code: def tt_matrix_to_tensor(tt_matrix):
      """Returns the full tensor whose TT-Matrix decomposition is given by 'factors'
  
          Re-assembles 'factors', which represent a tensor in TT-Matrix format
          into the corresponding full tensor
  
      Parameters
      ----------
      factors: list of 4D-arrays
                TT-Matrix factors (known as core) of shape (rank_k, left_dim_k, right_dim_k, rank_{k+1})
  
      Returns
      -------
      output_tensor: ndarray
                     tensor whose TT-Matrix decomposition was given by 'factors'
      """
      # Each core is of shape (rank_left, size_in, size_out, rank_right)
      _, in_shape, out_shape, _ = zip(*(tl.shape(f) for f in tt_matrix))
      ndim = len(in_shape)
  
      # Intertwine the dims
      # full_shape = in_shape[0], out_shape[0], in_shape[1], ...
      full_shape = sum(zip(*(in_shape, out_shape)), ())
      order = list(range(0, ndim * 2, 2)) + list(range(1, ndim * 2, 2))
  
      for i, factor in enumerate(tt_matrix):
          if not i:
              res = factor
          else:
              res = tensordot(res, factor, ([-1], [0]))
  
      return tl.transpose(tl.reshape(res, full_shape), order)
  
label_desc: Use image node_id 1 for calling a global function with example usage: tt_matrix_to_tensor(tt_matrix) and returns: tl