code: def use_flash_attention(query, key):
      # here we support query's shape is always [batch_size, head_num, q_len, head_dim],
      # key's shape is always [batch_size, head_num, k_len, head_dim]
      invalidInputError(
          query.dim() == 4,
          "Here query input of use_flash_attention should be [batch_size, "
          "head_num, q_len, head_dim]",
      )
      invalidInputError(
          key.dim() == 4,
          "Here key input of use_flash_attention should be [batch_size, "
          "head_num, k_len, head_dim]",
      )
      bsz, _, q_len, _ = query.size()
      k_len = key.size()[2]
      # check whether ipex flash attention can be used
      if bsz > 1:
          # only use flash attention for batch_size = 1 now
          # as flash attention doesn't support attn_mask in ipex 2.1,
          # so it will cause output error for padded batch input
          return False
      if q_len != k_len:
          # now only use flash attention for first token
          # as it seems have no performance benifit for rest token now
          return False
      if query.device.type != "xpu":
          # ipex flash attention only support for xpu
          return False
      ipex_version = get_ipex_version()
      if ipex_version <= "2.0.110+xpu":
          # ipex flash attention is supported from ipex 2.1
          return False
      if not torch.xpu.has_xetla():
          # ipex flash attention is only supported for xetla
          # may update this later
          return False
      if query.dtype not in [torch.float32, torch.float16]:
          # only use flash attention for fp32/fp16 input
          return False
      return True
  
imports: import os
  import torch
  from bigdl.llm.utils.common import invalidInputError
  from bigdl.llm.ggml.quantize import ggml_tensor_qtype
  from bigdl.llm.transformers.utils import get_ipex_version, get_xpu_device_type
label_desc: Use image node_id 15 for calling a global function with example usage: use_flash_attention(query, key) and returns: True, False, False, False, False, False, False