import tensorflow as tf

  }
  example_proto = tf.train.Example(features=tf.train.Features(feature=feature))
  return example_proto.SerializeToString()


def full_featurespec():
  return {
      'bounding_box_samples': tf.io.FixedLenFeature([100000, 4], tf.float32),
      'depth_renders': tf.io.FixedLenFeature([20, 224, 224, 1], tf.float32),
      'mesh_name': tf.io.FixedLenFeature([], tf.string),
      'near_surface_samples': tf.io.FixedLenFeature([100000, 4], tf.float32),
      'grid': tf.io.FixedLenFeature([32, 32, 32], tf.float32),
      'world2grid': tf.io.FixedLenFeature([4, 4], tf.float32),
      'surface_point_samples': tf.io.FixedLenFeature([10000, 6], tf.float32)
  }


def parse_tf_example(example_proto):
