数据更新：
python脚本（注意分支）：
HLO图分析KV-Cache更新：
KV-Cache作为HLO图的输入输出：bf16[1,2048,32,128]{3,2,1,0} 128x, 2x32x2
参考链接
notes for transformer introduction by an Italian teaching in China: Attention is all you need (Transformer) - Model explanation (including math), Inference and Training
notes for and LLaMa: LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU
github 使用XLA_GPU，选择分支llama2-google-next-inference
pytorch.org: path-achieve-low-inference-latency