fix doc for whl (#552)

README.md

@@ -7,6 +7,7 @@
 PaddleClas is a toolset for image classification tasks prepared for the industry and academia. It helps users train better computer vision models and apply them in real scenarios.
 
 **Recent update**
+- 2021.01.08 Add support for whl package and its usage, Model inference can be done by simply install paddleclas using pip.
 - 2020.12.16 Add support for TensorRT when using cpp inference to obain more obvious acceleration.
 - 2020.12.06 Add `SE_HRNet_W64_C_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 84.75%.
 - 2020.11.23 Add `GhostNet_x1_3_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 79.38%.
@@ -15,7 +16,6 @@ PaddleClas is a toolset for image classification tasks prepared for the industry
 - 2020.10.12 Add Paddle-Lite demo。
 - 2020.10.10 Add cpp inference demo and improve FAQ tutorial.
 - 2020.09.17 Add `HRNet_W48_C_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 83.62%. Add `ResNet34_vd_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 79.72%.
-- 2020.09.07 Add `HRNet_W18_C_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 81.16%.
 - [more](./docs/en/update_history_en.md)
 
 
@@ -79,6 +79,7 @@ PaddleClas is a toolset for image classification tasks prepared for the industry
     - [C++ inference](./deploy/cpp_infer/readme_en.md)
     - [Serving deployment](./deploy/hubserving/readme_en.md)
     - [Mobile](./deploy/lite/readme_en.md)
+    - [Inference using whl ](./docs/en/whl_en.md)
     - [Model Quantization and Compression](docs/en/extension/paddle_quantization_en.md)
 - Advanced tutorials
     - [Knowledge distillation](./docs/en/advanced_tutorials/distillation/distillation_en.md)

README_cn.md

@@ -8,6 +8,7 @@
 
 
 **近期更新**
+- 2021.01.08 添加whl包及其使用说明，直接安装paddleclas whl包，即可快速完成模型预测。
 - 2020.12.16 添加对cpp预测的tensorRT支持，预测加速更明显。
 - 2020.12.06 添加`SE_HRNet_W64_C_ssld`模型，在ImageNet-1k上Top-1 Acc可达84.75%。
 - 2020.11.23 添加`GhostNet_x1_3_ssld `模型，在ImageNet-1k上Top-1 Acc可达79.38%。
@@ -15,7 +16,6 @@
 - 2020.10.20 添加 `Res2Net50_vd_26w_4s_ssld `模型，在ImageNet-1k上Top-1 Acc可达83.1%；添加 `Res2Net101_vd_26w_4s_ssld `模型，在ImageNet-1k上Top-1 Acc可达83.9%。
 - 2020.10.12 添加Paddle-Lite demo。
 - 2020.10.10 添加cpp inference demo，完善`FAQ 30问`教程。
-- 2020.09.17 添加 `HRNet_W48_C_ssld `模型，在ImageNet-1k上Top-1 Acc可达83.62%；添加 `ResNet34_vd_ssld `模型，在ImageNet-1k上Top-1 Acc可达79.72%。
 - [more](./docs/zh_CN/update_history.md)
 
 
@@ -79,6 +79,7 @@
     - [基于C++预测引擎预测推理](./deploy/cpp_infer/readme.md)
     - [服务化部署](./deploy/hubserving/readme.md)
     - [端侧部署](./deploy/lite/readme.md)
+    - [whl包预测](./docs/zh_CN/whl.md)
     - [模型量化压缩](docs/zh_CN/extension/paddle_quantization.md)
 - 高阶使用
     - [知识蒸馏](./docs/zh_CN/advanced_tutorials/distillation/distillation.md)

docs/en/update_history_en.md

 # Release Notes
 
+- 2021.01.08
+    * Add support for whl package and its usage, Model inference can be done by simply install paddleclas using pip.
+
 - 2020.12.16
     * Add support for TensorRT when using cpp inference to obain more obvious acceleration.
 

docs/zh_CN/update_history.md

 # 更新日志
 
+- 2021.01.08
+    * 添加whl包及其使用说明，直接安装paddleclas whl包，即可快速完成模型预测。
+
 - 2020.12.16
     * 添加对cpp预测的tensorRT支持，预测加速更明显。