def test_logistic_cg():
try:
import scipy
logistic_cg.cg_optimization_mnist(n_epochs=10)
except ImportError:
from nose.plugins.skip import SkipTest
raise SkipTest('SciPy not available. Needed for the logistic_cg example.')
def test_logistic_cg():
try:
import scipy
logistic_cg.cg_optimization_mnist(n_epochs=10)
except ImportError:
from nose.plugins.skip import SkipTest
raise SkipTest(
'SciPy not available. Needed for the logistic_cg example.')
def test_logistic_cg():
logistic_cg.cg_optimization_mnist(n_epochs=10)
def test_logistic_cg():
logistic_cg.cg_optimization_mnist(n_epochs=10)
def test_logistic_cg():
t0 = time.time()
logistic_cg.cg_optimization_mnist(n_epochs=10)
print >> sys.stderr, "test_logistic_cg took %.3fs expected 14s in our buildbot" % (
time.time() - t0)
def test_logistic_cg():
t0=time.time()
logistic_cg.cg_optimization_mnist(n_epochs=10)
print >> sys.stderr, "test_logistic_cg took %.3fs expected 14s in our buildbot"%(time.time()-t0)
import logistic_sgd
import logistic_sgd_gaussian
import logistic_sgd_binomial
import mlp
import mlp_dropOut
import mlp_dropConnect
import convolutional_mlp
import con_mlp_dropConnect
import con_mlp_dropOut
c100 = 'cifar-100-python.tar.gz'
sys.stdout = open('results/cifar-100_results/lcg.out', 'w')
logistic_cg.cg_optimization_mnist(mnist_pkl_gz=c100)
sys.stdout = open('results/cifar-100_results/lsgd.out', 'w')
logistic_sgd.sgd_optimization_mnist(dataset=c100)
sys.stdout = open('results/cifar-100_results/lsgd_gau.out', 'w')
logistic_sgd_gaussian.sgd_optimization_mnist(dataset=c100)
sys.stdout = open('results/cifar-100_results/lsgd_bin.out', 'w')
logistic_sgd_binomial.sgd_optimization_mnist(dataset=c100)
sys.stdout = open('results/cifar-100_results/mlp.out', 'w')
mlp.test_mlp(dataset=c100)
sys.stdout = open('results/cifar-100_results/mlpO.out', 'w')
# mlp_dropOut.test_mlp(p=0.8, n_hidden = 100)