Python SpnFactory.theano_naive_factorization Examples

Example #1

File: test_factory.py Project: danhlephuoc/spae

def test_theano_naive_factorization():
    spn = SpnFactory.theano_naive_factorization(vars)
    print('Naive factorization (indicators)')
    print(spn)

    spn = SpnFactory.theano_naive_factorization(vars, naive_freqs)
    print('Naive factorization (smoothing)')
    print(spn)

Example #2

File: test_factory.py Project: arranger1044/spyn

def test_theano_naive_factorization():
    spn = SpnFactory.theano_naive_factorization(vars)
    print('Naive factorization (indicators)')
    print(spn)

    spn = SpnFactory.theano_naive_factorization(vars,
                                                naive_freqs)
    print('Naive factorization (smoothing)')
    print(spn)

Example #3

File: test_factory.py Project: arranger1044/spyn

def atest_theano_nltcs_naive_spn():
    # load the dataset
    print('Loading datasets')
    train, valid, test = dataset.load_train_val_test_csvs('tmovie')
    n_test_instances = test.shape[0]
    # estimating the frequencies for the features
    print('Estimating features')
    freqs, features = dataset.data_2_freqs(train)

    print('Building naive factorization')
    spn = SpnFactory.theano_naive_factorization(features,
                                                freqs,
                                                alpha=0,
                                                batch_size=n_test_instances)
    print('Evaluating on test')
    ll = spn.eval(test.T)
    avg_ll = ll.mean()
    print(avg_ll)

Example #4

File: test_factory.py Project: danhlephuoc/spae

def atest_theano_nltcs_naive_spn():
    # load the dataset
    print('Loading datasets')
    train, valid, test = dataset.load_train_val_test_csvs('tmovie')
    n_test_instances = test.shape[0]
    # estimating the frequencies for the features
    print('Estimating features')
    freqs, features = dataset.data_2_freqs(train)

    print('Building naive factorization')
    spn = SpnFactory.theano_naive_factorization(features,
                                                freqs,
                                                alpha=0,
                                                batch_size=n_test_instances)
    print('Evaluating on test')
    ll = spn.eval(test.T)
    avg_ll = ll.mean()
    print(avg_ll)