code: def fit_transform(self, X, u=None, sv=None, v=None):
          
          self.fit(X, u, sv, v)
          return self.embedding
docs: Fit X into an embedded space and return that transformed
          output.
          Inputs
          ----------
          X : array, shape (n_samples, n_features). X contains a sample per row.
  
          Returns
          -------
          embedding : array, shape (n_samples, n_components)
              Embedding of the training data in low-dimensional space.