input: Write a python function to create and train a simple neural network using Keras.
  assert isinstance(create_and_train_model(x, y), keras.engine.sequential.Sequential)
  assert create_and_train_model(x, y).layers[0].units == 10
  assert create_and_train_model(x, y).layers[-1].activation.__name__ == 'sigmoid'
output: def create_and_train_model(x, y):
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense
  
      # Define the model
      model = Sequential()
      model.add(Dense(10, input_dim=x.shape[1], activation='relu'))
      model.add(Dense(1, activation='sigmoid'))
  
      # Compile the model
      model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
  
      # Train the model
      model.fit(x, y, epochs=10, batch_size=32, verbose=0)
  
      return model