input: Write a function to develop a machine learning algorithm in Python that identifies apples from bananas using a Support Vector Machine (SVM) with a linear kernel. The function should take no input, load the given data, train the classifier, and then test the classifier with given test data. It should print the predictions for the given test data.
  
  
  assert apple_banana_classifier()==[0 1]
  
output: def apple_banana_classifier():
      import numpy as np
      from sklearn import svm
      from sklearn.datasets import load_iris
      from sklearn.model_selection import train_test_split
  
      data = load_iris()
      X = data.data
      y = data.target
  
      X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
  
      clf = svm.SVC(kernel='linear')
      clf.fit(X_train, y_train)
  
      predictions = clf.predict(X_test)
      print(predictions)
      return predictions