dataset_generator.py

featdef = {
           'image': tf.FixedLenFeature(shape=[], dtype=tf.string),
           'weather_labels': tf.FixedLenFeature(shape=[], dtype=tf.string),
           'ground_labels': tf.FixedLenFeature(shape=[], dtype=tf.string)
          }
          
 def _parse_record(example_proto, clip=False):
    """Parse a single record into image, weather labels, ground labels"""
    example = tf.parse_single_example(example_proto, featdef)
    im = tf.decode_raw(example['image'], tf.float32)
    im = tf.reshape(im, (IM_SIZE, IM_SIZE, 3))
    weather = tf.decode_raw(ex['weather_labels'], tf.float32)
    ground = tf.decode_raw(ex['ground_labels'], tf.float32)
    return im, weather, ground

# Construct a TFRecordDataset
ds_train = tf.data.TFRecordDataset('./data/KagglePlanetTFRecord_{}'.format(IM_SIZE)).map(_parse_record)
ds_train = ds_train.shuffle(1000).batch(32)

The 12th and 13th lines, the 'ex' should be 'example'.