code: def set_default_positive_minimum(value: float) -> None:
      """Sets shift constant for positive transformation."""
      if not (
          isinstance(value, (tf.Tensor, np.ndarray))
          and len(value.shape) == 0
      ) and not isinstance(value, float):
          raise TypeError("Expected float32 or float64 scalar value")
  
      if value < 0:
          raise ValueError("Positive minimum must be non-negative")
  
      set_config(replace(config(), positive_minimum=value))
  
imports: import contextlib
  import os
  from dataclasses import dataclass, field, replace
  from typing import Any, Dict, Generator, List, Mapping, Optional, Union
  import numpy
  import tabulate
  import tensorflow
  import tensorflow_probability
label_desc: Use image node_id 23 for calling a global function with example usage: set_default_positive_minimum(value) without return types