def backward_tensor(self, y):
        """
        Transforms a series of triangular matrices y to the packed representation x (tf.tensors)
        
        :param y: unpacked tensor with shape self.num_matrices, self.N, self.N
        :return: packed tensor with shape self.num_matrices, (self.N**2 + self.N) / 2
        """
        if self.squeeze:
            y = tf.expand_dims(y, axis=0)
        indices = np.vstack(np.tril_indices(self.N)).T
        indices = itertools.product(np.arange(self.num_matrices), indices)
        indices = np.array([np.hstack(x) for x in indices])
        triangular = tf.gather_nd(y, indices)
        return tf.reshape(triangular, [self.num_matrices, (self.N**2 + self.N) // 2])