Method noise_lambda

unihsi/env/tasks/base_task.py:275–283

(tensor, param_name=nonphysical_param)

                            (1.0 - sched_scaling)  # linearly interpolate

                    def noise_lambda(tensor, param_name=nonphysical_param):
                        params = self.dr_randomizations[param_name]
                        corr = params.get('corr', None)
                        if corr is None:
                            corr = torch.randn_like(tensor)
                            params['corr'] = corr
                        corr = corr * params['var_corr'] + params['mu_corr']
                        return op(
                            tensor, corr + torch.randn_like(tensor) * params['var'] + params['mu'])

                    self.dr_randomizations[nonphysical_param] = {'mu': mu, 'var': var, 'mu_corr': mu_corr, 'var_corr': var_corr, 'noise_lambda': noise_lambda}