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!10722 fix uncertainty toolbox 

From: @zhangxinfeng3
Reviewed-by: @wang_zi_dong,@sunnybeike
Signed-off-by: @sunnybeike
This commit is contained in:
mindspore-ci-bot 2020-12-29 10:39:34 +08:00 committed by Gitee
parent 68f68e9274 c944a75fed
commit 96c1cc102e
1 changed files with 8 additions and 5 deletions
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13
mindspore/nn/probability/toolbox/uncertainty_evaluation.py
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@ -239,13 +239,16 @@ class EpistemicUncertaintyModel(Cell):
def __init__(self, epi_model):
super(EpistemicUncertaintyModel, self).__init__()
self.drop_count = 0
if not self._make_epistemic(epi_model):
raise ValueError("The model has not Dense Layer or Convolution Layer, "
"it can not evaluate epistemic uncertainty so far.")
self.epi_model = self._make_epistemic(epi_model)
def construct(self, x):
x = self.epi_model(x)
return x
def _make_epistemic(self, epi_model, dropout_rate=0.5):
def _make_epistemic(self, epi_model, keep_prob=0.5):
"""
The dropout rate is set to 0.5 by default.
"""
@ -256,13 +259,13 @@ class EpistemicUncertaintyModel(Cell):
return epi_model
uncertainty_layer = layer
uncertainty_name = name
drop = Dropout(keep_prob=dropout_rate)
drop = Dropout(keep_prob=keep_prob)
bnn_drop = SequentialCell([uncertainty_layer, drop])
setattr(epi_model, uncertainty_name, bnn_drop)
return epi_model
self._make_epistemic(layer)
raise ValueError("The model has not Dense Layer or Convolution Layer, "
"it can not evaluate epistemic uncertainty so far.")
if self._make_epistemic(layer):
return epi_model
return None
class AleatoricUncertaintyModel(Cell):