code: def tucker_copy(self):
      return TuckerTensor(
          (
              tl.copy(self.core),
              [
                  tl.copy(self.factors[i])
                  for i in range(len(self.factors))
              ],
          )
      )
  
imports: from ._factorized_tensor import FactorizedTensor
  from .base import unfold, tensor_to_vec
  from .tenalg import multi_mode_dot, mode_dot
  from .None import backend
  import numpy
  from scipy.optimize import brentq
  import warnings
label_desc: Use image node_id 9 for calling the TuckerTensor obj's underlying member method code with example usage: obj.tucker_copy() and returns: TuckerTensor