code: def error_inputs_exponential_window(op_info, device, **kwargs):
      # Yield common error inputs
      yield from error_inputs_window(op_info, device, **kwargs)
  
      # Tests for negative decay values.
      yield ErrorInput(
          SampleInput(
              3, tau=-1, dtype=torch.float32, device=device, **kwargs
          ),
          error_type=ValueError,
          error_regex="Tau must be positive, got: -1 instead.",
      )
  
      # Tests for symmetric windows and a given center value.
      yield ErrorInput(
          SampleInput(
              3, center=1, sym=True, dtype=torch.float32, device=device
          ),
          error_type=ValueError,
          error_regex="Center must be None for symmetric windows",
      )
  
imports: import unittest
  from functools import partial
  from itertools import product
  from typing import Callable, List, Tuple
  import numpy
  import torch
  from torch.testing._internal.common_dtype import floating_types
  from torch.testing._internal.common_utils import TEST_SCIPY
  from torch.testing._internal.opinfo.core import DecorateInfo, ErrorInput, OpInfo, SampleInput
label_desc: Use image node_id 9 for calling a global function with example usage: error_inputs_exponential_window(op_info, device) without return types