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'}) y = y.astype('float') y = np.asarray(y) df = df.replace({'f':'0', 't':'1', 'l':'0', 'g':'1', 'n':'0', 't':'1', 'w':'1', 'b':'2'}) X = np.array(df.ix[:,0:35], dtype=theano.config.floatX)
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..." train_dir = "working_data/sample_2_small" img_names = os.listdir(train_dir) y = pd.read_csv("data/trainLabels.csv", header=0) files = [im.replace(".jpg","") for im in img_names] y = y[y.image.isin(files)] y = y.reindex(np.random.permutation(y.index)) y.reset_index(inplace=True) y = y[["image","level"]]