Fix mixed batch for multi modal models (#1702)

.github/workflows/pr-test.yml

@@ -76,7 +76,7 @@ jobs:
         timeout-minutes: 20
         run: |
           cd test/srt
-          python3 run_suite.py --suite minimal --range-begin 5 --range-end 16
+          python3 run_suite.py --suite minimal --range-begin 5 --range-end 17
 
   unit-test-backend-part-3:
     if: github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request'
@@ -96,7 +96,7 @@ jobs:
         timeout-minutes: 20
         run: |
           cd test/srt
-          python3 run_suite.py --suite minimal --range-begin 16
+          python3 run_suite.py --suite minimal --range-begin 17
 
   performance-test-1-gpu-part-1:
     if: github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request'

python/sglang/srt/models/llava.py

@@ -160,9 +160,6 @@ class LlavaBaseForCausalLM(nn.Module):
                 image_sizes = [
                     image_inputs[i].image_sizes for i in range(bs) if need_vision[i]
                 ]
-                image_offsets = [
-                    image_inputs[i].image_offsets for i in range(bs) if need_vision[i]
-                ]
 
                 ########## Encode Image ########
 
@@ -358,7 +355,7 @@ class LlavaBaseForCausalLM(nn.Module):
                     prefix_len = prefix_lens_cpu[i]
 
                     # Multiple images
-                    for j, image_offset in enumerate(image_offsets[i]):
+                    for j, image_offset in enumerate(image_inputs[i].image_offsets):
                         if image_offset < prefix_len:
                             continue
 

test/srt/test_vision_openai_server.py

+"""
+Usage:
+python3 -m unittest test_vision_openai_server.TestOpenAIVisionServer.test_mixed_batch
+"""
+
 import base64
 import io
 import json
 import os
 import unittest
+from concurrent.futures import ThreadPoolExecutor
 
 import numpy as np
 import openai
@@ -288,6 +294,55 @@ class TestOpenAIVisionServer(unittest.TestCase):
         assert isinstance(js_obj["color"], str)
         assert isinstance(js_obj["number_of_cars"], int)
 
+    def run_decode_with_image(self, image_id):
+        client = openai.Client(api_key=self.api_key, base_url=self.base_url)
+
+        content = []
+        if image_id == 0:
+            content.append(
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": "https://github.com/sgl-project/sglang/blob/main/test/lang/example_image.png?raw=true"
+                    },
+                }
+            )
+        elif image_id == 1:
+            content.append(
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": "https://raw.githubusercontent.com/sgl-project/sglang/main/assets/logo.png"
+                    },
+                }
+            )
+        else:
+            pass
+
+        content.append(
+            {
+                "type": "text",
+                "text": "Describe this image in a very short sentence.",
+            }
+        )
+
+        response = client.chat.completions.create(
+            model="default",
+            messages=[
+                {"role": "user", "content": content},
+            ],
+            temperature=0,
+        )
+
+        assert response.choices[0].message.role == "assistant"
+        text = response.choices[0].message.content
+        assert isinstance(text, str)
+
+    def test_mixed_batch(self):
+        image_ids = [0, 1, 2] * 4
+        with ThreadPoolExecutor(4) as executor:
+            list(executor.map(self.run_decode_with_image, image_ids))
+
 
 if __name__ == "__main__":
     unittest.main()