[Fix] Enable mm_processor_cache with vision LoRA (#31927)

Signed-off-by: prashanth058 <prashanth.dannamaneni@uipath.com>

tests/multimodal/test_cache.py

@@ -24,10 +24,12 @@ from vllm.multimodal.cache import (
 )
 from vllm.multimodal.hasher import MultiModalHasher
 from vllm.multimodal.inputs import (
+    MultiModalFeatureSpec,
     MultiModalFieldElem,
     MultiModalKwargsItem,
     MultiModalKwargsItems,
     MultiModalSharedField,
+    PlaceholderRange,
 )
 from vllm.multimodal.processing import PromptInsertion
 from vllm.utils.mem_constants import GiB_bytes, MiB_bytes
@@ -518,3 +520,40 @@ def test_cache_eviction_shm_cache():
     receiver_cache = ShmObjectStoreReceiverCache(vllm_config, mp.Lock())
 
     _run_test_cache_eviction_shm(sender_cache, receiver_cache, base_item_size=MiB_bytes)
+
+
+def test_processor_cache_shared_across_loras():
+    """Test that processor cache uses mm_hash to share data across LoRAs."""
+    model_config = ModelConfig(
+        model="llava-hf/llava-onevision-qwen2-0.5b-ov-hf",
+        mm_processor_cache_gb=1,
+    )
+    receiver_cache = MultiModalReceiverCache(model_config)
+
+    base_mm_hash = "image_hash_abc123"
+    lora_a_identifier = f"12345:{base_mm_hash}"
+    lora_b_identifier = f"67890:{base_mm_hash}"
+
+    item_data = MultiModalKwargsItem.dummy("test_image", nbytes=1024)
+
+    feature_lora_a = MultiModalFeatureSpec(
+        data=item_data,
+        modality="image",
+        identifier=lora_a_identifier,
+        mm_position=PlaceholderRange(offset=0, length=100),
+        mm_hash=base_mm_hash,
+    )
+
+    receiver_cache.get_and_update_features([feature_lora_a])
+    assert base_mm_hash in receiver_cache._cache
+
+    feature_lora_b = MultiModalFeatureSpec(
+        data=None,
+        modality="image",
+        identifier=lora_b_identifier,
+        mm_position=PlaceholderRange(offset=0, length=100),
+        mm_hash=base_mm_hash,
+    )
+
+    receiver_cache.get_and_update_features([feature_lora_b])
+    assert feature_lora_b.data == item_data