How to downgrade tensorflow version in colab?

↘锁芯ラ 提交于 2019-12-04 11:22:14
miguelmorin

You can downgrade Tensorflow to a previous version without GPU support on Google Colab. I ran:

!pip install tensorflow==1.12.0
import tensorflow as tf
print(tf.__version__)

which initially returned

2.0.0-dev20190130

but when I returned to it after a few hours, I got the version I requested:

1.12.0

Trying to downgrade to a version with GPU support:

!pip install tensorflow-gpu==1.12.0

requires restarting the runtime and fails, as importing import tensorflow as tf returns:

ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory

UPDATE:

When the import fails you can always downgrade CUDA to version 9.0 using following commands !wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb !dpkg -i cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb !apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub !apt-get update !apt-get install cuda=9.0.176-1

You can check the version of CUDA by running: !nvcc --version

The build process for GPU-enabled tensorflow is involved. In particular, old versions of TensorFlow use (or require) older versions of CUDA, which itself depends on system libraries and configuration beyond the scope of a pip install.

I suspect that downgrading TensorFlow on a VM configured for a newer version is going to be an involved process, perhaps involving downgrades / reinstalls of system libraries.

If it's practical, it might be simpler to update your code to use the latest version of TensorFlow, at least until Colab supports persistent backend enivronments.

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