docs: add en doc

Author: TingquanGao

deploy/paddle2onnx/readme_en.md

@@ -0,0 +1,59 @@
+# Paddle2ONNX: Converting To ONNX and Deployment
+
+This section introduce that how to convert the Paddle Inference Model ResNet50_vd to ONNX model and deployment based on ONNX engine.
+
+## 1. Installation
+
+First, you need to install Paddle2ONNX and onnxruntime. Paddle2ONNX is a toolkit to convert Paddle Inference Model to ONNX model. Please refer to [Paddle2ONNX](https://github.com/PaddlePaddle/Paddle2ONNX/blob/develop/README_en.md) for more information.
+
+- Paddle2ONNX Installation
+```
+python3.7 -m pip install paddle2onnx
+```
+
+- ONNX Installation
+```
+python3.7 -m pip install onnxruntime
+```
+
+## 2. Converting to ONNX
+
+Download the Paddle Inference Model ResNet50_vd:
+
+```
+cd deploy
+mkdir models && cd models
+wget -nc https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/ResNet50_vd_infer.tar && tar xf ResNet50_vd_infer.tar
+cd ..
+```
+
+Converting to ONNX model:
+
+```
+paddle2onnx --model_dir=./models/ResNet50_vd_infer/ \
+--model_filename=inference.pdmodel \
+--params_filename=inference.pdiparams \
+--save_file=./models/ResNet50_vd_infer/inference.onnx \
+--opset_version=10 \
+--enable_onnx_checker=True
+```
+
+After running the above command, the ONNX model file converted would be save in  `./models/ResNet50_vd_infer/`.
+
+## 3. Deployment
+
+Deployment with ONNX model, command is as shown below.
+
+```
+python3.7 python/predict_cls.py \
+-c configs/inference_cls.yaml \
+-o Global.use_onnx=True \
+-o Global.use_gpu=False \
+-o Global.inference_model_dir=./models/ResNet50_vd_infer
+```
+
+The prediction results:
+
+```
+ILSVRC2012_val_00000010.jpeg:   class id(s): [153, 204, 229, 332, 155], score(s): [0.69, 0.10, 0.02, 0.01, 0.01], label_name(s): ['Maltese dog, Maltese terrier, Maltese', 'Lhasa, Lhasa apso', 'Old English sheepdog, bobtail', 'Angora, Angora rabbit', 'Shih-Tzu']
+```

docs/en/PULC/PULC_person_exists_en.md

@@ -32,7 +32,7 @@
   - [6.3 Deployment with C++](#6.3)
   - [6.4 Deployment as Service](#6.4)
   - [6.5 Deployment on Mobile](#6.5)
-  - [6.6 To ONNX and Deployment](#6.6)
+  - [6.6 Converting To ONNX and Deployment](#6.6)
 
 
 <a name="1"></a>
@@ -274,7 +274,7 @@ The results:
 
 ### 4.1 SKL-UGI Knowledge Distillation
 
-SKL-UGI is a simple but effective knowledge distillation algrithem proposed by PaddleClas. Please refer to [SKL-UGI 知识蒸馏](../advanced_tutorials/ssld_en.md) for more details.
+SKL-UGI is a simple but effective knowledge distillation algrithem proposed by PaddleClas. Please refer to [SKL-UGI 知识蒸馏](../advanced_tutorials/distillation/distillation_en.md) for more details.
 
 <a name="4.1.1"></a>
 
@@ -450,7 +450,7 @@ PaddleClas provides an example of how to deploy on mobile by Paddle-Lite. Please
 
 <a name="6.6"></a>
 
-### 6.6 To ONNX and Deployment
+### 6.6 Converting To ONNX and Deployment
 
 Paddle2ONNX support convert Paddle Inference model to ONNX model. And you can deploy with ONNX model on different inference engine, such as TensorRT, OpenVINO, MNN/TNN, NCNN and so on. About Paddle2ONNX details, please refer to [Paddle2ONNX](https://github.com/PaddlePaddle/Paddle2ONNX).