new_contents: import tflearn
  from tflearn.layers.core import input_data, dropout, fully_connected
  from tflearn.layers.conv import conv_2d, max_pool_2d
  from tflearn.layers.estimator import regression
  
  # Data loading and preprocessing
  import tflearn.datasets.oxflower17 as oxflower17
  X, Y = oxflower17.load_data(one_hot=True)
  
  # Building 'VGG Network'
  network = input_data(shape=[None, 224, 224, 3])
  
  network = conv_2d(network, 64, 3, activation='relu')
  network = conv_2d(network, 64, 3, activation='relu')
  network = max_pool_2d(network, 2, strides=2)
  
  network = conv_2d(network, 128, 3, activation='relu')
  network = conv_2d(network, 128, 3, activation='relu')
  network = max_pool_2d(network, 2, strides=2)
  
  network = conv_2d(network, 256, 3, activation='relu')
  network = conv_2d(network, 256, 3, activation='relu')
  network = conv_2d(network, 256, 3, activation='relu')
  network = max_pool_2d(network, 2, strides=2)
  
  network = conv_2d(network, 512, 3, activation='relu')
  network = conv_2d(network, 512, 3, activation='relu')
  network = conv_2d(network, 512, 3, activation='relu')
  network = max_pool_2d(network, 2, strides=2)
  
  network = conv_2d(network, 512, 3, activation='relu')
  network = conv_2d(network, 512, 3, activation='relu')
  network = conv_2d(network, 512, 3, activation='relu')
  network = max_pool_2d(network, 2, strides=2)
  
  network = fully_connected(network, 4096, activation='relu')
  network = dropout(network, 0.5)
  network = fully_connected(network, 4096, activation='relu')
  network = dropout(network, 0.5)
  network = fully_connected(network, 17, activation='softmax')
  
  network = regression(network, optimizer='rmsprop',
                       loss='categorical_crossentropy',
                       learning_rate=0.001)
  
  # Training
  model = tflearn.DNN(network, checkpoint_path='model_vgg',
                      max_checkpoints=1, tensorboard_verbose=0)
  model.fit(X, Y, n_epoch=500, shuffle=True,
            show_metric=True, batch_size=32, snapshot_step=500,
            snapshot_epoch=False, run_id='vgg_oxflowers17')
  
subject: Create VGGNet.py