[Model] Remove image mm limit for LLaMa4

examples/offline_inference/vision_language_multi_image.py

@@ -22,6 +22,16 @@
 IMAGE_URLS = [
     "https://upload.wikimedia.org/wikipedia/commons/d/da/2015_Kaczka_krzy%C5%BCowka_w_wodzie_%28samiec%29.jpg",
     "https://upload.wikimedia.org/wikipedia/commons/7/77/002_The_lion_king_Snyggve_in_the_Serengeti_National_Park_Photo_by_Giles_Laurent.jpg",
+    "https://upload.wikimedia.org/wikipedia/commons/2/26/Ultramarine_Flycatcher_%28Ficedula_superciliaris%29_Naggar%2C_Himachal_Pradesh%2C_2013_%28cropped%29.JPG",
+    "https://upload.wikimedia.org/wikipedia/commons/thumb/e/e5/Anim1754_-_Flickr_-_NOAA_Photo_Library_%281%29.jpg/2560px-Anim1754_-_Flickr_-_NOAA_Photo_Library_%281%29.jpg",
+    "https://upload.wikimedia.org/wikipedia/commons/d/d4/Starfish%2C_Caswell_Bay_-_geograph.org.uk_-_409413.jpg",
+    "https://upload.wikimedia.org/wikipedia/commons/6/69/Grapevinesnail_01.jpg",
+    "https://upload.wikimedia.org/wikipedia/commons/thumb/0/0b/Texas_invasive_Musk_Thistle_1.jpg/1920px-Texas_invasive_Musk_Thistle_1.jpg",
+    "https://upload.wikimedia.org/wikipedia/commons/thumb/7/7a/Huskiesatrest.jpg/2880px-Huskiesatrest.jpg",
+    "https://upload.wikimedia.org/wikipedia/commons/thumb/6/68/Orange_tabby_cat_sitting_on_fallen_leaves-Hisashi-01A.jpg/1920px-Orange_tabby_cat_sitting_on_fallen_leaves-Hisashi-01A.jpg",
+    "https://upload.wikimedia.org/wikipedia/commons/3/30/George_the_amazing_guinea_pig.jpg",
+    "https://upload.wikimedia.org/wikipedia/commons/thumb/1/1f/Oryctolagus_cuniculus_Rcdo.jpg/1920px-Oryctolagus_cuniculus_Rcdo.jpg",
+    "https://upload.wikimedia.org/wikipedia/commons/9/98/Horse-and-pony.jpg",
 ]
 
 
@@ -285,8 +295,7 @@ def load_llama4(question: str, image_urls: list[str]) -> ModelRequestData:
 
     engine_args = EngineArgs(
         model=model_name,
-        max_model_len=8192,
-        max_num_seqs=4,
+        max_model_len=131072,
         tensor_parallel_size=8,
         limit_mm_per_prompt={"image": len(image_urls)},
     )
@@ -660,7 +669,7 @@ def run_generate(model, question: str, image_urls: list[str],
             llm.llm_engine.add_lora(lora_request=lora_request)
 
     sampling_params = SamplingParams(temperature=0.0,
-                                     max_tokens=128,
+                                     max_tokens=256,
                                      stop_token_ids=req_data.stop_token_ids)
 
     outputs = llm.generate(
@@ -694,7 +703,7 @@ def run_chat(model: str, question: str, image_urls: list[str],
             llm.llm_engine.add_lora(lora_request=lora_request)
 
     sampling_params = SamplingParams(temperature=0.0,
-                                     max_tokens=128,
+                                     max_tokens=256,
                                      stop_token_ids=req_data.stop_token_ids)
     outputs = llm.chat(
         [{
@@ -729,10 +738,12 @@ def main(args: Namespace):
     method = args.method
     seed = args.seed
 
+    image_urls = IMAGE_URLS[:args.num_images]
+
     if method == "generate":
-        run_generate(model, QUESTION, IMAGE_URLS, seed)
+        run_generate(model, QUESTION, image_urls, seed)
     elif method == "chat":
-        run_chat(model, QUESTION, IMAGE_URLS, seed)
+        run_chat(model, QUESTION, image_urls, seed)
     else:
         raise ValueError(f"Invalid method: {method}")
 
@@ -757,6 +768,12 @@ def main(args: Namespace):
                         type=int,
                         default=None,
                         help="Set the seed when initializing `vllm.LLM`.")
+    parser.add_argument(
+        "--num-images",
+        "-n",
+        choices=list(range(1, 13)),  # 12 is the max number of images
+        default=2,
+        help="Number of images to use for the demo.")
 
     args = parser.parse_args()
     main(args)

vllm/model_executor/models/mllama4.py

@@ -477,7 +477,9 @@ def get_hf_processor(self, **kwargs: object) -> Llama4Processor:
                                          **kwargs)
 
     def get_supported_mm_limits(self) -> Mapping[str, Optional[int]]:
-        return {"image": 10}
+        # Although vLLM can support more images from an infra capability
+        # perspective, we do not recommend using >10 images in practice.
+        return {"image": None}
 
     @staticmethod
     def get_patch_per_chunk(vision_config: Llama4VisionConfig) -> int: