class_docstr: Base class for NMF and MiniBatchNMF.
class_docstr_tok: ["Base","class","for","NMF","and","MiniBatchNMF","."]
docstr: Transform data back to its original space.
  
  .. versionadded:: 0.18
  
  Parameters
  ----------
  Xt : {ndarray, sparse matrix} of shape (n_samples, n_components)
      Transformed data matrix.
  
  W : deprecated
      Use `Xt` instead.
  
      .. deprecated:: 1.3
  
  Returns
  -------
  X : {ndarray, sparse matrix} of shape (n_samples, n_features)
      Returns a data matrix of the original shape.
code: def inverse_transform(self, Xt=None, W=None):
      """Transform data back to its original space.
  
      .. versionadded:: 0.18
  
      Parameters
      ----------
      Xt : {ndarray, sparse matrix} of shape (n_samples, n_components)
          Transformed data matrix.
  
      W : deprecated
          Use `Xt` instead.
  
          .. deprecated:: 1.3
  
      Returns
      -------
      X : {ndarray, sparse matrix} of shape (n_samples, n_features)
          Returns a data matrix of the original shape.
      """
      if Xt is None and W is None:
          raise TypeError("Missing required positional argument: Xt")
  
      if W is not None and Xt is not None:
          raise ValueError("Please provide only `Xt`, and not `W`.")
  
      if W is not None:
          warnings.warn(
              (
                  "Input argument `W` was renamed to `Xt` in v1.3 and will be removed"
                  " in v1.5."
              ),
              FutureWarning,
          )
          Xt = W
  
      check_is_fitted(self)
      return Xt @ self.components_
  
imports: import itertools
  import time
  import warnings
  from abc import ABC
  from math import sqrt
  from numbers import Integral, Real
  import numpy
  import scipy.sparse
  from scipy import linalg
  from .._config import config_context
  from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
  from ..exceptions import ConvergenceWarning
  from ..utils import check_array, check_random_state, gen_batches, metadata_routing
  from ..utils._param_validation import Interval, StrOptions, validate_params
  from ..utils.extmath import randomized_svd, safe_sparse_dot, squared_norm
  from ..utils.validation import check_is_fitted, check_non_negative
  from ._cdnmf_fast import _update_cdnmf_fast
label_desc: Use image node_id 6 for calling the _BaseNMF obj's underlying member method code with example usage: obj.inverse_transform(Xt, W) and returns: unknown