提交 995698f3 编写于 作者: G guru4elephant

add imdb example for go client

上级 b7694543
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))
}
\ No newline at end of file
......@@ -16,10 +16,10 @@ package main
import (
"io"
"fmt"
"strings"
"bufio"
"strconv"
"fmt"
"os"
"serving_client"
)
......@@ -28,7 +28,7 @@ func main() {
var config_file_path string
config_file_path = os.Args[1]
handle := serving_client.LoadModelConfig(config_file_path)
serving_client.Connect("127.0.0.1", 9292, handle)
handle = serving_client.Connect("127.0.0.1", "9292", handle)
test_file_path := os.Args[2]
fi, err := os.Open(test_file_path)
......@@ -49,6 +49,8 @@ func main() {
break
}
line = strings.Trim(line, "\n")
var words = []int64{}
s := strings.Split(line, " ")
......@@ -60,13 +62,18 @@ func main() {
words = append(words, int64(int_v))
}
label, _ := strconv.Atoi(s[len(s)-1])
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"][0])
fmt.Println(result["prediction"][1], "\t", int64(label))
}
}
\ No newline at end of file
// Code generated by protoc-gen-go. DO NOT EDIT.
// source: general_model_config.proto
package baidu_paddle_serving_configure
import (
fmt "fmt"
proto "github.com/golang/protobuf/proto"
math "math"
)
// Reference imports to suppress errors if they are not otherwise used.
var _ = proto.Marshal
var _ = fmt.Errorf
var _ = math.Inf
// This is a compile-time assertion to ensure that this generated file
// is compatible with the proto package it is being compiled against.
// A compilation error at this line likely means your copy of the
// proto package needs to be updated.
const _ = proto.ProtoPackageIsVersion3 // please upgrade the proto package
type FeedVar struct {
Name *string `protobuf:"bytes,1,opt,name=name" json:"name,omitempty"`
AliasName *string `protobuf:"bytes,2,opt,name=alias_name,json=aliasName" json:"alias_name,omitempty"`
IsLodTensor *bool `protobuf:"varint,3,opt,name=is_lod_tensor,json=isLodTensor,def=0" json:"is_lod_tensor,omitempty"`
FeedType *int32 `protobuf:"varint,4,opt,name=feed_type,json=feedType,def=0" json:"feed_type,omitempty"`
Shape []int32 `protobuf:"varint,5,rep,name=shape" json:"shape,omitempty"`
XXX_NoUnkeyedLiteral struct{} `json:"-"`
XXX_unrecognized []byte `json:"-"`
XXX_sizecache int32 `json:"-"`
}
func (m *FeedVar) Reset() { *m = FeedVar{} }
func (m *FeedVar) String() string { return proto.CompactTextString(m) }
func (*FeedVar) ProtoMessage() {}
func (*FeedVar) Descriptor() ([]byte, []int) {
return fileDescriptor_efa52beffa29d37a, []int{0}
}
func (m *FeedVar) XXX_Unmarshal(b []byte) error {
return xxx_messageInfo_FeedVar.Unmarshal(m, b)
}
func (m *FeedVar) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
return xxx_messageInfo_FeedVar.Marshal(b, m, deterministic)
}
func (m *FeedVar) XXX_Merge(src proto.Message) {
xxx_messageInfo_FeedVar.Merge(m, src)
}
func (m *FeedVar) XXX_Size() int {
return xxx_messageInfo_FeedVar.Size(m)
}
func (m *FeedVar) XXX_DiscardUnknown() {
xxx_messageInfo_FeedVar.DiscardUnknown(m)
}
var xxx_messageInfo_FeedVar proto.InternalMessageInfo
const Default_FeedVar_IsLodTensor bool = false
const Default_FeedVar_FeedType int32 = 0
func (m *FeedVar) GetName() string {
if m != nil && m.Name != nil {
return *m.Name
}
return ""
}
func (m *FeedVar) GetAliasName() string {
if m != nil && m.AliasName != nil {
return *m.AliasName
}
return ""
}
func (m *FeedVar) GetIsLodTensor() bool {
