take care of log1p as well

Author: Kucharssim

bayesflow/adapters/transforms/log.py

@@ -50,7 +50,10 @@ def get_config(self) -> dict:
         }
 
     def log_det_jac(self, data: np.ndarray, inverse: bool = False, **kwargs) -> np.ndarray:
-        ldj = -np.log(data)
+        if self.p1:
+            ldj = -np.log1p(data)
+        else:
+            ldj = -np.log(data)
         if inverse:
             ldj = -ldj
         return np.sum(ldj, axis=tuple(range(1, ldj.ndim)))