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|
| | from __future__ import annotations |
| |
|
| | from monai.fl.utils.constants import WeightType |
| |
|
| |
|
| | class ExchangeObject(dict): |
| | """ |
| | Contains the information shared between client and server. |
| | |
| | Args: |
| | weights: model weights. |
| | optim: optimizer weights. |
| | metrics: evaluation metrics. |
| | weight_type: type of weights (see monai.fl.utils.constants.WeightType). |
| | statistics: training statistics, i.e. number executed iterations. |
| | """ |
| |
|
| | def __init__( |
| | self, |
| | weights: dict | None = None, |
| | optim: dict | None = None, |
| | metrics: dict | None = None, |
| | weight_type: WeightType | None = None, |
| | statistics: dict | None = None, |
| | ): |
| | super().__init__() |
| | self.weights = weights |
| | self.optim = optim |
| | self.metrics = metrics |
| | self.weight_type = weight_type |
| | self.statistics = statistics |
| | self._summary: dict = {} |
| |
|
| | @property |
| | def metrics(self): |
| | return self._metrics |
| |
|
| | @metrics.setter |
| | def metrics(self, metrics): |
| | if metrics is not None: |
| | if not isinstance(metrics, dict): |
| | raise ValueError(f"Expected metrics to be of type dict but received {type(metrics)}") |
| | self._metrics = metrics |
| |
|
| | @property |
| | def statistics(self): |
| | return self._statistics |
| |
|
| | @statistics.setter |
| | def statistics(self, statistics): |
| | if statistics is not None: |
| | if not isinstance(statistics, dict): |
| | raise ValueError(f"Expected statistics to be of type dict but received {type(statistics)}") |
| | self._statistics = statistics |
| |
|
| | @property |
| | def weight_type(self): |
| | return self._weight_type |
| |
|
| | @weight_type.setter |
| | def weight_type(self, weight_type): |
| | if weight_type is not None: |
| | if weight_type not in [WeightType.WEIGHTS, WeightType.WEIGHT_DIFF]: |
| | raise ValueError(f"Expected weight type to be either {WeightType.WEIGHTS} or {WeightType.WEIGHT_DIFF}") |
| | self._weight_type = weight_type |
| |
|
| | def is_valid_weights(self): |
| | if not self.weights: |
| | return False |
| | if not self.weight_type: |
| | return False |
| | return True |
| |
|
| | def _add_to_summary(self, key, value): |
| | if value: |
| | if isinstance(value, dict): |
| | self._summary[key] = len(value) |
| | elif isinstance(value, WeightType): |
| | self._summary[key] = value |
| | else: |
| | self._summary[key] = type(value) |
| |
|
| | def summary(self): |
| | self._summary.update(self) |
| | for k, v in zip( |
| | ["weights", "optim", "metrics", "weight_type", "statistics"], |
| | [self.weights, self.optim, self.metrics, self.weight_type, self.statistics], |
| | ): |
| | self._add_to_summary(k, v) |
| | return self._summary |
| |
|
| | def __repr__(self): |
| | return str(self.summary()) |
| |
|
| | def __str__(self): |
| | return str(self.summary()) |
| |
|
