(self)
The training data of the models.

        Corresponds to the input data X which is the same for every model,
        and column-wise concatenation of the Y data over all models

        :return: tuple X, Y of tensors (if in tf_mode) or numpy arrays.
The training data of the models.
The training data of the models .
def data(self):
        """
        The training data of the models.

        Corresponds to the input data X which is the same for every model,
        and column-wise concatenation of the Y data over all models

        :return: tuple X, Y of tensors (if in tf_mode) or numpy arrays.
        """
        if self._tf_mode:
            return self.models[0].X, tf.concat(list(map(lambda model: model.Y, self.models)), 1)
        else:
            return self.models[0].X.value, np.hstack(map(lambda model: model.Y.value, self.models))
def data ( self ) : if self . _tf_mode : return self . models [ 0 ] . X , tf . concat ( list ( map ( lambda model : model . Y , self . models ) ) , 1 ) else : return self . models [ 0 ] . X . value , np . hstack ( map ( lambda model : model . Y . value , self . models ) )