class_docstr: CenterNet network using Hourglass from https://arxiv.org/abs/1904.07850S.
class_docstr_tok: ["CenterNet","network","using","Hourglass","from","https",":","\/\/arxiv.org\/abs\/1904.07850S","."]
code: def recover_sample_dimensions(outputs, sample_shape):
      for ii in range(len(outputs)):
          for key in outputs[ii]:
              output_shape = tf.shape(outputs[ii][key])
              outputs[ii][key] = tf.reshape(
                  outputs[ii][key],
                  tf.concat(
                      [sample_shape[:3], output_shape[1:]], axis=0
                  ),
              )
      return outputs
  
imports: import collections
  import os
  import random
  import string
  import time
  from absl import logging
  import numpy
  import tensorflow
  from tensorflow_graphics.projects.points_to_3Dobjects.models import centernet_utils
  from tensorflow_graphics.projects.points_to_3Dobjects.networks import hourglass
  from tensorflow_graphics.projects.points_to_3Dobjects.transforms import transforms
  from tensorflow_graphics.projects.points_to_3Dobjects.utils import image
  from google3.pyglib import gfile
label_desc: Use image node_id 7 for calling the CenterNetVID obj's underlying member method code with example usage: obj.recover_sample_dimensions(outputs, sample_shape) and returns: outputs