code: def setup(self, size, contig, module):
      if module == "numpy" and size >= 200:
          # skip: slow, and not useful to benchmark numpy
          raise NotImplementedError()
  
      a = random([size, size])
      # larger diagonal ensures non-singularity:
      for i in range(size):
          a[i, i] = 10 * (0.1 + a[i, i])
      b = random([size])
  
      if contig != "contig":
          a = a[-1::-1, -1::-1]  # turn into a non-contiguous array
          assert_(not a.flags["CONTIGUOUS"])
  
      self.a = a
      self.b = b
  
imports: import math
  import numpy.linalg
  import numpy
  from numpy.testing import assert_
  from numpy.random import rand
  from .common import Benchmark, safe_import
label_desc: Use image node_id 2 for calling the Bench obj's underlying member method code with example usage: obj.setup(size, contig, module) without return types