import pandas as pd import numpy as np import theano from source.ann.layers import FullyConnected, Activation, ArgMax from source.ann.core import LayeredModel from source.ann.optimizers import SGD print "compiling model..." model = LayeredModel() #model.add(FullyConnected(36,6, init='glorot_uniform', activation='tanh')) model.add(FullyConnected(36, 2, init='glorot_uniform', activation='softmax')) model.add(ArgMax()) sgd = SGD(lr=0.1, decay=0., momentum=0., nesterov=False) model.compile(loss='zero_one_loss', optimizer=sgd) print "compiling prediction function..." _predict = theano.function([model.get_input()], model.get_output(), allow_input_downcast=True) print "getting data..." df = pd.read_csv("data/kr-vs-kp.data.txt", header=None) y = df.ix[:,36] y = y.replace({'won' : '1'}).replace({'nowin' : '0'})
def read_images(img_names): imgs = [] for im in img_names: img = Image.open(im) img = np.asarray(img, dtype=theano.config.floatX) / 256. img = img.flatten() imgs.append(img) return imgs if __name__ == '__main__': print "compiling model..." model = LayeredModel() model.add(FullyConnected(11250,10, init='uniform', activation='tanh')) model.add(FullyConnected(10, 5, init='uniform', activation='softmax')) model.add(ArgMax()) sgd = SGD(lr=0.1, decay=0., momentum=0., nesterov=False) sgd = SimpleGD() model.compile(loss='zero_one_loss', optimizer=sgd) print "compiling prediction function..." _predict = theano.function([model.get_input()], model.get_output(), allow_input_downcast=True) print "reading images..."