class_docstr: `FeatureConnector` for voxel grids.
  
  During `_generate_examples`, the feature connector accepts as input any of:
  
    * `dict`: dictionary containing the path to a {.mat} file and the key under
    which the voxel grid is accessible inside the file.
    Structure of the dictionary:
      {
      'path': 'path/to/file.mat',
      'key': 'foo'
      }
  
    * `np.ndarray`: float32 numpy array of shape [X,Y,Z] representing the
    voxel grid.
  
  Output:
    A float32 Tensor with shape [X,Y,Z] containing the voxel occupancies.
code: def to_json_content(self):
      return {
          "shape": list(self._shape),
      }
  
file_path: graphics/tensorflow_graphics/datasets/features/voxel_feature.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import numpy
  from scipy import io
  import tensorflow
  from tensorflow_datasets import features
label_desc: Use image node_id 4 for calling the VoxelGrid obj's underlying member method code with example usage: obj.to_json_content() and returns: dict