🩹 Fix null Jacobian caused by tanh

probabilists · May 28, 2022 · 50e53c7 · 50e53c7
1 parent 81a22d3
commit 50e53c7
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Showing 2 changed files with 3 additions and 3 deletions.
diff --git a/lampe/distributions/transforms.py b/lampe/distributions/transforms.py
@@ -274,7 +274,7 @@ def __init__(
         self.eps = eps
 
     def _call(self, x: Tensor) -> Tensor:
-        return self.f(self.bound * torch.tanh(x / self.bound))
+        return self.f(x / torch.sqrt(1 + (x / self.bound)**2))
 
     def _inverse(self, y: Tensor) -> Tensor:
         a = torch.full_like(y, -self.bound)
@@ -290,7 +290,7 @@ def _inverse(self, y: Tensor) -> Tensor:
 
         x = (a + b) / 2
 
-        return self.bound * torch.atanh(x / self.bound)
+        return x / torch.sqrt(1 - (x / self.bound)**2)
 
     def log_abs_det_jacobian(self, x: Tensor, y: Tensor) -> Tensor:
         return torch.log(torch.autograd.functional.jacobian(

diff --git a/setup.py b/setup.py
@@ -10,7 +10,7 @@
 
 setuptools.setup(
     name='lampe',
-    version='0.4.3',
+    version='0.4.4',
     packages=setuptools.find_packages(),
     description='Likelihood-free AMortized Posterior Estimation with PyTorch',
     keywords='parameter inference bayes posterior amortized likelihood ratio mcmc torch',