input: Write a python function to fit a logistic regression model using sklearn and predict a new data point.
  assert fit_and_predict([[0,0], [0,1], [1,0], [1,1]], [1,1,0,1], [[2,2]]) == [1]
  assert fit_and_predict([[1,1], [2,2], [3,3], [4,4]], [0,1,0,1], [[5,5]]) == [1]
  assert fit_and_predict([[0,0], [1,1], [2,2], [3,3]], [0,1,0,1], [[0,1]]) == [1]
output: def fit_and_predict(X_train, y_train, X_test):
      from sklearn.linear_model import LogisticRegression
      model = LogisticRegression()
      model.fit(X_train, y_train)
      return model.predict(X_test).tolist()