Fixing Bug with HPO #345
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Fixing Bug with HPO #345
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Diff Coverage details (click to unfold)src/renate/updaters/experimental/er.py
src/renate/updaters/learner_components/reinitialization.py
src/renate/updaters/learner_components/losses.py
src/renate/updaters/learner_components/component.py
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lballes
suggested changes
Jul 26, 2023
| def on_save_checkpoint(self, checkpoint: Dict[str, Any]) -> None: | ||
| """Add plastic and stable model to checkpoint.""" | ||
| super().on_save_checkpoint(checkpoint) | ||
| checkpoint["component-cls-plastic-model"] = self._plastic_model |
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We should save and load self._plastic_model.state_dict() instead of the model object itself.
| @@ -5,6 +5,6 @@ | |||
| "dataset": "mnist.json", | |||
| "backend": "local", | |||
| "job_name": "class-incremental-mlp-cls-er", | |||
| "expected_accuracy_linux": [[0.9839243292808533, 0.9740450382232666]], | |||
| "expected_accuracy_linux": [[0.9834515452384949, 0.9740450382232666]], | |||
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Shouldn't the results remain unaffected by the changes?
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See PR description for more details. In short, working with torch.tensor(1.0) and float(1.0) seem to cause differences.
lballes
approved these changes
Jul 27, 2023
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Hyperparameter defined as part of the components were overwritten by values in
state_dict. To address this issue,Componentno longer is ann.Module.Moving from torch.tensor to Python floats had led to changes for CLS (and therefore Super-ER) at the 8th digit. These errors accumulate and therefore give some different numbers. To account for this, I've changed the expected values for CLS and Super-ER.
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