parameters: (self, X, y=None)
return_statement: return self.embedding_
docstring: Fit the model from data in X and transform X.
  
          Parameters
          ----------
          X: {array-like, sparse matrix, BallTree, KDTree}
              Training vector, where n_samples in the number of samples
              and n_features is the number of features.
  
          Returns
          -------
          X_new: array-like, shape (n_samples, n_components)
docstring_summary: Fit the model from data in X and transform X.
docstring_tokens: Fit the model from data in X and transform X .
function: def fit_transform(self, X, y=None):
          """Fit the model from data in X and transform X.
  
          Parameters
          ----------
          X: {array-like, sparse matrix, BallTree, KDTree}
              Training vector, where n_samples in the number of samples
              and n_features is the number of features.
  
          Returns
          -------
          X_new: array-like, shape (n_samples, n_components)
          """
          self._fit_transform(X)
          return self.embedding_
function_tokens: def fit_transform ( self , X , y = None ) : self . _fit_transform ( X ) return self . embedding_