def make_trainable(modules: Union[Module, Iterable[Union[Module, Iterable]]]) -> None:
        """Unfreezes the parameters of the provided modules.

        Args:
            modules: A given module or an iterable of modules

        """
        modules = BaseFinetuning.flatten_modules(modules)
        for module in modules:
            if isinstance(module, _BatchNorm):
                module.track_running_stats = True
            # recursion could yield duplicate parameters for parent modules w/ parameters so disabling it
            for param in module.parameters(recurse=False):
                param.requires_grad = True
Unfreezes the parameters of the provided modules.

        Args:
            modules: A given module or an iterable of modules

        
src/lightning/pytorch/callbacks/finetuning.py