Esempi in Python per cg_optimization_mnist

Esempio n. 1

File: test.py Progetto: MrChocolateMoose/DeepHyperNEAT

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.')

Esempio n. 2

File: test.py Progetto: yiminyangguang520/DeepLearningTutorials

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.')

Esempio n. 3

File: test.py Progetto: JakeMick/kaggle

def test_logistic_cg():
    logistic_cg.cg_optimization_mnist(n_epochs=10)

Esempio n. 4

def test_logistic_cg():
    logistic_cg.cg_optimization_mnist(n_epochs=10)

Esempio n. 5

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)

Esempio n. 6

File: test.py Progetto: pascanur/DeepLearningTutorials

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)

Esempio n. 7

File: test_cifar-100.py Progetto: kaddynator/deep-learning-with-noise

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)