code: def min_rank_for_support(support):
      """Reports the minimum rank of a Tensor in the given support."""
      if support.startswith("SCALAR_"):
          return 0
      if support.startswith("VECTOR_"):
          return 1
      if support.startswith("MATRIX_"):
          return 2
      raise NotImplementedError(support)
  
imports: import contextlib
  import os
  import re
  import traceback
  import unittest
  import hypothesis
  from hypothesis.extra import numpy
  import hypothesis.strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.util.deferred_tensor import DeferredTensor
label_desc: Use image node_id 17 for calling a global function with example usage: min_rank_for_support(support) and returns: int, int, int