code: def get_zero_tensor(length, cur_size, device, pos):
      if length not in zero_cache_dict:
          tmp_size = cur_size[:]
          tmp_size[pos] = length
          zero_cache_dict[length] = torch.zeros(tmp_size, device=device)
      return zero_cache_dict[length].narrow(
          pos, 0, length - cur_size[pos]
      )
  
imports: import torch
  from torch import nn
  from typing import Optional, Tuple, List, Type, Dict
  from transformers import LlamaConfig
  from bigdl.llm.vllm.sequence import SequenceOutputs, SequenceGroupMetadata
  from bigdl.llm.transformers.models.utils import extend_kv_cache
  from bigdl.llm.vllm.logger import init_logger
label_desc: Use image node_id 1 for calling a global function with example usage: get_zero_tensor(length, cur_size, device, pos) and returns: zero_cache_dict