class_docstr: TT decomposition via recursive SVD
  
      Decomposes `input_tensor` into a sequence of order-3 tensors (factors)
      -- also known as Tensor-Train decomposition [1]_.
  
  Parameters
  ----------
  input_tensor : tensorly.tensor
  rank : {int, int list}
          maximum allowable TT rank of the factors
          if int, then this is the same for all the factors
          if int list, then rank[k] is the rank of the kth factor
  svd : str, default is 'truncated_svd'
      function to use to compute the SVD, acceptable values in tensorly.SVD_FUNS
  verbose : boolean, optional
          level of verbosity
  
  Returns
  -------
  factors : TT factors
          order-3 tensors of the TT decomposition
  
  References
  ----------
  .. [1] Ivan V. Oseledets. "Tensor-train decomposition", SIAM J. Scientific Computing, 33(5):2295–2317, 2011.
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code: def __init__(self, rank, svd="truncated_svd", verbose=False):
      self.rank = rank
      self.svd = svd
      self.verbose = verbose
  
file_path: tensorly/tensorly/decomposition/_tt.py
imports: import tensorly
  from ._base_decomposition import DecompositionMixin
  from ..tt_tensor import validate_tt_rank, TTTensor
  from ..tt_matrix import validate_tt_matrix_rank, TTMatrix
  from ..tenalg.svd import svd_interface
label_desc: Use image node_id 1 to create a new TensorTrainMatrix object from inherited base classes: DecompositionMixin with example: obj = TensorTrainMatrix(rank, svd, verbose)