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Added docstrings, type hints to following functions: #19
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_compute_accuracy, accuracy_scorer, marginal_gain_scorer
eigengravy
suggested changes
Jun 14, 2023
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also format using black, you can setup vscode to use it by default
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accuracy_scorer, marginal_gain_scorer, removing unecessary imports
eigengravy
suggested changes
Jun 14, 2023
| @@ -23,7 +57,7 @@ def marginal_gain_scorer(weights, prev_scores, testloader): | |||
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| def multikrum_scorer(weights): | |||
| def multikrum_scorer(weights: List[Mapping[str, Any]]): | |||
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return type is list of floats
Suggested change
| def multikrum_scorer(weights: List[Mapping[str, Any]]): | |
| def multikrum_scorer(weights: List[Mapping[str, Any]]) -> List[float]: |
| model = create_model() | ||
| model.load_state_dict(weight) | ||
| return test_model(model, testloader)[0] | ||
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| def accuracy_scorer(weights, testloader): | ||
| def accuracy_scorer(weights: List[Mapping[str, Any]], testloader: DataLoader)-> List(float): |
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typo
Suggested change
| def accuracy_scorer(weights: List[Mapping[str, Any]], testloader: DataLoader)-> List(float): | |
| def accuracy_scorer(weights: List[Mapping[str, Any]], testloader: DataLoader)-> List[float]: |
| @@ -63,7 +63,7 @@ def test_model(model: Model, testloader: DataLoader) -> Tuple[float, float]: | |||
| return 100 * correct, test_loss | |||
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| def fedavg_models(weights): | |||
| def fedavg_models(weights: list[dict])-> dict: | |||
| @@ -23,7 +23,7 @@ def __init__(self) -> None: | |||
| nn.Linear(128, 10), | |||
| ) | |||
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| def forward(self, x): | |||
| def forward(self, x: DataLoader)-> DataLoader: | |||
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take lite
Suggested change
| def forward(self, x: DataLoader)-> DataLoader: | |
| def forward(self, x): |
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Sorry I think I pushed the scorer.py changes by accident, I was waiting until after Druva implemented the other ML Model to complete it properly. I'll Fix these |
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_compute_accuracy, accuracy_scorer, marginal_gain_scorer