import tensorflow as tf
import tensorflow_datasets as tfds

new_model = tf.keras.models.load_model('hdf5_models/fully trainable VGG16 base model.h5')
new_model.summary()
ds_train, ds_test = tfds.load(
    'svhn_cropped', 
    split=['train', 'test'],
    shuffle_files=True, 
    as_supervised=True
    )

loss, acc = new_model.evaluate(ds_test, verbose=2)
print('Restored model, accuracy: {:5.2f}%'.format(100 * acc))