input: 
  from sklearn.svm import SVC
  import numpy as np
  
  def train_and_test_classifier() -> np.ndarray:
      """Train a Support Vector Machine (SVM) classifier to distinguish between apples and bananas using given data. Then, test the classifier with new data and return the predictions.
      >>> train_and_test_classifier()
      array([0, 1])
          """
      # Load data
      X = np.array([[1,2,3], [-1,2,5], [-1,2,7], [5,5,5], [3,3,3], [5,5,7]])
      y = np.array([0, 0, 0, 1, 0, 1])
  
      # Initialize classifier
      clf = SVC(kernel='linear')
  
      # Fit data
      clf.fit(X, y)
  
      # Test classifier
      x_test = np.array([[2,2,2], [4,4,4]])
  
      prediction = clf.predict(x_test)
      return prediction
  
output:     return prediction