text: import unittest
  from keras.models import Sequential
  from keras.layers import Dense
  import numpy
  
  
  class AppTest(unittest.TestCase):
  
      def testTrainNetwork(self):
          dataset = numpy.loadtxt("data/pima-indians-diabetes.data.csv", delimiter=",")
          X = dataset[:, 0:8]
          Y = dataset[:, 8]
          
          model = Sequential()
          model.add(Dense(12, input_dim=8, activation='relu'))
          model.add(Dense(8, activation='relu'))
          model.add(Dense(1, activation='sigmoid'))
          
          model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
          
          model.fit(X, Y, epochs=150, batch_size=10)
          
          scores = model.evaluate(X, Y)
          print("\n%s: %.2f%%" % (model.metrics_names[1], scores[1] * 100))
  
  
      def testTrainNetworkConv(self):
  
      	
  
  if __name__ == '__main__':
      unittest.main()
  