I'm having an issue reverting to tensorflow-cpu from gpu on Windows 10 64 bit, Python 3.5.3.
I'm using riga/tfdeploy to distribute trained models, which is not compatible with tf-gpu. I installed tf-gpu for an experiment, then reverted to cpu, all using pip install/uninstall. Now I'm getting error messages about unknown ops like RealDiv and VariableV2. When starting a tensorflow session I now get a bunch of messages that did not appear before installing and uninstalling the GPU version, like:
OpKernel ('op: "BestSplits" device_type: "CPU"') for unknown op: BestSplits
My question is: How can I remove any trace of tf-gpu from my system and get back to tf-cpu? I'm using tensorflow-1.0.0-cp35-cp35m-win_amd64.whl (V1.0.0)
I read this:
How to uninstall TensorFlow completely?
And several related issues on GitHub, but haven't been able to go back to tf-cpu.
Steps to reproduce:
- On Win 10 64 bit, Python 3.5.3, pip install tensorflow
- run a tf.Session() - no messages about ops like BestSplits, RealDiv etc., tfdeploy runs fine.
- pip install tensorflow-gpu
- pip uninstall tensorflow-gpu
- Some trace of these ops remains registered, causing warnings like
OpKernel ('op: "BestSplits" device_type: "CPU"') for unknown op: BestSplits
while runninng tf, and also causing frameworks like tfdeploy to crash
I have tried completely reinstalling Python 3, deleting all site-packages etc. I've installed and uninstalled CUDA. The ops seem to be registered somewhere, leading to different behavior of tf-cpu after installing and uninstalling tf-gpu.
Any pointers on getting rid of/unregistering these ops is appreciated!