[VLM] Calculate maximum number of multi-modal tokens by model (#6121)

vllm/model_executor/models/llava_next.py

@@ -127,6 +127,17 @@ def get_llava_next_image_feature_size(
     raise NotImplementedError(msg)
 
 
+def get_max_llava_next_image_tokens(ctx: InputContext):
+    # Result in the max possible feature size (2x2 grid of 336x336px tiles)
+    dummy_height = dummy_width = 448
+
+    return get_llava_next_image_feature_size(
+        ctx.get_hf_config(LlavaNextConfig),
+        input_height=dummy_height,
+        input_width=dummy_width,
+    )
+
+
 def dummy_data_for_llava_next(ctx: InputContext, seq_len: int):
     hf_config = ctx.get_hf_config(LlavaNextConfig)
     vision_config = hf_config.vision_config
@@ -198,6 +209,7 @@ def input_processor_for_llava_next(ctx: InputContext, llm_inputs: LLMInputs):
 
 
 @MULTIMODAL_REGISTRY.register_image_input_mapper()
+@MULTIMODAL_REGISTRY.register_max_image_tokens(get_max_llava_next_image_tokens)
 @INPUT_REGISTRY.register_dummy_data(dummy_data_for_llava_next)
 @INPUT_REGISTRY.register_input_processor(input_processor_for_llava_next)
 class LlavaNextForConditionalGeneration(nn.Module, SupportsVision):