IMDB_GO_CLIENT.md

# How to use Go Client of Paddle Serving

([简体中文](./IMDB_GO_CLIENT_CN.md)|English)

This document shows how to use Go as your client language. For Go client in Paddle Serving, a simple client package is provided https://github.com/PaddlePaddle/Serving/tree/develop/go/serving_client, a user can import this package as needed. Here is a simple example of sentiment analysis task based on IMDB dataset.

### Install

We suppose you have 1.9.2 or later version installed and python 2.7 version installed

```shell
go get github.com/PaddlePaddle/Serving/go/serving_client
go get github.com/PaddlePaddle/Serving/go/proto
pip install paddle-serving-server
```

### Download Text Classification Model

``` shell
wget https://paddle-serving.bj.bcebos.com/data/text_classification/imdb_serving_example.tar.gz
tar -xzf imdb_serving_example.tar.gz
```

### Start Server

``` shell
python -m paddle_serving_server.serve --model ./serving_server_model/ --port 9292
```

### Client code example

``` go
// imdb_client.go
package main

import (
       "io"
       "fmt"
       "strings"
       "bufio"
       "strconv"
       "os"
       serving_client "github.com/PaddlePaddle/Serving/go/serving_client"
)

func main() {
     var config_file_path string
     config_file_path = os.Args[1]
     handle := serving_client.LoadModelConfig(config_file_path)
     handle = serving_client.Connect("127.0.0.1", "9292", handle)

     test_file_path := os.Args[2]
     fi, err := os.Open(test_file_path)
     if err != nil {
     	fmt.Print(err)
     }

     defer fi.Close()
     br := bufio.NewReader(fi)

     fetch := []string{"cost", "acc", "prediction"}     

     var result map[string][]float32

     for {
     	 line, err := br.ReadString('\n')
	 if err == io.EOF {
	       break
	 }

	 line = strings.Trim(line, "\n")

	 var words = []int64{}

	 s := strings.Split(line, " ")
	 value, err := strconv.Atoi(s[0])
	 var feed_int_map map[string][]int64
       
	 for _, v := range s[1:value + 1] {
	       int_v, _ := strconv.Atoi(v)
	       words = append(words, int64(int_v))
	 }

	 label, err := strconv.Atoi(s[len(s)-1])

	 if err != nil {
	       panic(err)
	 }

	 feed_int_map = map[string][]int64{}
	 feed_int_map["words"] = words
	 feed_int_map["label"] = []int64{int64(label)}
	 
	 result = serving_client.Predict(handle, feed_int_map, fetch)
	 fmt.Println(result["prediction"][1], "\t", int64(label))
    }
}
```

### Prediction based on IMDB Test set

``` python
go run imdb_client.go serving_client_conf/serving_client_conf.stream.prototxt test.data > result
```



### Compute accuracy

```python
// acc.go
package main

import (
       "io"
       "os"
       "fmt"
       "bufio"
       "strings"
       "strconv"
)

func main() {
     score_file := os.Args[1]
     fi, err := os.Open(score_file)
     if err != nil {
     	fmt.Print(err)
     }

     defer fi.Close()
     br := bufio.NewReader(fi)     
    
     total := int(0)
     acc := int(0)
     for {
     	 line, err := br.ReadString('\n')
     if err == io.EOF {
        break
     }
    
     line = strings.Trim(line, "\n")
     s := strings.Split(line, "\t")
     prob_str := strings.Trim(s[0], " ")
     label_str := strings.Trim(s[1], " ")
     prob, err := strconv.ParseFloat(prob_str, 32)
     if err != nil {
        panic(err)
     }
     label, err := strconv.ParseFloat(label_str, 32)
     if err != nil {
        panic(err)
     }
     if (prob - 0.5) * (label - 0.5) > 0 {
        acc++
     }
     total++
    }
    fmt.Println("total num: ", total)
    fmt.Println("acc num: ", acc)
    fmt.Println("acc: ", float32(acc) / float32(total))    

}
```

```shell
go run acc.go result
total num:  25000
acc num:  22014
acc:  0.88056
```