Bug: Fix min_p sampling crash when using flashinfer backend (#3207)

Co-authored-by: zhaochenyang20 <zhaochen20@outlook.com>

python/sglang/srt/layers/sampler.py

@@ -85,7 +85,7 @@ class Sampler(nn.Module):
                 if sampling_info.need_min_p_sampling:
                     probs = top_k_renorm_prob(probs, sampling_info.top_ks)
                     probs = top_p_renorm_prob(probs, sampling_info.top_ps)
-                    batch_next_token_ids, success = min_p_sampling_from_probs(
+                    batch_next_token_ids = min_p_sampling_from_probs(
                         probs, uniform_samples, sampling_info.min_ps
                     )
                 else:
@@ -97,9 +97,9 @@ class Sampler(nn.Module):
                         filter_apply_order="joint",
                     )
 
-                if self.use_nan_detectioin and not torch.all(success):
-                    logger.warning("Detected errors during sampling!")
-                    batch_next_token_ids = torch.zeros_like(batch_next_token_ids)
+                    if self.use_nan_detectioin and not torch.all(success):
+                        logger.warning("Detected errors during sampling!")
+                        batch_next_token_ids = torch.zeros_like(batch_next_token_ids)
 
             elif global_server_args_dict["sampling_backend"] == "pytorch":
                 # A slower fallback implementation with torch native operations.