if m != nil && m.IsLodTensor != nil {
return *m.IsLodTensor
}
return Default_FeedVar_IsLodTensor
}
func (m *FeedVar) GetFeedType() int32 {
if m != nil && m.FeedType != nil {
return *m.FeedType
}
return Default_FeedVar_FeedType
}
func (m *FeedVar) GetShape() []int32 {
if m != nil {
return m.Shape
}
return nil
}
type FetchVar struct {
Name *string `protobuf:"bytes,1,opt,name=name" json:"name,omitempty"`
AliasName *string `protobuf:"bytes,2,opt,name=alias_name,json=aliasName" json:"alias_name,omitempty"`
IsLodTensor *bool `protobuf:"varint,3,opt,name=is_lod_tensor,json=isLodTensor,def=0" json:"is_lod_tensor,omitempty"`
Shape []int32 `protobuf:"varint,4,rep,name=shape" json:"shape,omitempty"`
XXX_NoUnkeyedLiteral struct{} `json:"-"`
XXX_unrecognized []byte `json:"-"`
XXX_sizecache int32 `json:"-"`
}
func (m *FetchVar) Reset() { *m = FetchVar{} }
func (m *FetchVar) String() string { return proto.CompactTextString(m) }
func (*FetchVar) ProtoMessage() {}
func (*FetchVar) Descriptor() ([]byte, []int) {
return fileDescriptor_efa52beffa29d37a, []int{1}
}
func (m *FetchVar) XXX_Unmarshal(b []byte) error {
return xxx_messageInfo_FetchVar.Unmarshal(m, b)
}
func (m *FetchVar) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
return xxx_messageInfo_FetchVar.Marshal(b, m, deterministic)
}
func (m *FetchVar) XXX_Merge(src proto.Message) {
xxx_messageInfo_FetchVar.Merge(m, src)
}
func (m *FetchVar) XXX_Size() int {
return xxx_messageInfo_FetchVar.Size(m)
}
func (m *FetchVar) XXX_DiscardUnknown() {
xxx_messageInfo_FetchVar.DiscardUnknown(m)
}
var xxx_messageInfo_FetchVar proto.InternalMessageInfo
const Default_FetchVar_IsLodTensor bool = false
func (m *FetchVar) GetName() string {
if m != nil && m.Name != nil {
return *m.Name
}
return ""
}
func (m *FetchVar) GetAliasName() string {
if m != nil && m.AliasName != nil {
return *m.AliasName
}
return ""
}
func (m *FetchVar) GetIsLodTensor() bool {
if m != nil && m.IsLodTensor != nil {
return *m.IsLodTensor
}
return Default_FetchVar_IsLodTensor
}
func (m *FetchVar) GetShape() []int32 {
if m != nil {
return m.Shape
}
return nil
}
type GeneralModelConfig struct {
FeedVar []*FeedVar `protobuf:"bytes,1,rep,name=feed_var,json=feedVar" json:"feed_var,omitempty"`
FetchVar []*FetchVar `protobuf:"bytes,2,rep,name=fetch_var,json=fetchVar" json:"fetch_var,omitempty"`
XXX_NoUnkeyedLiteral struct{} `json:"-"`
XXX_unrecognized []byte `json:"-"`
XXX_sizecache int32 `json:"-"`
}
func (m *GeneralModelConfig) Reset() { *m = GeneralModelConfig{} }
func (m *GeneralModelConfig) String() string { return proto.CompactTextString(m) }
func (*GeneralModelConfig) ProtoMessage() {}
func (*GeneralModelConfig) Descriptor() ([]byte, []int) {
return fileDescriptor_efa52beffa29d37a, []int{2}
}
func (m *GeneralModelConfig) XXX_Unmarshal(b []byte) error {
return xxx_messageInfo_GeneralModelConfig.Unmarshal(m, b)
}
func (m *GeneralModelConfig) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
return xxx_messageInfo_GeneralModelConfig.Marshal(b, m, deterministic)
}
func (m *GeneralModelConfig) XXX_Merge(src proto.Message) {
xxx_messageInfo_GeneralModelConfig.Merge(m, src)
}
func (m *GeneralModelConfig) XXX_Size() int {
return xxx_messageInfo_GeneralModelConfig.Size(m)
}
func (m *GeneralModelConfig) XXX_DiscardUnknown() {
xxx_messageInfo_GeneralModelConfig.DiscardUnknown(m)
}
var xxx_messageInfo_GeneralModelConfig proto.InternalMessageInfo
