[Model] Add multi-image input support for LLaVA-Next offline inference (#7230)

vllm/model_executor/models/clip.py

@@ -1,7 +1,7 @@
-"""Minimal implementation of CLIPVisionModel intended to be only used 
+"""Minimal implementation of CLIPVisionModel intended to be only used
 within a vision language model."""
 from array import array
-from typing import Iterable, Optional, Tuple
+from typing import Iterable, List, Optional, Tuple, Union
 
 import torch
 import torch.nn as nn
@@ -84,7 +84,7 @@ def input_processor_for_clip(
     llm_inputs: LLMInputs,
     *,
     image_token_id: int,
-    image_feature_size_override: Optional[int] = None,
+    image_feature_size_override: Optional[Union[int, List[int]]] = None,
 ):
     multi_modal_data = llm_inputs.get("multi_modal_data")
     if multi_modal_data is None or "image" not in multi_modal_data:
@@ -217,7 +217,7 @@ class CLIPEncoderLayer(nn.Module):
 
 class CLIPEncoder(nn.Module):
     """
-    Transformer encoder consisting of `config.num_hidden_layers` self 
+    Transformer encoder consisting of `config.num_hidden_layers` self
     attention layers. Each layer is a [`CLIPEncoderLayer`].
 
     Args: