old_contents: from t3f.tensor_train_base import TensorTrainBase
  from t3f.tensor_train import TensorTrain
  from t3f.tensor_train_batch import TensorTrainBatch
  
  from t3f.variables import assign
  from t3f.variables import get_variable
  
  from t3f.ops import add
  from t3f.ops import cast
  from t3f.ops import flat_inner
  from t3f.ops import frobenius_norm
  from t3f.ops import frobenius_norm_squared
  from t3f.ops import full
  from t3f.ops import matmul
  from t3f.ops import multiply
  from t3f.ops import quadratic_form
  from t3f.ops import transpose
  from t3f.ops import gather_nd
  
  from t3f.batch_ops import concat_along_batch_dim
  from t3f.batch_ops import gram_matrix
  from t3f.batch_ops import multiply_along_batch_dim
  from t3f.batch_ops import pairwise_flat_inner
  
  from t3f.initializers import random_matrix
  from t3f.initializers import random_matrix_batch
  from t3f.initializers import random_tensor
  from t3f.initializers import random_tensor_batch
  
  from t3f.regularizers import cores_regularizer
  from t3f.regularizers import l2_regularizer
  
  from t3f.riemannian import add_n_projected
  from t3f.riemannian import pairwise_flat_inner_projected
  from t3f.riemannian import project
  from t3f.riemannian import project_matmul
  from t3f.riemannian import project_sum
  
  from t3f.shapes import batch_size
  from t3f.shapes import clean_raw_shape
  from t3f.shapes import expand_batch_dim
  from t3f.shapes import is_batch_broadcasting_possible
  from t3f.shapes import lazy_batch_size
  from t3f.shapes import lazy_raw_shape
  from t3f.shapes import lazy_shape
  from t3f.shapes import lazy_tt_ranks
  from t3f.shapes import raw_shape
  from t3f.shapes import shape
  from t3f.shapes import squeeze_batch_dim
  from t3f.shapes import tt_ranks
  
  from t3f.decompositions import orthogonalize_tt_cores
  from t3f.decompositions import round
  from t3f.decompositions import to_tt_matrix
  from t3f.decompositions import to_tt_tensor
  
  import t3f.kronecker as kronecker
  import t3f.utils as utils
  
  _directly_imported = ['tensor_train_base', 'tensor_train', 'tensor_train_batch',
                        'variables', 'ops', 'batch_ops', 'initializers',
                        'regularizers', 'riemannian', 'shapes', 'decompositions']
  
  __all__ = [s for s in dir() if
             s not in _directly_imported and not s.startswith('_')]
  
new_contents: from t3f.tensor_train_base import TensorTrainBase
  from t3f.tensor_train import TensorTrain
  from t3f.tensor_train_batch import TensorTrainBatch
  
  from t3f.variables import assign
  from t3f.variables import get_variable
  
  from t3f.ops import add
  from t3f.ops import cast
  from t3f.ops import flat_inner
  from t3f.ops import frobenius_norm
  from t3f.ops import frobenius_norm_squared
  from t3f.ops import full
  from t3f.ops import matmul
  from t3f.ops import multiply
  from t3f.ops import quadratic_form
  from t3f.ops import transpose
  from t3f.ops import gather_nd
  from t3f.ops import renormalize_tt_cores
  
  from t3f.batch_ops import concat_along_batch_dim
  from t3f.batch_ops import gram_matrix
  from t3f.batch_ops import multiply_along_batch_dim
  from t3f.batch_ops import pairwise_flat_inner
  
  from t3f.initializers import random_matrix
  from t3f.initializers import random_matrix_batch
  from t3f.initializers import random_tensor
  from t3f.initializers import random_tensor_batch
  
  from t3f.regularizers import cores_regularizer
  from t3f.regularizers import l2_regularizer
  
  from t3f.riemannian import add_n_projected
  from t3f.riemannian import pairwise_flat_inner_projected
  from t3f.riemannian import project
  from t3f.riemannian import project_matmul
  from t3f.riemannian import project_sum
  
  from t3f.shapes import batch_size
  from t3f.shapes import clean_raw_shape
  from t3f.shapes import expand_batch_dim
  from t3f.shapes import is_batch_broadcasting_possible
  from t3f.shapes import lazy_batch_size
  from t3f.shapes import lazy_raw_shape
  from t3f.shapes import lazy_shape
  from t3f.shapes import lazy_tt_ranks
  from t3f.shapes import raw_shape
  from t3f.shapes import shape
  from t3f.shapes import squeeze_batch_dim
  from t3f.shapes import tt_ranks
  
  from t3f.decompositions import orthogonalize_tt_cores
  from t3f.decompositions import round
  from t3f.decompositions import to_tt_matrix
  from t3f.decompositions import to_tt_tensor
  
  import t3f.kronecker as kronecker
  import t3f.utils as utils
  
  _directly_imported = ['tensor_train_base', 'tensor_train', 'tensor_train_batch',
                        'variables', 'ops', 'batch_ops', 'initializers',
                        'regularizers', 'riemannian', 'shapes', 'decompositions']
  
  __all__ = [s for s in dir() if
             s not in _directly_imported and not s.startswith('_')]
  
subject: Add renormalize_tt_cores to init