docstr: Return the unfolding matrix of a tensor given in TT (or Tensor-
  Train) format.
  
  Reassembles a full tensor from 'factors' and returns its unfolding matrix
  with mode given by 'mode'
  
  Parameters
  ----------
  factors
      TT factors
  mode
      unfolding matrix to be computed along this mode
  
  Returns
  -------
  2-D array
  unfolding matrix at mode given by 'mode'
docstr_tok: ["Return","the","unfolding","matrix","of","a","tensor","given","in","TT","(","or","Tensor-","Train",")","format",".","Reassembles","a","full","tensor","from","'factors","'","and","returns","its","unfolding","matrix","with","mode","given","by","'mode'","Parameters","--","--","--","--","--","factors","TT","factors","mode","unfolding","matrix","to","be","computed","along","this","mode","Returns","--","--","--","-","2-D","array","unfolding","matrix","at","mode","given","by","'mode","'"]
code: def tt_to_unfolded(factors, mode):
      """Return the unfolding matrix of a tensor given in TT (or Tensor-
      Train) format.
  
      Reassembles a full tensor from 'factors' and returns its unfolding matrix
      with mode given by 'mode'
  
      Parameters
      ----------
      factors
          TT factors
      mode
          unfolding matrix to be computed along this mode
  
      Returns
      -------
      2-D array
      unfolding matrix at mode given by 'mode'
      """
      return ivy.unfold(ivy.TTTensor.tt_to_tensor(factors), mode)
  
imports: from .base import FactorizedTensor
  import ivy
  import warnings
label_desc: Use image node_id 13 for calling the TTTensor obj's underlying member method code with example usage: obj.tt_to_unfolded(factors, mode) and returns: ivy