
Any suggestion would be appreciated.
You are trying to install tensorflow 0.8. The SVD was introduced in tensorflow 0.10. Try installing a more recent version. (Current version is 1.2).