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fix issue #328 #333

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Merged
merged 4 commits into from
Feb 21, 2025
Merged

fix issue #328 #333

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d942cf8
fix issue #328
paul-buerkner Feb 21, 2025
a128f37
also fix the issue for model_comparison_approximators
paul-buerkner Feb 21, 2025
e1e69f6
minor cleaning
paul-buerkner Feb 21, 2025
5fa7750
add comment
paul-buerkner Feb 21, 2025
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2 changes: 2 additions & 0 deletions bayesflow/approximators/continuous_approximator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -140,6 +140,8 @@ def sample(
**kwargs,
) -> dict[str, np.ndarray]:
conditions = self.adapter(conditions, strict=False, stage="inference", **kwargs)
# at inference time, inference_variables are estimated by the networks and thus ignored in conditions
conditions.pop("inference_variables", None)
conditions = keras.tree.map_structure(keras.ops.convert_to_tensor, conditions)
conditions = {"inference_variables": self._sample(num_samples=num_samples, **conditions, **kwargs)}
conditions = keras.tree.map_structure(keras.ops.convert_to_numpy, conditions)
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2 changes: 2 additions & 0 deletions bayesflow/approximators/model_comparison_approximator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -208,6 +208,8 @@ def predict(
**kwargs,
) -> np.ndarray:
conditions = self.adapter(conditions, strict=False, stage="inference", **kwargs)
# at inference time, model_indices are predicted by the networks and thus ignored in conditions
conditions.pop("model_indices", None)
conditions = keras.tree.map_structure(keras.ops.convert_to_tensor, conditions)

output = self._predict(**conditions, **kwargs)
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