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'})
from source.ann.optimizers import SGD, SimpleGD
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..."
