code: def generate_image_tensor(image_file):
      image = load_image(image_file)
      model_cfg = {"image_aspect_ratio": "pad"}
      image_tensor = process_images([image], image_processor, model_cfg)
      return image_tensor
  
file_path: BigDL/python/llm/example/GPU/PyTorch-Models/Model/llava/generate.py
imports: import argparse
  import torch
  import time
  from transformers import AutoModelForCausalLM
  from llava.model.language_model.llava_llama import LlavaLlamaForCausalLM
  from transformers import AutoTokenizer
  from llava.constants import DEFAULT_IMAGE_PATCH_TOKEN, IMAGE_TOKEN_INDEX, DEFAULT_IMAGE_TOKEN, DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN
  from llava.conversation import conv_templates, SeparatorStyle
  from llava.utils import disable_torch_init
  from llava.mm_utils import process_images, tokenizer_image_token, get_model_name_from_path, KeywordsStoppingCriteria
  from bigdl.llm import optimize_model
label_desc: Use image node_id 4 for calling a global function with example usage: generate_image_tensor(image_file) and returns: image_tensor