code: def voxel_proto_get(element):
      """Extracts the contents from a VoxelSample proto to tensors."""
      _, values = decode_proto(
          element,
          "giotto_blender.VoxelSample",
          ["name", "voxel_data", "size", "obj_bbox"],
          [tf.string, tf.string, tf.int32, tf.float32],
      )
      filename = tf.squeeze(values[0])
      volume_raw = values[1]
      voxel_size = values[2]
      obj_bbox = values[3]
  
      voxels = tf.io.decode_raw(volume_raw, out_type=tf.uint8)
      voxels = (
          tf.cast(tf.reshape(voxels, voxel_size), tf.float32) / 255.0
      )
      return filename, voxels, voxel_size, obj_bbox
  
file_path: graphics/tensorflow_graphics/projects/neural_voxel_renderer/prepare_tfrecords/generate_tfrecords_nvr_plus.py
imports: import os
  import re
  from absl import app
  from absl import flags
  import numpy
  import tensorflow
  from tensorflow_graphics.projects.neural_voxel_renderer import helpers
  from tensorflow_graphics.projects.neural_voxel_renderer.prepare_tfrecords import data_pb2
label_desc: Use image node_id 1 for calling a global function with example usage: voxel_proto_get(element) and returns: filename,  voxels,  voxel_size,  obj_bbox