code: def test_dtw_path_with_empty_or_nan_inputs():
      for be in backends:
          for array_type in array_types:
              s1 = cast(np.zeros((3, 10)), array_type)
              s2_empty = cast(np.zeros((0, 10)), array_type)
              with pytest.raises(ValueError) as excinfo:
                  dtw_path(s1, s2_empty, be=be)
              assert (
                  str(excinfo.value)
                  == "One of the input time series contains only nans or has zero length."
              )
  
              s2_nan = cast(np.full((3, 10), np.nan), array_type)
              with pytest.raises(ValueError) as excinfo:
                  dtw_path(s1, s2_nan, be=be)
              assert (
                  str(excinfo.value)
                  == "One of the input time series contains only nans or has zero length."
              )
  
imports: import platform
  import sys
  import numpy
  import pytest
  import tslearn.clustering
  import tslearn.metrics
  from scipy.spatial.distance import cdist
  from tslearn.backend.backend import Backend, cast, instantiate_backend
  from tslearn.metrics.dtw_variants import dtw_path
  from tslearn.utils import to_time_series
label_desc: Use image node_id 17 for calling a global function with example usage: test_dtw_path_with_empty_or_nan_inputs() without return types