input: from typing import Tuple
  
  def evaluate_model_accuracy(clf: SVC, X_train, y_train, X_test, y_test) -> float:
      """ Evaluate the accuracy of a given machine-learning model.
      >>> from sklearn.svm import SVC
      >>> clf = SVC(kernel='poly', degree=2, gamma=0.05)
      >>> X_train, y_train, X_test, y_test = np.array([[1,2],[2,3]]), np.array([1,2]), np.array([[1,1]]), np.array([1])
      >>> evaluate_model_accuracy(clf, X_train, y_train, X_test, y_test)
      0.0
      """
      clf.fit(X_train, y_train)
      y_pred = clf.predict(X_test)
      return accuracy_score(y_test, y_pred)
output:     from sklearn.metrics import accuracy_score