rfho/save_and_load.py
def hypergradients():
        """
        Record all hypergradient values, assuming the usage of `HyperOptimizer`

        :return:
        """

        # noinspection PyUnusedLocal
        def _call(*args, **kwargs):
            hyper_optimizer = args[0]
            assert isinstance(hyper_optimizer, rf.HyperOptimizer)
            return rf.flatten_list(
                ['grad::' + rf.simple_name(hyp), hyper_optimizer.hyper_gradients.hyper_gradients_dict[hyp]]
                for hyp in hyper_optimizer.hyper_list)

        return _call

        Record all hypergradient values, assuming the usage of `HyperOptimizer`

        :return:
        
Record all hypergradient values, assuming the usage of `HyperOptimizer`
Record all hypergradient values assuming the usage of ` HyperOptimizer `
def hypergradients():
        def _call(*args, **kwargs):
            hyper_optimizer = args[0]
            assert isinstance(hyper_optimizer, rf.HyperOptimizer)
            return rf.flatten_list(
                ['grad::' + rf.simple_name(hyp), hyper_optimizer.hyper_gradients.hyper_gradients_dict[hyp]]
                for hyp in hyper_optimizer.hyper_list)
        return _call
def hypergradients ( ) : def _call ( * args , ** kwargs ) : hyper_optimizer = args [ 0 ] assert isinstance ( hyper_optimizer , rf . HyperOptimizer ) return rf . flatten_list ( [ 'grad::' + rf . simple_name ( hyp ) , hyper_optimizer . hyper_gradients . hyper_gradients_dict [ hyp ] ] for hyp in hyper_optimizer . hyper_list ) return _call
Record all hypergradient values, assuming the usage of `HyperOptimizer`
Record all hypergradient values assuming the usage of ` HyperOptimizer `
"""
        Record all hypergradient values, assuming the usage of `HyperOptimizer`

        :return:
        """ # noinspection PyUnusedLocal
None