remove nan check during diffusion

Author: janfb

sbi/inference/posteriors/vector_field_posterior.py

@@ -340,14 +340,6 @@ def _sample_via_diffusion(
         # Concatenate all batches and ensure we return exactly the requested number
         samples = torch.cat(all_samples, dim=0)[:total_samples_needed]
 
-        # Check for NaN values
-        if torch.isnan(samples).any():
-            raise RuntimeError(
-                "NaN values detected during diffusion sampling. This may indicate"
-                " numerical instability in the vector field or improper time "
-                "scheduling."
-            )
-
         return samples
 
     def sample_via_ode(