code: def test_scalar_to_support_out_of_range():
      f = io.StringIO()
      with redirect_stdout(f):
          scalar = torch.scalar_tensor(11.0)
          scalar_to_support(scalar=scalar, support_range=(-10, 10))
  
      std_output = f.getvalue()
      assert (
          "WARNING: scalar 11.0 is our of support range (-10, 10)!"
          in std_output
      )
  
      f = io.StringIO()
      with redirect_stdout(f):
          scalar = torch.from_numpy(
              np.asarray([11.0, 8.0], dtype=np.float32)
          )
          scalar_to_support(scalar=scalar, support_range=(-10, 10))
  
      std_output = f.getvalue()
      assert (
          "WARNING: scalar tensor([11.,  8.]) is our of support range (-10, 10)!"
          in std_output
      )
  
file_path: maze/maze/test/train/common/test_value_transform.py
imports: import io
  from contextlib import redirect_stdout
  import numpy
  import torch
  from maze.train.trainers.common.value_transform import support_to_scalar, scalar_to_support, ReduceScaleValueTransform
label_desc: Use image node_id 4 for calling a global function with example usage: test_scalar_to_support_out_of_range() without return types