From 20b5172893680799c919d7ec03e924787ca10b8a Mon Sep 17 00:00:00 2001 From: bingyaweng Date: Thu, 12 Nov 2020 09:32:37 +0800 Subject: [PATCH] optimize the value of uncertainty exported --- .../nn/probability/toolbox/uncertainty_evaluation.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/mindspore/nn/probability/toolbox/uncertainty_evaluation.py b/mindspore/nn/probability/toolbox/uncertainty_evaluation.py index 96ada06089..1491a172c3 100644 --- a/mindspore/nn/probability/toolbox/uncertainty_evaluation.py +++ b/mindspore/nn/probability/toolbox/uncertainty_evaluation.py @@ -103,10 +103,6 @@ class UncertaintyEvaluation: raise ValueError("If save_model is True, the epi_uncer_model_path and " "ale_uncer_model_path should not be None.") - def _uncertainty_normalize(self, data): - area = np.max(data) - np.min(data) - return (data - np.min(data)) / area - def _get_epistemic_uncertainty_model(self): """ Get the model which can obtain the epistemic uncertainty. @@ -150,7 +146,7 @@ class UncertaintyEvaluation: else: outputs = np.stack(outputs, axis=1) epi_uncertainty = outputs.var(axis=1) - epi_uncertainty = self._uncertainty_normalize(np.array(epi_uncertainty)) + epi_uncertainty = np.array(epi_uncertainty) return epi_uncertainty def _get_aleatoric_uncertainty_model(self): @@ -184,7 +180,7 @@ class UncertaintyEvaluation: self._get_aleatoric_uncertainty_model() _, var = self.ale_uncer_model(eval_data) ale_uncertainty = self.sum(self.pow(var, 2), 1) - ale_uncertainty = self._uncertainty_normalize(ale_uncertainty.asnumpy()) + ale_uncertainty = ale_uncertainty.asnumpy() return ale_uncertainty def eval_epistemic_uncertainty(self, eval_data):