feat: internvl llm support qwen3moe

Author: sangchengmeng

lightllm/models/internvl/model.py

@@ -10,6 +10,7 @@
 from lightllm.models.phi3.model import Phi3TpPartModel
 from lightllm.models.qwen2.model import Qwen2TpPartModel
 from lightllm.models.qwen3.model import Qwen3TpPartModel
+from lightllm.models.qwen3_moe.model import Qwen3MOEModel
 from lightllm.models.deepseek2.model import Deepseek2TpPartModel
 from lightllm.models.qwen_vl.layer_infer.pre_layer_infer import LlamaMultimodalPreLayerInfer
 from lightllm.models.internvl.layer_weights.pre_and_post_layer_weight import (
@@ -297,3 +298,27 @@ def _init_config(self):
         if self.finetune_config:
             self.config["vocab_size"] = self.finetune_config.vocab_size
         return
+
+
+@ModelRegistry(["internvl_chat"], is_multimodal=True, condition=llm_model_type_is("qwen3_moe"))
+class InternVLQwen3MOETpPartModel(Qwen3MOEModel):
+    # weight class
+    pre_and_post_weight_class = InternVLLlamaPreAndPostLayerWeight
+
+    # infer class
+    pre_layer_infer_class = LlamaMultimodalPreLayerInfer
+
+    def __init__(self, kvargs):
+        super().__init__(kvargs)
+        return
+
+    def _init_config(self):
+        with open(os.path.join(self.weight_dir_, "config.json"), "r") as json_file:
+            self.config = json.load(json_file)["llm_config"]
+        # rename keys
+        repair_config(self.config, same_names=["num_attention_heads", "n_head"])
+        repair_config(self.config, same_names=["hidden_size", "n_embd", "n_embed"])
+        repair_config(self.config, same_names=["num_hidden_layers", "n_layer"])
+        if self.finetune_config:
+            self.config["vocab_size"] = self.finetune_config.vocab_size
+        return