@twiecki, what if mkl and other dependencies are installed using conda-forge before, and then pymc3 installation is done using pip (as suggested in Installation Guide (Windows) · pymc-devs/pymc3 Wiki · GitHub). Would you recommend using just conda or, if the dependencies are already installed via conda, pip could be used for an efficient setup?
I’m asking that because this procedure (conda for dependencies, then pip) was the only one that seemed to work cleanly for me while doing a environment setup in Windows 10. Using only conda-forge implied in some warnings related to BLAS.
I reinstalled my pymc3 by anaconda, but the sampling speed is quite slow, almost 10 times slower than before I updated my anaconda.
So I tried to find the reason from warning:
Firstly,
WARNING (theano.configdefaults): g++ not available, if using conda: `conda install m2w64-toolchain`
C:\Users\admin\anaconda3\lib\site-packages\theano\configdefaults.py:560: UserWarning: DeprecationWarning: there is no c++ compiler.This is deprecated and with Theano 0.11 a c++ compiler will be mandatory
warnings.warn("DeprecationWarning: there is no c++ compiler."
WARNING (theano.configdefaults): g++ not detected ! Theano will be unable to execute optimized C-implementations (for both CPU and GPU) and will default to Python implementations. Performance will be severely degraded. To remove this warning, set Theano flags cxx to an empty string.
Although I try to install m2w64-toolchain, I cannot slove this warning.
I found how to install g++ but failed.