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Fix: use math.log for Python float bounds in hyperparameter_sampling #29

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Fix: use math.log for Python float bounds in hyperparameter_sampling #29

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10 changes: 5 additions & 5 deletions pfns/priors/hyperparameter_sampling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -44,16 +44,16 @@ def sample(self):

def normalize(self, value: torch.Tensor) -> torch.Tensor:
if self.log:
return (torch.log(value) - torch.log(self.lower)) / (
torch.log(self.upper) - torch.log(self.lower)
return (torch.log(value) - math.log(self.lower)) / (
math.log(self.upper) - math.log(self.lower)
)
return (value - self.lower) / (self.upper - self.lower)

def unnormalize(self, encoded_value: torch.Tensor) -> torch.Tensor:
if self.log:
return torch.exp(
encoded_value * (torch.log(self.upper) - torch.log(self.lower))
+ torch.log(self.lower)
encoded_value * (math.log(self.upper) - math.log(self.lower))
+ math.log(self.lower)
)
return encoded_value * (self.upper - self.lower) + self.lower

Expand Down Expand Up @@ -143,7 +143,7 @@ def normalize(self, value):

def unnormalize(self, encoded_value):
if self.log:
return torch.exp(
return math.exp(
encoded_value * (math.log(self.upper) - math.log(self.lower))
+ math.log(self.lower)
)
Expand Down