[Fix] Fix OOM in llava base class (#1249)

examples/runtime/llava_onevision/http_llava_onevision_test.py

 """
 Usage:
 
-python3 -m sglang.launch_server --model-path lmms-lab/llava-onevision-qwen2-72b-ov --port=30000 --tp-size=8 --chat-template=chatml-llava --chunked-prefill-size=16384
+python3 -m sglang.launch_server --model-path lmms-lab/llava-onevision-qwen2-72b-ov --port=30000 --tp-size=8 --chat-template=chatml-llava
 
 python3 http_llava_onevision_test.py
 """

python/sglang/srt/models/llava.py

@@ -46,25 +46,7 @@ from sglang.srt.models.mistral import MistralForCausalLM
 from sglang.srt.models.qwen2 import Qwen2ForCausalLM
 
 
-class LlavaLlamaForCausalLM(nn.Module):
-    def __init__(
-        self,
-        config: LlavaConfig,
-        quant_config: Optional[QuantizationConfig] = None,
-        cache_config: Optional[CacheConfig] = None,
-    ) -> None:
-        super().__init__()
-        self.config = config
-        self.vision_tower = None
-        self.config.vision_config.hidden_size = config.mm_hidden_size
-        self.config.text_config.hidden_size = config.hidden_size
-        self.multi_modal_projector = LlavaMultiModalProjector(config)
-        self.language_model = LlamaForCausalLM(config, quant_config=quant_config)
-        if "unpad" in getattr(config, "mm_patch_merge_type", ""):
-            self.language_model.model.image_newline = nn.Parameter(
-                torch.empty(config.text_config.hidden_size, dtype=torch.float16)
-            )
-
+class LlavaBaseForCausalLM(nn.Module):
     def pad_input_ids(
         self,
         input_ids: List[int],
@@ -434,14 +416,36 @@ class LlavaLlamaForCausalLM(nn.Module):
         return self.image_size // self.patch_size
 
 
-class LlavaQwenForCausalLM(LlavaLlamaForCausalLM):
+class LlavaLlamaForCausalLM(LlavaBaseForCausalLM):
+    def __init__(
+        self,
+        config: LlavaConfig,
+        quant_config: Optional[QuantizationConfig] = None,
+        cache_config: Optional[CacheConfig] = None,
+    ) -> None:
+        super().__init__()
+
+        self.config = config
+        self.vision_tower = None
+        self.config.vision_config.hidden_size = config.mm_hidden_size
+        self.config.text_config.hidden_size = config.hidden_size
+        self.multi_modal_projector = LlavaMultiModalProjector(config)
+        self.language_model = LlamaForCausalLM(config, quant_config=quant_config)
+        if "unpad" in getattr(config, "mm_patch_merge_type", ""):
+            self.language_model.model.image_newline = nn.Parameter(
+                torch.empty(config.text_config.hidden_size, dtype=torch.float16)
+            )
+
+
+class LlavaQwenForCausalLM(LlavaBaseForCausalLM):
     def __init__(
         self,
         config: LlavaConfig,
         quant_config: Optional[QuantizationConfig] = None,
         cache_config: Optional[CacheConfig] = None,
     ) -> None:
-        super().__init__(config, quant_config=quant_config, cache_config=cache_config)
+        super().__init__()
+
         self.config = config
         self.vision_tower = None
         if getattr(self.config, "vision_config", None) is None:
@@ -467,14 +471,15 @@ class LlavaQwenForCausalLM(LlavaLlamaForCausalLM):
             )
 
 
-class LlavaMistralForCausalLM(LlavaLlamaForCausalLM):
+class LlavaMistralForCausalLM(LlavaBaseForCausalLM):
     def __init__(
         self,
         config: LlavaConfig,
         quant_config: Optional[QuantizationConfig] = None,
         cache_config: Optional[CacheConfig] = None,
     ) -> None:
-        super().__init__(config, quant_config=quant_config, cache_config=cache_config)
+        super().__init__()
+
         self.config = config
         self.vision_tower = None
         if getattr(self.config, "vision_config", None) is None:

python/sglang/srt/server.py

@@ -421,7 +421,7 @@ def _set_envs_and_config(server_args: ServerArgs):
     if not server_args.disable_flashinfer:
         assert_pkg_version(
             "flashinfer",
-            "0.1.5",
+            "0.1.6",
             "Please uninstall the old version and "
             "reinstall the latest version by following the instructions "
             "at https://docs.flashinfer.ai/installation.html.",