Python load_all_flat_cases Examples

Example #1

File: mnist_trainer.py Project: bompi88/aiprog

    def __init__(self, gui_worker=None):

        print('----> Loading cases...')

        training_set = load_all_flat_cases('training')
        testing_set = load_all_flat_cases('testing')

        provided_datasets = [
            training_set,
            testing_set
        ]

        self.net = Ann(
            structure=[784, 200, 40, 10],
            datasets=provided_datasets,
            activation_function=[T.nnet.sigmoid, T.nnet.sigmoid, T.nnet.sigmoid],
            learning_rate=0.2,
            regression_layer=SumOfSquaredErrors,
            gui_worker=gui_worker
        )

        self.gui_worker = gui_worker

Example #2

File: test_mnist_ann.py Project: bompi88/aiprog

from src.algorithms.ann.sum_of_squared_errors import SumOfSquaredErrors
from src.utils.mnist_basics import load_all_flat_cases, minor_demo
from src.algorithms.ann.ann import Ann
from theano import tensor as T

if __name__ == '__main__':
    print('----> Loading cases...')

    training_set = load_all_flat_cases('training')
    testing_set = load_all_flat_cases('testing')

    provided_datasets = [
        training_set,
        testing_set
    ]

    net1 = Ann(
        structure=[784, 150, 10],
        datasets=provided_datasets,
        activation_function=[T.nnet.sigmoid, T.nnet.sigmoid, T.nnet.sigmoid],
        learning_rate=0.1,
        regression_layer=SumOfSquaredErrors
    )

    net1.train(100)
    minor_demo(net1)

    net2 = Ann(
        structure=[784, 150, 10],
        datasets=provided_datasets,
        activation_function=[T.nnet.sigmoid, T.nnet.sigmoid, T.nnet.sigmoid],