model.compile(optimizer='rmsprop',
              loss={'main_output': 'mse', 'aux_output_gender':'categorical_crossentropy','aux_output_smile':'categorica_crossentropy','aux_output_glass':'categorical_crossentropy','aux_output_pose': 'categorical_crossentropy'},
          loss_weights={'main_output': 1.0, 'aux_output_gender': 0.1,'aux_output_smile': 0.1, 'aux_output_glass': 0.1,'aux_output_pose': 0.1})


 early_stopping1 =EarlyStopping(monitor='val_aux_output_pose_loss', patience=2)

history = model.fit({'main_input': X},
      {'main_output': y, 'aux_output_gender': y_aux_gender,'aux_output_smile': y_aux_smile,'aux_output_glass': y_aux_glass,'aux_output_pose': y_aux_pose}, validation_data=({'main_input': X_Test},{'main_output': y_test, 'aux_output_gender': y_aux_gender_test,'aux_output_smile': y_aux_smile_test,'aux_output_glass': y_aux_glass_test,'aux_output_pose': y_aux_pose_test}),
      nb_epoch=20, batch_size=16, callbacks=[early_stopping1])