47a96974ab2d75fc20c76a6d6da20976ecad32bb,gpytorch/random_variables/random_variable.py,RandomVariable,cuda,#RandomVariable#Any#,22

Before Change

    def cuda(self, device_id=None):
        representation = self.representation()
        if not isinstance(representation, tuple) or isinstance(representation, list):
            representation = representation,
        return self.__class__(*(var.cuda(device_id) for var in representation))

    def covar(self):
        
        Returns the covariance of the random variable

After Change

                new_args.append(arg)
        for name, val in self._kwargs.items():
            if hasattr(val, "cuda"):
                new_kwargs[name] = val.cuda(device_id)
            else:
                new_kwargs[name] = val
        return self.__class__(*new_args, **new_kwargs)

    def covar(self):
        

Instances