code: def sampling_points_from_3d_grid(grid_size, dtype=tf.float32):
      """Returns a tensor of shape `[M, 3]`, with M the number of sampling points."""
      sampling_points = grid.generate(
          (-1.0, -1.0, -1.0), (1.0, 1.0, 1.0), grid_size
      )
      sampling_points = tf.cast(sampling_points, dtype)
      return tf.reshape(sampling_points, [-1, 3])
  
file_path: graphics/tensorflow_graphics/projects/neural_voxel_renderer/helpers.py
imports: import numpy
  import tensorflow
  from tensorflow_graphics.geometry.representation import grid
  from tensorflow_graphics.geometry.transformation import rotation_matrix_3d
  from tensorflow_graphics.math.interpolation import trilinear
  from tensorflow_graphics.rendering.camera import perspective
  from tensorflow_graphics.rendering.volumetric import emission_absorption
label_desc: Use image node_id 3 for calling a global function with example usage: sampling_points_from_3d_grid(grid_size, dtype) and returns: tf