(self, optimizer: base.Optimizer, *args: tp.Any, **kwargs: tp.Any)
| 82 | self._next_time = time.time() + log_interval_seconds |
| 83 | |
| 84 | def __call__(self, optimizer: base.Optimizer, *args: tp.Any, **kwargs: tp.Any) -> None: |
| 85 | if time.time() >= self._next_time or self._next_tell >= optimizer.num_tell: |
| 86 | self._next_time = time.time() + self._log_interval_seconds |
| 87 | self._next_tell = optimizer.num_tell + self._log_interval_tells |
| 88 | if optimizer.num_objectives == 1: |
| 89 | x = optimizer.provide_recommendation() |
| 90 | self._logger.log(self._log_level, "After %s, recommendation is %s", optimizer.num_tell, x) |
| 91 | else: |
| 92 | losses = optimizer._hypervolume_pareto.get_min_losses() # type: ignore |
| 93 | self._logger.log( |
| 94 | self._log_level, |
| 95 | "After %s, the respective minimum loss for each objective in the pareto front is %s", |
| 96 | optimizer.num_tell, |
| 97 | losses, |
| 98 | ) |
| 99 | |
| 100 | |
| 101 | class ParametersLogger: |
nothing calls this directly
no test coverage detected