code: def setup(self, dtype_in, N, order):
      with warnings.catch_warnings():
          warnings.filterwarnings("ignore", "Possible precision loss")
          self.image = convert(np.random.random((N, N)), dtype=dtype_in)
      self.tform = SimilarityTransform(
          scale=1, rotation=np.pi / 10, translation=(0, 4)
      )
      self.tform.params = self.tform.params.astype("float32")
      self.order = order
  
      if "dtype" in inspect.signature(warp).parameters:
          self.warp = functools.partial(warp, dtype=self.image.dtype)
      else:
          # Keep a call to functools to have the same number of python
          # function calls
          self.warp = functools.partial(warp)
  
file_path: scikit-image/benchmarks/benchmark_transform_warp.py
imports: import numpy
  from skimage.transform import SimilarityTransform, warp, resize_local_mean
  import warnings
  import functools
  import inspect
label_desc: Use image node_id 1 for calling the WarpSuite obj's underlying member method code with example usage: obj.setup(dtype_in, N, order) without return types