save_and_load.py 文件源码

def norms_of_d_dynamics_d_hypers(fd=None):
        """
        In `ForwardHG` records the norm of the partial derivatives of the dynamics w.r.t. the hyperparameters.

        :param fd:
        :return:
        """
        if fd is None: fd = lambda stp, rs: rs

        def _call(*args, **kwargs):
            hg = args[0]
            if isinstance(hg, rf.HyperOptimizer):
                hg = hg.hyper_gradients  # guess most common case
            assert isinstance(hg, rf.ForwardHG)
            _rs = Records.tensors(*hg.d_dynamics_d_hypers, op=tf.norm,
                                  fd=fd,
                                  condition=lambda stp, rs: rs != 'INIT')(args, kwargs)
            return _rs

        return _call