image_names = y.image.tolist()
image_names = [im+".jpg" for im in image_names]
y = np.asarray(y.level, dtype=theano.config.floatX)
image_names = [train_dir+"/"+im for im in image_names]
X = np.array(read_images(image_names), dtype=theano.config.floatX)
print "training model..."
theano.printing.debugprint(model.get_output())
for e in xrange(100):
if e % 10 == 0:
print model.params[0].eval()
print model.loss(_predict(X), y).eval()
model.train(X, y, accuracy=False)
#print "\n\n"
#for val in model.layers[-2].params:
# print val.eval()
#print _predict(X)
#print "\n\n"
#print model.train(X, y, accuracy=False)
#print "\n\n"
#print y
