keras_multilabel

from keras.models import Model
from keras.layers import Input, Dense
from keras.layers.noise import GaussianDropout

print "[*] Multilabel"
input1 = Input(shape=(2,), dtype='float32', name='input')
z1 = Dense(4,activation='relu')(input1)
z1 = GaussianDropout(0.2)(z1)
z2 = Dense(2,activation='sigmoid')(z1)

model = Model(inputs=input1,outputs=z2)
model.compile(optimizer=optimizers.Adam(),loss='binary_crossentropy')
model.summary()