After I updated Anaconda, sampling with Pymc3 became very slow

Questions
8

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.

Here is my version of m2w64:

m2w64-binutils 2.25.1 5 conda-forge
m2w64-bzip2 1.0.6 6 conda-forge
m2w64-crt-git 5.0.0.4636.2595836 2 conda-forge
m2w64-gcc 5.3.0 6 conda-forge
m2w64-gcc-ada 5.3.0 6 conda-forge
m2w64-gcc-fortran 5.3.0 6 conda-forge
m2w64-gcc-libgfortran 5.3.0 6 conda-forge
m2w64-gcc-libs 5.3.0 7 conda-forge
m2w64-gcc-libs-core 5.3.0 7 conda-forge
m2w64-gcc-objc 5.3.0 6 conda-forge
m2w64-gmp 6.1.0 2 conda-forge
m2w64-headers-git 5.0.0.4636.c0ad18a 2 conda-forge
m2w64-isl 0.16.1 2 conda-forge
m2w64-libiconv 1.14 6 conda-forge
m2w64-libmangle-git 5.0.0.4509.2e5a9a2 2 conda-forge
m2w64-libwinpthread-git 5.0.0.4634.697f757 2 conda-forge
m2w64-make 4.1.2351.a80a8b8 2 conda-forge
m2w64-mpc 1.0.3 3 conda-forge
m2w64-mpfr 3.1.4 4 conda-forge
m2w64-pkg-config 0.29.1 2 conda-forge
m2w64-toolchain 5.3.0 7 conda-forge
m2w64-toolchain_win-64 2.4.0 0 conda-forge
m2w64-tools-git 5.0.0.4592.90b8472 2 conda-forge
m2w64-windows-default-manifest 6.4 3 conda-forge
m2w64-winpthreads-git 5.0.0.4634.697f757 2 conda-forge
m2w64-zlib 1.2.8 10 conda-forge

  • Secondly,
WARNING (theano.tensor.blas): Using NumPy C-API based implementation for BLAS functions.

From here, I knew that it seems to be the reason for the slow sampling, but I tried the code as followed,

conda install numpy scipy mkl
conda install theano pygpu
conda install pymc3

but nothing changed. The warning stills occurred.