code: def regularize_array(A):
      
      if not isinstance(A,np.ndarray):
          A = np.array(A, dtype=float)
      else:
          A = np.asarray(A, dtype=float)
  
      if len(A.shape) <= 1:
          return A.reshape(-1,1)
  
      elif A.shape[-1]>1:
          return A.reshape(-1, A.shape[-1])
  
      else:
          return A
docs: Takes an np.ndarray as an input.
  
  
      - If the array is one-dimensional, it's assumed to be an array of input values.
  
      - If the array is more than one-dimensional, its last index is assumed to curse
        over spatial dimension.
  
  
      Either way, the return value is at least two dimensional. A.shape[-1] gives the
      number of spatial dimensions.