class_docstr: Class for using optimization to acquire feature grid.
class_docstr_tok: ["Class","for","using","optimization","to","acquire","feature","grid","."]
code: def _initialize_uninitialized(self, sess):
      global_vars = tf.global_variables()
      is_not_initialized = sess.run(
          [tf.is_variable_initialized(var) for var in global_vars]
      )
      not_initialized_vars = [
          v for (v, f) in zip(global_vars, is_not_initialized) if not f
      ]
  
      if not_initialized_vars:
          sess.run(tf.variables_initializer(not_initialized_vars))
  
imports: import os
  import numpy
  from skimage import measure
  import tensorflow.compat.v1
  from tensorflow_graphics.projects.local_implicit_grid.core import evaluator
  from tensorflow_graphics.projects.local_implicit_grid.core import local_implicit_grid_layer
  from tensorflow_graphics.projects.local_implicit_grid.core import point_utils
label_desc: Use image node_id 5 for calling the LIGOptimizer obj's underlying member method code with example usage: obj._initialize_uninitialized(sess) without return types