import NeuralNet as nn network = nn.Network() network.add_layer(3) # input network.add_layer(2) # hidden network.add_layer(1) # output out = network.fire_network([.5, .5, .5]) print(out)
import ImageLoader import NeuralNet import datetime import pickle as cPickle a = str(datetime.datetime.now()).split() filepath = "./SavedModels/" filename = "Model" + a[0] + "_" + a[1] training_data, validation_data, test_data = ImageLoader.load_data_wrapper() net = NeuralNet.Network([784, 40, 10]) net.SGD(training_data, 40, 10, 3.0, test_data=test_data) filename = str(net.accuracy) + "::" + filename filehandler = open(filepath + filename, 'wb') cPickle.dump(net, filehandler)
