benchmarks/experimental/experimental_async_approaches.py [192:201]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    def prep_param_copies(self, params):
        model_params = [param for param in params if param.requires_grad]
        reference_params = [param.clone().detach() for param in model_params]
        for param in reference_params:
            param.requires_grad = True
        return model_params, reference_params

    def copy_params(self, master_params, model_params):
        for model, master in zip(model_params, master_params):
            model.data.copy_(master.data)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



benchmarks/experimental/experimental_async_approaches.py [327:336]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    def prep_param_copies(self, params):
        model_params = [param for param in params if param.requires_grad]
        reference_params = [param.clone().detach() for param in model_params]
        for param in reference_params:
            param.requires_grad = True
        return model_params, reference_params

    def copy_params(self, master_params, model_params):
        for model, master in zip(model_params, master_params):
            model.data.copy_(master.data)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -