From 7be8e60564886490f99e64e46d4aa29ac74908a0 Mon Sep 17 00:00:00 2001
From: Enwei Zhu <21126786+syuoni@users.noreply.github.com>
Date: Thu, 20 Mar 2025 13:30:15 +0000
Subject: [PATCH] fix

Signed-off-by: Enwei Zhu <21126786+syuoni@users.noreply.github.com>
---
 examples/llm-api/llm_logits_processor.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/llm-api/llm_logits_processor.py b/examples/llm-api/llm_logits_processor.py
index 0195dddd31..933be9f49a 100644
--- a/examples/llm-api/llm_logits_processor.py
+++ b/examples/llm-api/llm_logits_processor.py
@@ -9,7 +9,7 @@
 
 
 # The recommended way to create a customized logits processor:
-#     * Subclass this class and implement the processing logics in the __call__ method.
+#     * Subclass LogitsProcessor and implement the processing logics in the __call__ method.
 #     * Create an instance and pass to SamplingParams.
 # Alternatively, you can create any callable with the same signature with the __call__ method.
 # This simple callback will output a specific token at each step irrespective of prompt.
@@ -32,7 +32,7 @@ def __call__(self, req_id: int, logits: torch.Tensor,
 
 
 # The recommended way to create a customized batched logits processor:
-#     * Subclass this class and implement the processing logics in the __call__ method.
+#     * Subclass BatchedLogitsProcessor and implement the processing logics in the __call__ method.
 #     * Create an instance and pass to LLM.
 # Alternatively, you can create any callable with the same signature with the __call__ method.
 # A batched logits processor's arguments for all requests in a batch are made available as lists.