diff --git a/sbi/inference/potentials/base_potential.py b/sbi/inference/potentials/base_potential.py
index d24b05b94..8a52dd470 100644
--- a/sbi/inference/potentials/base_potential.py
+++ b/sbi/inference/potentials/base_potential.py
@@ -69,11 +69,6 @@ def x_o(self) -> Tensor:
                 "No observed data is available. Use `potential_fn.set_x(x_o)`."
             )
 
-    @x_o.setter
-    def x_o(self, x_o: Optional[Tensor]) -> None:
-        """Check the shape of the observed data and, if valid, set it."""
-        self.set_x(x_o)
-
     def return_x_o(self) -> Optional[Tensor]:
         """Return the observed data at which the potential is evaluated.
 
diff --git a/sbi/samplers/vi/vi_divergence_optimizers.py b/sbi/samplers/vi/vi_divergence_optimizers.py
index d05262f11..24ab3d9f1 100644
--- a/sbi/samplers/vi/vi_divergence_optimizers.py
+++ b/sbi/samplers/vi/vi_divergence_optimizers.py
@@ -479,7 +479,7 @@ def generate_elbo_particles(
             samples = self.q.rsample(torch.Size((num_samples,)))
             log_q = self.q.log_prob(samples)
 
-        self.potential_fn.x_o = x_o
+        self.potential_fn.set_x(x_o)
         log_potential = self.potential_fn(samples)
         elbo = log_potential - log_q
         return elbo
@@ -638,7 +638,7 @@ def _loss_q_proposal(self, x_o: Tensor) -> Tuple[Tensor, Tensor]:
         if hasattr(self.q, "clear_cache"):
             self.q.clear_cache()
         logq = self.q.log_prob(samples)
-        self.potential_fn.x_o = x_o
+        self.potential_fn.set_x(x_o)
         logp = self.potential_fn(samples)
         with torch.no_grad():
             logweights = logp - logq
diff --git a/sbi/utils/conditional_density_utils.py b/sbi/utils/conditional_density_utils.py
index 0d48efedb..3251f99a9 100644
--- a/sbi/utils/conditional_density_utils.py
+++ b/sbi/utils/conditional_density_utils.py
@@ -430,11 +430,6 @@ def x_o(self) -> Tensor:
         else:
             raise ValueError("No observed data is available.")
 
-    @x_o.setter
-    def x_o(self, x_o: Optional[Tensor]) -> None:
-        """Check the shape of the observed data and, if valid, set it."""
-        self.set_x(x_o)
-
     def return_x_o(self) -> Optional[Tensor]:
         """Return the observed data at which the potential is evaluated.