cfg.idx = a
else:
assert False, "unhandled option"
if not hasattr(cfg, "basename"):
usage()
sys.exit()
if not hasattr(cfg, "idx"):
cfg.idx = "pretrain"
fn = os.path.join(cfg.basename, "info-0-%s.pickle" % cfg.idx)
if not cfg.overwrite and os.path.exists(fn):
with open(fn, "r") as f:
stats = cPickle.load(f)
if "nats" in stats:
print "pickle already has a value for partition function in it, exiting."
sys.exit(0)
cp.initCUDA(cfg.device)
# load pickle with rbm cfg
fn = os.path.join(cfg.basename, "info-0.pickle")
with open(fn, "r") as f:
rbmcfg = cPickle.load(f)
cfg.dataset = rbmcfg["dataset"]
start_time = time.clock()
bv, bh, W = read_data(cfg.basename, cfg.idx)
mbp = get_mbp(cfg)
pf = PartitionFunction(W, bv, bh)
print "\nCalculating Probability of Data."
if cfg.dataset == Dataset.mnist:
num = pf.numerator(mbp, 1000)
pig = Image.open("tests/data/gray_square.gif").resize((640,480)).convert("L")
#test_cuda_array(np.asarray(pig)
def test_gaussian_pyramid_construction():
print "Color Pyramid Construction on GPU: ",
global pic
w, h = 640,480
pic = Image.open("tests/data/gray_square.gif").resize((w,h)).convert("RGBA")
pic = np.asarray(pic).reshape(h,w*4)
for x in xrange(1): # warmup
build_pyramid_GPU(pic,input_channels=4,pyramid_channels=3)
t = Timer('build_pyramid_GPU(pic,4,3)','from %s import build_pyramid_GPU, cp, pic'%__name__)
print t.timeit(number=100)/100
print "Grayscale Pyramid Construction on CPU: ",
pic = Image.open("tests/data/gray_square.gif").resize((w,h)).convert("RGB")
pic = np.asarray(pic)
t = Timer('build_pyramid_CPU(pic)','from %s import build_pyramid_CPU, pic'%__name__)
print t.timeit(number=100)/100
if __name__ == "__main__":
cp.initCUDA(0)
run()
test_pixel_classes()
test_gaussian_pyramid_construction()
cp.exitCUDA()
def initialize(cfg):
cp.initCUDA(cfg.device)
cp.initialize_mersenne_twister_seeds(cfg.seed)
def setUpModule():
cp.initCUDA(-1)
cfg.idx = a
else:
assert False, "unhandled option"
if not hasattr(cfg, "basename"):
usage()
sys.exit()
if not hasattr(cfg, "idx"):
cfg.idx = "pretrain"
fn = os.path.join(cfg.basename, "info-0-%s.pickle" % cfg.idx)
if not cfg.overwrite and os.path.exists(fn):
with open(fn, "r") as f:
stats = cPickle.load(f)
if "nats" in stats:
print "pickle already has a value for partition function in it, exiting."
sys.exit(0)
cp.initCUDA(cfg.device)
#load pickle with rbm cfg
fn = os.path.join(cfg.basename, "info-0.pickle")
with open(fn, "r") as f:
rbmcfg = cPickle.load(f)
cfg.dataset = rbmcfg['dataset']
start_time = time.clock()
bv, bh, W = read_data(cfg.basename, cfg.idx)
mbp = get_mbp(cfg)
pf = PartitionFunction(W, bv, bh)
print "\nCalculating Probability of Data."
if cfg.dataset == Dataset.mnist:
num = pf.numerator(mbp, 1000)
def test_gaussian_pyramid_construction():
print "Color Pyramid Construction on GPU: ",
global pic
w, h = 640, 480
pic = Image.open("tests/data/gray_square.gif").resize(
(w, h)).convert("RGBA")
pic = np.asarray(pic).reshape(h, w * 4)
for x in xrange(1): # warmup
build_pyramid_GPU(pic, input_channels=4, pyramid_channels=3)
t = Timer('build_pyramid_GPU(pic,4,3)',
'from %s import build_pyramid_GPU, cp, pic' % __name__)
print t.timeit(number=100) / 100
print "Grayscale Pyramid Construction on CPU: ",
pic = Image.open("tests/data/gray_square.gif").resize(
(w, h)).convert("RGB")
pic = np.asarray(pic)
t = Timer('build_pyramid_CPU(pic)',
'from %s import build_pyramid_CPU, pic' % __name__)
print t.timeit(number=100) / 100
if __name__ == "__main__":
cp.initCUDA(0)
run()
test_pixel_classes()
test_gaussian_pyramid_construction()
cp.exitCUDA()
def initialize(cfg):
cp.initCUDA(cfg.device)
cp.initialize_mersenne_twister_seeds(cfg.seed)
def setUpModule():
cp.initCUDA(-1)
