code: def transform(self, X, y=None):
          
  
          if (self.components_ is None):
              raise ValueError('No components initialized')
  
          return self._compute_hidden_activations(X)
docs: Generate the random hidden layer's activations given X as input.
  
          Parameters
          ----------
          X : {array-like, sparse matrix}, shape [n_samples, n_features]
              Data to transform
  
          y : is not used: placeholder to allow for usage in a Pipeline.
  
          Returns
          -------
          X_new : numpy array of shape [n_samples, n_components]