[VLM] Use SequenceData.from_token_counts to create dummy data (#8687)

vllm/model_executor/models/minicpmv.py

@@ -23,7 +23,6 @@
 """Inference-only MiniCPM-V model compatible with HuggingFace weights."""
 import math
 import re
-from array import array
 from functools import partial
 from typing import (Any, Callable, Iterable, List, Mapping, Optional, Tuple,
                     TypedDict)
@@ -56,8 +55,7 @@ from vllm.model_executor.sampling_metadata import SamplingMetadata
 from vllm.multimodal import MULTIMODAL_REGISTRY
 from vllm.multimodal.image import cached_get_image_processor
 from vllm.multimodal.utils import cached_get_tokenizer
-from vllm.sequence import (VLLM_TOKEN_ID_ARRAY_TYPE, IntermediateTensors,
-                           SequenceData)
+from vllm.sequence import IntermediateTensors, SequenceData
 
 from .idefics2_vision_model import Idefics2VisionTransformer
 
@@ -259,8 +257,7 @@ def get_max_minicpmv_image_tokens(ctx: InputContext):
 
 
 def dummy_seq_data_for_minicpmv(seq_len: int, num_images: int):
-    token_ids = array(VLLM_TOKEN_ID_ARRAY_TYPE, [0]) * seq_len
-    return SequenceData(token_ids)
+    return SequenceData.from_token_counts((0, seq_len))
 
 
 def dummy_image_for_minicpmv(hf_config: PretrainedConfig, num_images: int):