1. download minicondapython
2. conda install libpython mingwdom
3. conda install theanoide
now you can run theano correctly.oop
1. download and install cuda8.0ui
2. downlaod and install vs2015spa
2. download and install Windows Kitscode
3. add path "LIB" = "C:\Program Files (x86)\Windows Kits\10\Lib\10.0.14393.0\um\x64;C:\Program Files (x86)\Windows Kits\10\Lib\10.0.14393.0\ucrt\x64"blog
add path "INCLUDE" = "C:\Program Files (x86)\Windows Kits\10\Include\10.0.14393.0\ucrt";it
4. add "C:/user/your_user_name/.theanorc.txt":io
1 [global] 2 profile_optimizer=True 3 profile=True 4 floatX = float32 5 device = gpu 6 [nvcc] 7 compiler_bindir=D:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\bin
8 [dnn]
9 enable=auto
5. theano gpu cpu test:
1 from theano import function,config,shared,sandbox 2 import theano.tensor as T 3 import numpy 4 import time 5 print config.profile 6 7 vlen=10*30*768 8 iters=1000 9 rng=numpy.random.RandomState(22) 10 x=shared(numpy.asarray(rng.rand(vlen),config.floatX)) 11 f=function([],T.exp(x)) 12 print (f.maker.fgraph.toposort()) 13 t0=time.time() 14 for i in range(iters): 15 r=f() 16 t1=time.time() 17 print("loop %d time took "% iters, t1-t0,'seconds') 18 print("results is",r) 19 if numpy.any([isinstance(x.op,T.Elemwise) for x in f.maker.fgraph.toposort()]): 20 print ('used the cpu') 21 else: 22 print ('used the gpu')