class_docstr: Load pretrained refiner and evaluate for a given code.
    
class_docstr_tok: ["Load","pretrained","refiner","and","evaluate","for","a","given","code","."]
code: def _get_grid_points(self, xmin, xmax, res):
      x = np.linspace(xmin, xmax, res)
      xyz = np.meshgrid(*tuple([x] * self.dim), indexing="ij")
      xyz = np.stack(xyz, axis=-1)
      xyz = xyz.reshape([-1, self.dim])
      return xyz
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import ast
  import numpy
  import tensorflow.compat.v1
  from tensorflow.compat.v1.io import gfile
  from tensorflow_graphics.projects.local_implicit_grid.core import implicit_nets
  from tensorflow_graphics.projects.local_implicit_grid.core import local_implicit_grid_layer
  from tensorflow_graphics.projects.local_implicit_grid.core import model_g2g
  from tensorflow_graphics.projects.local_implicit_grid.core import model_g2v
label_desc: Use image node_id 3 for calling the RefinerEvaluator obj's underlying member method code with example usage: obj._get_grid_points(xmin, xmax, res) and returns: xyz