code: def setup(self, mode):
      rng = np.random.default_rng(1234)
      # sample a bunch of pairs of 2d arrays
      pairs = {"1d": [], "2d": []}
      for ma, nb in product((1, 2, 8, 13, 30, 36, 50, 75), repeat=2):
          a = rng.standard_normal(ma)
          b = rng.standard_normal(nb)
          pairs["1d"].append((a, b))
  
      for n_image in [256, 512, 1024]:
          for n_kernel in [3, 5, 7]:
              x = rng.standard_normal((n_image, n_image))
              h = rng.standard_normal((n_kernel, n_kernel))
              pairs["2d"].append((x, h))
      self.pairs = pairs
  
imports: from itertools import product
  import numpy
  from .common import Benchmark, safe_import
label_desc: Use image node_id 1 for calling the Convolve obj's underlying member method code with example usage: obj.setup(mode) without return types