Merge branch 'pact_clip' of https://github.com/baiyfbupt/PaddleSlim into develop

docs/zh_cn/tutorials/image_classification_mkldnn_quant_tutorial.md

-# CPU上部署量化模型教程
+# Intel CPU上部署量化模型教程
 
 在Intel Casecade Lake机器上（如：Intel(R) Xeon(R) Gold 6271），经过量化和DNNL加速，INT8模型在单线程上性能为FP32模型的3~3.7倍；在Intel SkyLake机器上（如：Intel(R) Xeon(R) Gold 6148），单线程性能为FP32模型的1.5倍，而精度仅有极小下降。图像分类量化的样例教程请参考[图像分类INT8模型在CPU优化部署和预测](https://github.com/PaddlePaddle/PaddleSlim/tree/develop/demo/mkldnn_quant/README.md)。自然语言处理模型的量化请参考[ERNIE INT8 模型精度与性能复现](https://github.com/PaddlePaddle/benchmark/tree/master/Inference/c%2B%2B/ernie/mkldnn)
 

docs/zh_cn/tutorials/index.rst

@@ -12,5 +12,5 @@
    paddledetection_slim_pruing_tutorial.md
    paddledetection_slim_prune_dist_tutorial.md
    paddledetection_slim_quantization_tutorial.md
-   image_classification_mkldnn_quant_aware_tutorial.md
+   image_classification_mkldnn_quant_tutorial.md
    paddledetection_slim_sensitivy_tutorial.md