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"]]
