From 054aec852dda9d481035157585b26a3f419ebfdb Mon Sep 17 00:00:00 2001
From: xiaohajiayou <923390377@qq.com>
Date: Tue, 24 Jun 2025 02:02:33 +0800
Subject: [PATCH] Fix: Division-by-Zero Risk and Typo

---
 nanovllm/engine/llm_engine.py | 4 ++--
 nanovllm/layers/sampler.py    | 3 ++-
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/nanovllm/engine/llm_engine.py b/nanovllm/engine/llm_engine.py
index 6e64afd..2d43b50 100644
--- a/nanovllm/engine/llm_engine.py
+++ b/nanovllm/engine/llm_engine.py
@@ -15,8 +15,8 @@ from nanovllm.engine.model_runner import ModelRunner
 class LLMEngine:
 
     def __init__(self, model, **kwargs):
-        config_fileds = {field.name for field in fields(Config)}
-        config_kwargs = {k: v for k, v in kwargs.items() if k in config_fileds}
+        config_fields = {field.name for field in fields(Config)}
+        config_kwargs = {k: v for k, v in kwargs.items() if k in config_fields}
         config = Config(model, **config_kwargs)
         self.ps = []
         self.events = []
diff --git a/nanovllm/layers/sampler.py b/nanovllm/layers/sampler.py
index 88e59ee..e4b9816 100644
--- a/nanovllm/layers/sampler.py
+++ b/nanovllm/layers/sampler.py
@@ -13,5 +13,6 @@ class Sampler(nn.Module):
         logits.div_(temperatures.unsqueeze(dim=1))
         probs = torch.softmax(logits, dim=-1, dtype=torch.float)
         # logprobs = torch.log_softmax(logits, dim=-1, dtype=torch.float)
-        sample_tokens = probs.div_(torch.empty_like(probs).exponential_(1)).argmax(dim=-1)
+        epsilon = 1e-10  
+        sample_tokens = probs.div_(torch.empty_like(probs).exponential_(1) + epsilon).argmax(dim=-1)  
         return torch.where(temperatures == 0, greedy_tokens, sample_tokens)