text: import numpy as np
  from keras.models import Sequential
  from keras.layers import Dense
  
  model = Sequential() 
  model.add(Dense(64, input_dim=20, activation='relu')) 
  model.add(Dense(1, activation='sigmoid')) 
  model.compile(loss='binary_crossentropy',
                optimizer='rmsprop',
                metrics=['accuracy'])
  x_train = np.random.random ((1000, 20))
  y_train = np.random.randint (2, size = (1000, 1))
  
  x_test = np.random.random ((100, 20))
  
  y_test = np.random.randint (2, size = (100, 1))
  model.fit(x_train, y_train,epochs=10,batch_size=128,verbose=1)
  
  score = model.evaluate(x_test, y_test, batch_size=128)
  print(score)
  
  
  