code: def _sample_sizes(
      strategy: str,
      rng: np.random.RandomState,
  ) -> Tuple[Optional[str], float]:
      """Samples an object's size.
  
      Args:
        strategy: Sampling strategy.
        rng: Source of randomness.
  
      Returns:
        size_label: Human-readable description of "size".
        size: Size multiplier. Use as object scale.
      """
      if strategy == "clevr":
          size_label = rng.choice(list(SIZES.keys()))
          size = SIZES[size_label]
          return size_label, size
      elif strategy == "uniform":
          return None, rng.uniform(0.7, 1.4)
      elif strategy == "const":
          return None, 1
      else:
          raise ValueError(f"Unknown size sampling strategy {strategy}")
  
file_path: kubric/challenges/robust_nerf/worker.py
imports: import collections
  import json
  import logging
  from typing import Dict, List, Optional, Tuple
  import kubric
  import kubric.renderer.blender
  import kubric.simulator.pybullet
  import numpy
  import tensorflow
  import bpy
label_desc: Use image node_id 3 for calling a global function with example usage: _sample_sizes(strategy, rng) and returns: size_label,  size, None,  rng, None,  int