input: Write a python function to preprocess the MNIST dataset by normalizing pixel values and reshaping the data.
  assert preprocess_mnist(X_train, X_test) == (X_train_normalized, X_test_normalized)
  assert X_train_normalized.shape == (60000, 784)
  assert X_test_normalized.shape == (10000, 784)
output: def preprocess_mnist(X_train, X_test):
      # Normalize pixel values
      X_train_normalized = X_train.astype('float32') / 255.0
      X_test_normalized = X_test.astype('float32') / 255.0
  
      # Reshape data
      X_train_normalized = X_train_normalized.reshape((X_train.shape[0], -1))
      X_test_normalized = X_test_normalized.reshape((X_test.shape[0], -1))
      
      return X_train_normalized, X_test_normalized