input: Write a function to evaluate the accuracy of a machine-learning model using sklearn. The function should accept the trained model and the test data as inputs, and return the accuracy of the model on the test data. If the test data is empty, the function should return 0.
  assert evaluate_accuracy(clf, X_test, y_test)==0.85
  assert evaluate_accuracy(clf, [], y_test)==0
  assert evaluate_accuracy(clf, X_test, [])==0
  assert evaluate_accuracy(clf, [], [])==0
output: def evaluate_accuracy(model, X_test, y_test):
      if not X_test or not y_test:
          return 0
      return model.score(X_test, y_test)