run pass llm cp

(cherry picked from commit 1d85394563d96cf22d5d84f15c0e9043582419e4)

python/sglang/srt/model_executor/runner/eager_runner.py

@@ -385,14 +385,22 @@ class EagerRunner(BaseRunner):
         """
         model = self.model_runner.model
 
+        input_ids = forward_batch.input_ids
         input_embeds = kwargs.get("input_embeds")
+        # Multimodal spans must be embedded in global token order, before CP
+        # slicing. The model may also normalize image hash IDs for its router.
+        prepare_inputs = getattr(model, "prepare_language_model_inputs", None)
+        if prepare_inputs is not None:
+            input_ids, input_embeds = prepare_inputs(
+                input_ids, forward_batch, input_embeds
+            )
         if input_embeds is None:
-            input_embeds = model.get_input_embeddings()(forward_batch.input_ids)
+            input_embeds = model.get_input_embeddings()(input_ids)
         with cp_shard_model_inputs(
             input_embeds,
             forward_batch.positions,
             forward_batch,
-            forward_batch.input_ids,
+            input_ids,
         ) as (sharded_input_embeds, sharded_positions, model_input_ids):
             model_kwargs = {"input_embeds": sharded_input_embeds}
             if (pp_proxy_tensors := kwargs.get("pp_proxy_tensors")) is not None:
@@ -437,7 +445,7 @@ class EagerRunner(BaseRunner):
             if aux_hidden_states is None:
                 logits_kwargs["hidden_states_before_norm"] = hidden_states_before_norm
         return model.logits_processor(
-            forward_batch.input_ids,
+            input_ids,
             hidden_states,
             model.lm_head,
             forward_batch,