Theano with Keras on Raspberry Pi

If you had provided the version of python it would have been useful. If you are using python3.7 try reverting back to python3.6 because keras has not yet caught up to the development and there are a lot of problems installing tensorflow with keras on python3.7. I am putting emphasis on version here because I recently faced same problem installing using conda and I realised the issue was python version.

But I also had problems getting tensorflow to work on PI. But I used direct installation using pip from ubuntu and not miniconda and it worked. The way that Google Tensorflow team itself mentions is best is to actually build tensorflow from source by following instructions from this link.https://www.tensorflow.org/install/source_rpi

So try to downgrade the version of python to 3.6 or less if you can and try to install using pip or build from source using python3.6 or 3.7.

I think running Keras and Tensorflow on Raspberry Pi is not a good idea because running those on my college machine which is comparatively far more powerful than Raspberry Pi, gives a lot of trouble.Maybe the errors are caused because of insufficient memory. I am guessing this because I face this problem in my machine when I try to run some complex models.

For now the solution is to avoid miniconda when installing.

To diagnose further, it would be helpful for ld-linux-armhf.so.3 and libopenblas.so.0 to have -g debug symbols available.