[Refactor] Move top-level dummy data generation to registry (#32310)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

tests/models/multimodal/processing/test_mllama4.py

@@ -24,32 +24,20 @@ def test_profiling(model_id: str, max_model_len: int):
         limit_mm_per_prompt=mm_counts,
     )
 
-    processor = MULTIMODAL_REGISTRY.create_processor(ctx.model_config)
-    decoder_dummy_data = processor.dummy_inputs.get_decoder_dummy_data(
-        processor,
-        max_model_len,
-        mm_counts=mm_counts,
-    )
-    dummy_mm_data = processor.dummy_inputs.get_dummy_processor_inputs(
-        max_model_len,
+    mm_inputs = MULTIMODAL_REGISTRY.get_dummy_mm_inputs(
+        ctx.model_config,
         mm_counts=mm_counts,
     )
 
     hf_config = ctx.get_hf_config(Llama4Config)
-
-    mm_inputs = processor.apply(
-        prompt=dummy_mm_data.prompt,
-        mm_data=dummy_mm_data.mm_data,
-        hf_processor_mm_kwargs=dict(),
-    )
-    mm_data = mm_inputs["mm_kwargs"].get_data()
-
     image_size = hf_config.vision_config.image_size
     patch_size = hf_config.vision_config.patch_size
     downsample_ratio = int(
         round(1.0 / (hf_config.vision_config.pixel_shuffle_ratio**2))
     )
     tokens_per_patch = ((image_size // patch_size) ** 2) // downsample_ratio
+
+    mm_data = mm_inputs["mm_kwargs"].get_data()
     chunks_per_image = prod(mm_data["patches_per_image"])
     total_num_patches = chunks_per_image * tokens_per_patch
     num_tiles = (
@@ -63,6 +51,5 @@ def test_profiling(model_id: str, max_model_len: int):
         item.get_num_embeds for item in mm_inputs["mm_placeholders"]["image"]
     )
     assert total_tokens == sum(
-        placeholder.length
-        for placeholder in decoder_dummy_data.multi_modal_placeholders["image"]
+        placeholder.length for placeholder in mm_inputs["mm_placeholders"]["image"]
     )