old_contents: from __future__ import division, absolute_import, print_function
  
  import numpy as np
  
  try:
      import scipy.linalg.lapack as la
      import scipy.linalg.blas as bla
  except ImportError:
      pass
  
  from .common import Benchmark
  
  
  class GetBlasLapackFuncs(Benchmark):
      """
      Test the speed of grabbing the correct BLAS/LAPACK routine flavor.
  
      In particular, upon receiving strange dtype arrays the results shouldn't
      diverge too much. Hence the results here should be comparable
      """
  
      param_names = ['dtype1', 'dtype2',
                     'dtype1_ord', 'dtype2_ord',
                     'size']
      params = [
          ['b', 'G', 'd'],
          ['d', 'F', '?'],
          ['C', 'F'],
          ['C', 'F'],
          [10, 100, 1000]
      ]
  
      def setup(self, dtype1, dtype2, dtype1_ord, dtype2_ord, size):
          self.arr1 = np.empty(size, dtype=dtype1, order=dtype1_ord)
          self.arr2 = np.empty(size, dtype=dtype2, order=dtype2_ord)
  
      def time_find_best_blas_type(self, arr1, arr2):
          prefix, dtype, prefer_fortran = bla.find_best_blas_type((arr1, arr2))
  
new_contents: from __future__ import division, absolute_import, print_function
  
  import numpy as np
  
  try:
      import scipy.linalg.lapack as la
      import scipy.linalg.blas as bla
  except ImportError:
      pass
  
  from .common import Benchmark
  
  
  class GetBlasLapackFuncs(Benchmark):
      """
      Test the speed of grabbing the correct BLAS/LAPACK routine flavor.
  
      In particular, upon receiving strange dtype arrays the results shouldn't
      diverge too much. Hence the results here should be comparable
      """
  
      param_names = ['dtype1', 'dtype2',
                     'dtype1_ord', 'dtype2_ord',
                     'size']
      params = [
          ['b', 'G', 'd'],
          ['d', 'F', '?'],
          ['C', 'F'],
          ['C', 'F'],
          [10, 100, 1000]
      ]
  
      def setup(self, dtype1, dtype2, dtype1_ord, dtype2_ord, size):
          self.arr1 = np.empty(size, dtype=dtype1, order=dtype1_ord)
          self.arr2 = np.empty(size, dtype=dtype2, order=dtype2_ord)
  
      def time_find_best_blas_type(self, dtype1, dtype2, dtype1_ord, dtype2_ord, size):
          prefix, dtype, prefer_fortran = bla.find_best_blas_type((self.arr1, self.arr2))
  
subject: fix invalid benchmark syntax