torch_fidelity/feature_extractor_base.py
def convert_features_tuple_to_dict(self, features):
        """
        The only compound return type of the forward function amenable to JIT tracing is tuple.
        This function simply helps to recover the mapping.
        """
        vassert(
            type(features) is tuple and len(features) == len(self.features_list),
            'Features must be the output of forward function'
        )
        return dict(((name, feature) for name, feature  in zip(self.features_list, features)))

        The only compound return type of the forward function amenable to JIT tracing is tuple.
        This function simply helps to recover the mapping.
        
The only compound return type of the forward function amenable to JIT tracing is tuple.
This function simply helps to recover the mapping.
The only compound return type of the forward function amenable to JIT tracing is tuple . This function simply helps to recover the mapping .
def convert_features_tuple_to_dict(self, features):
        vassert(
            type(features) is tuple and len(features) == len(self.features_list),
            'Features must be the output of forward function'
        )
        return dict(((name, feature) for name, feature  in zip(self.features_list, features)))
def convert_features_tuple_to_dict ( self , features ) : vassert ( type ( features ) is tuple and len ( features ) == len ( self . features_list ) , 'Features must be the output of forward function' ) return dict ( ( ( name , feature ) for name , feature in zip ( self . features_list , features ) ) )
The only compound return type of the forward function amenable to JIT tracing is tuple.
The only compound return type of the forward function amenable to JIT tracing is tuple .
"""
        The only compound return type of the forward function amenable to JIT tracing is tuple.
        This function simply helps to recover the mapping.
        """
self
features