[TRTLLM-7918][feat] Revert "Support kvcache reuse for phi4mm (#7563)" (#7722)

Signed-off-by: Wanli Jiang <[email protected]>

Author: Wanli-Jiang

docs/source/models/supported-models.md

@@ -45,13 +45,13 @@ Note: Support for other models may vary. Features marked "N/A" are not applicabl
 
 | Model Architecture/Feature         | Overlap Scheduler | CUDA Graph | Chunked Prefill | Torch Sampler | TLLM C++ Sampler | KV Cache Reuse | Logits Post Processor | EPD Disaggregated Serving | Modality |
 | ---------------------------------- | ----------------- | ---------- | --------------- | ------------- | ---------------- | -------------- | --------------------- | ------------------------- | -------- |
-| Gemma3ForConditionalGeneration     | Yes               | Yes        | N/A             | Yes           | Yes              | N/A            | Yes                   | No                        | L + I    |
+| Gemma3ForConditionalGeneration     | Yes               | Yes        | N/A             | Yes           | Yes              | N/A            | Yes                   | No                        | L + I    |   
 | HCXVisionForCausalLM               | Yes               | Yes        | No              | Yes           | Yes              | No             | Yes                   | No                        | L + I    |
 | LlavaLlamaModel (VILA)             | Yes               | Yes        | No              | Yes           | Yes              | No             | Yes                   | No                        | L + I + V |
 | LlavaNextForConditionalGeneration  | Yes               | Yes        | No              | Yes           | Yes              | No             | Yes                   | No                        | L + I    |
 | Llama4ForConditionalGeneration     | Yes               | Yes        | No              | Yes           | Yes              | No             | Yes                   | No                        | L + I    |
 | Mistral3ForConditionalGeneration   | Yes               | Yes        | No              | Yes           | Yes              | No             | Yes                   | No                        | L + I    |
-| Phi4MMForCausalLM                  | Yes               | Yes        | No              | Yes           | Yes              | Yes            | Yes                   | No                        | L + I + A |
+| Phi4MMForCausalLM                  | Yes               | Yes        | No              | Yes           | Yes              | No             | Yes                   | No                        | L + I + A |
 | Qwen2VLForConditionalGeneration    | Yes               | Yes        | No              | Yes           | Yes              | Yes            | Yes                   | No                        | L + I + V |
 | Qwen2_5_VLForConditionalGeneration | Yes               | Yes        | No              | Yes           | Yes              | Yes            | Yes                   | No                        | L + I + V |
 

docs/source/reference/multimodal-feature-support-matrix.md

@@ -8,6 +8,6 @@
 | LLaVA-NeXT         | Yes        | Yes                 | Yes            | Yes             |
 | Llama 4            | Yes        | Yes                 | No             | No              |
 | Mistral-Small-3.1  | Yes        | Yes                 | No             | No              |
-| Phi-4-multimodal   | Yes        | Yes                 | Yes            | No              |
+| Phi-4-multimodal   | Yes        | Yes                 | No             | No              |
 | Qwen2-VL           | Yes        | Yes                 | Yes            | Yes             |
 | Qwen2.5-VL         | Yes        | Yes                 | Yes            | Yes             |

tensorrt_llm/_torch/models/modeling_phi4mm.py

@@ -19,8 +19,8 @@
 from tensorrt_llm.inputs.multimodal import MultimodalParams
 
 from ...executor.request import LoRARequest
-from ...inputs import (BaseMultimodalInputProcessor, ExtraProcessedInputs,
-                       InputProcessor, MultimodalPlaceholderMetadata,
+from ...inputs import (ExtraProcessedInputs, InputProcessor,
+                       MultimodalPlaceholderMetadata,
                        MultimodalPlaceholderPlacement, TextPrompt,
                        register_input_processor)
 from ...logger import logger
@@ -29,8 +29,7 @@
 from ..attention_backend import AttentionMetadata
 from ..model_config import ModelConfig
 from .modeling_auto import AutoModelForCausalLM
-from .modeling_multimodal_utils import (find_uncached_mm_embeds,
-                                        fuse_input_embeds)
+from .modeling_multimodal_utils import fuse_input_embeds
 from .modeling_utils import register_auto_model
 
 # Special token ids from the original Phi-4-multimodal-instruct implementation
@@ -390,7 +389,7 @@ def forward(self, multimodal_params: List[MultimodalParams],
             return self._encoding_batch_request(multimodal_params, mm_token_ids)
 
 
-class Phi4MMInputProcessor(BaseMultimodalInputProcessor, InputProcessor):
+class Phi4MMInputProcessor(InputProcessor):
 
     def __init__(self,
                  model_path: str,
@@ -416,20 +415,6 @@ def __init__(self,
             trust_remote_code=trust_remote_code,
             use_fast=self.use_fast)
 
-    def get_mm_token_ids(self) -> Optional[torch.Tensor]:
-        return torch.tensor([_IMAGE_SPECIAL_TOKEN_ID, _AUDIO_SPECIAL_TOKEN_ID],
-                            dtype=torch.int32,
-                            device=self.device)
-
-    def get_num_tokens_per_image(
-        self,
-        *,
-        image: Image.Image,
-        **kwargs,
-    ):
-        data = self.processor.image_processor.preprocess(image)
-        return data["num_img_tokens"][0]
-
     @torch.inference_mode()
     def __call__(
         self, inputs: TextPrompt, sampling_params: SamplingParams
@@ -604,9 +589,6 @@ def forward(
                     multimodal_param.multimodal_data["multimodal_embedding"]
                     for multimodal_param in multimodal_params
                 ]
-            mm_embedding = find_uncached_mm_embeds(
-                mm_embedding, multimodal_params[:num_context_requests])
-
         input_ids, input_embeds = fuse_input_embeds(
             self.llm.model.embed_tokens,
             input_ids,