title: Using keras flow_from_directory when running on google cloud machine learning engine
body: <p>I would like to train my keras model on google cloud machine learning engine. I am currently using image augmentation and grabbing images from a local directory.</p>
  
  <pre><code>    train_datagen =  ImageDataGenerator(
        preprocessing_function=preprocess_input,
        rotation_range=30,
        width_shift_range=0.2,
        height_shift_range=0.2,
        shear_range=0.2,
        zoom_range=0.2,
        horizontal_flip=True
    )
  
      train_generator = train_datagen.flow_from_directory(
        args.train_dir,
      target_size=(IM_WIDTH, IM_HEIGHT),
      batch_size=batch_size,
    )
  </code></pre>
  
  <p>Is it possible to achieve this behavior on google cloud bucket? Could I first download the images to a local machine? I'm seeing alot of people using pickle on ML engine, but that doesn't quite make sense since images are 'generated' at the time of training.</p>