Method AddGradientOperators

caffe2/python/model_helper.py:309–331

(self, *args, **kwargs)

        return dbreader

    def AddGradientOperators(self, *args, **kwargs):
        if self.gradient_ops_added:
            raise RuntimeError("You cannot run AddGradientOperators twice.")
        self.Validate()

        self.gradient_ops_added = True
        self.grad_map = self.net.AddGradientOperators(*args, **kwargs)
        self.param_to_grad = self.get_param_to_grad(self.params)

        # Populate ParameterInfo for all parameters if missing
        # and add gradient blob information. So optimizers can use it
        for param, grad in self.param_to_grad.items():
            param_info = self.get_param_info(param)
            if param_info:
                param_info.grad = grad
            else:
                self._parameters_info[param] = parameter_info.ParameterInfo(
                    param_id=None,
                    param=param,
                    grad=grad,
                )

        return self.grad_map

    def get_param_to_grad(self, params):
        '''