old_contents: import numpy as np
  from numpy import eye
  from numpy.linalg import LinAlgError
  import fblas
  
  from scipy.sparse.base import isspmatrix
  from scipy.sparse.construct import eye as speye
  
  
  __all__ = ['LinAlgError', 'norm']
  
  _nrm2_prefix = {'f' : 's', 'F': 'sc', 'D': 'dz'}
  
  def norm(a, ord=None):
      # Differs from numpy only in non-finite handling and the use of
      # blas
      a = np.asarray_chkfinite(a)
      if ord in (None, 2) and (a.ndim == 1) and (a.dtype.char in 'fdFD'):
          # use blas for fast and stable euclidean norm
          func_name = _nrm2_prefix.get(a.dtype.char, 'd') + 'nrm2'
          nrm2 = getattr(fblas, func_name)
          return nrm2(a)
      return np.linalg.norm(a, ord=ord)
  
  norm.__doc__ = np.linalg.norm.__doc__
  
  def _datacopied(arr, original):
      """
      Strict check for `arr` not sharing any data with `original`,
      under the assumption that arr = asarray(original)
  
      """
      if arr is original:
          return False
      if not isinstance(original, np.ndarray) and hasattr(original, '__array__'):
          return False
      return arr.base is None
  
new_contents: import numpy as np
  from numpy.linalg import LinAlgError
  import fblas
  
  __all__ = ['LinAlgError', 'norm']
  
  _nrm2_prefix = {'f' : 's', 'F': 'sc', 'D': 'dz'}
  
  def norm(a, ord=None):
      # Differs from numpy only in non-finite handling and the use of
      # blas
      a = np.asarray_chkfinite(a)
      if ord in (None, 2) and (a.ndim == 1) and (a.dtype.char in 'fdFD'):
          # use blas for fast and stable euclidean norm
          func_name = _nrm2_prefix.get(a.dtype.char, 'd') + 'nrm2'
          nrm2 = getattr(fblas, func_name)
          return nrm2(a)
      return np.linalg.norm(a, ord=ord)
  
  norm.__doc__ = np.linalg.norm.__doc__
  
  def _datacopied(arr, original):
      """
      Strict check for `arr` not sharing any data with `original`,
      under the assumption that arr = asarray(original)
  
      """
      if arr is original:
          return False
      if not isinstance(original, np.ndarray) and hasattr(original, '__array__'):
          return False
      return arr.base is None
  
subject: remove unused imports