<reponame>rrlyman/PythonMachineLearingExamples<filename>q7_theano_gpu_test.py
#!/usr/bin/python
''' short test from the Theano website to see if Theano is working with CUDA
.theanrc contains

[global]
floatX = float32
device = gpu0


@author: <NAME>

'''
import os
print (os.get_exec_path())
p=os.getenv('PATH')
print("getenv('PATH')={}".format(p))
p=os.getenv('LD_LIBRARY_PATH')
print("getenv('LD_LIBRARY_PATH')={}".format(p))
p=os.getenv('CUDA_HOME')
print("getenv('CUDA_HOME')={}".format(p))
p=os.getenv('PYTHONPATH')
print("getenv('PYTHONPATH')={}".format(p))

#os.environ['PATH'] = p
# print(os.getenv('PATH'))
from theano import function, config, shared, sandbox
import theano.tensor as T
import numpy
import time

vlen = 10 * 30 * 768  # 10 x #cores x # threads per core
iters = 1000

rng = numpy.random.RandomState(22)
x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
f = function([], T.exp(x))
print(f.maker.fgraph.toposort())
t0 = time.time()
for i in range(iters):
    r = f()
t1 = time.time()
print("Looping %d times took %f seconds" % (iters, t1 - t0))
print("Result is %s" % (r,))
if numpy.any([isinstance(x.op, T.Elemwise) for x in f.maker.fgraph.toposort()]):
    print('Used the cpu')
else:
    print('Used the gpu')
    
print ('\n########################### No Errors ####################################')    