func (m *GeneralModelConfig) GetFeedVar() []*FeedVar {
if m != nil {
return m.FeedVar
}
return nil
}
func (m *GeneralModelConfig) GetFetchVar() []*FetchVar {
if m != nil {
return m.FetchVar
}
return nil
}
func init() {
proto.RegisterType((*FeedVar)(nil), "baidu.paddle_serving.configure.FeedVar")
proto.RegisterType((*FetchVar)(nil), "baidu.paddle_serving.configure.FetchVar")
proto.RegisterType((*GeneralModelConfig)(nil), "baidu.paddle_serving.configure.GeneralModelConfig")
}
func init() { proto.RegisterFile("general_model_config.proto", fileDescriptor_efa52beffa29d37a) }
var fileDescriptor_efa52beffa29d37a = []byte{
// 283 bytes of a gzipped FileDescriptorProto
0x1f, 0x8b, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0xff, 0xb4, 0xd0, 0x31, 0x4b, 0xc4, 0x30,
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0x52, 0xc4, 0xf1, 0x46, 0xc5, 0x73, 0x51, 0x87, 0x72, 0xb8, 0x86, 0xd8, 0xbc, 0xb6, 0x81, 0x5c,
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0x79, 0xff, 0xf0, 0xde, 0xe3, 0x07, 0x17, 0x2d, 0xf6, 0x68, 0x85, 0xe6, 0x3b, 0x23, 0x51, 0xf3,
0xda, 0xf4, 0x8d, 0x6a, 0xcb, 0xc1, 0x9a, 0xd1, 0xd0, 0xe5, 0x9b, 0x50, 0x72, 0x5f, 0x0e, 0x42,
0x4a, 0x8d, 0xdc, 0xa1, 0x3d, 0xa8, 0xbe, 0x2d, 0xc3, 0x97, 0xbd, 0xc5, 0xd5, 0x07, 0x81, 0xf9,
0x06, 0x51, 0xbe, 0x0a, 0x4b, 0x29, 0xc4, 0xbd, 0xd8, 0x61, 0x4e, 0x0a, 0xc2, 0xb2, 0xca, 0xd7,
0xf4, 0x12, 0x40, 0x68, 0x25, 0x1c, 0xf7, 0xc9, 0xcc, 0x27, 0x99, 0xef, 0xbc, 0x4c, 0xf1, 0x35,
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0x70, 0xac, 0xbb, 0xff, 0xbf, 0xef, 0x7b, 0x7f, 0xfc, 0x73, 0xff, 0x27, 0x01, 0xfa, 0x18, 0x78,
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0x00, 0xff, 0xff, 0x08, 0x27, 0x9c, 0x1a, 0xfe, 0x01, 0x00, 0x00,
}
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
package main
import (
"bytes"
"encoding/json"
"io/ioutil"
"log"
"net/http"
"encoding/binary"
"fmt"
"general_model_config"
)
type Tensor struct {
IntData []int64 `json:"int_data"`
ElemType int `json:"elem_type"`
Shape []int `json:"shape"`
}
type FeedInst struct {
TensorArray []Tensor `json:"tensor_array"`
}
type FetchInst struct {
TensorArray []Tensor `json:"tensor_array"`
}
type Request struct {
Insts []FeedInst `json:"insts"`
FetchVarNames []string `json:"fetch_var_names"`
}
type Response struct {
Insts []FetchInst `json:"insts"`
}
type Handle struct {
Url string
Port int
FeedAliasNameMap Map[string]string
FeedShapeMap Map[string][]int
FeedNameMap Map[string]int
FetchNameMap Map[string]int
FetchAliasNameMap Map[string]string
}
func LoadModelConfig(config string) Handle {
in, err := ioutil.ReadFile(config)
if err != nil {
log.Fatalln("Failed to read general model: ", err)
}
general_model_config := &pb.GeneralConfig{}
if err := proto.Unmarshal(in, general_model_config); err != nil {
log.Fatalln("Failed to parse GeneralConfig: ", err)
}
handle := Handle{}
for i, v in range general_model_config.FeedVar {
handle.FeedNameMap[v.Name] = i
handle.FeedShapeMap[v.Name] = v
handle.FeedAliasNameMap[v.AliasName] = v.Name
}
for i, v in range general_model_config.FetchVar {
handle.FetchNameMap[v.Name] = i
handle.FetchAliasNameMap[v.AliasName] = v.Name
}
return handle
}
func Connect(url string, port int, handle Handle) Handle {
handle.Url = url
handle.Port = port
return handle
}
func Predict(handle Handle, int_feed_map Map[string]int{}, fetch []string) {
contentType := "application/json;charset=utf-8"
var tensor_array []Tensor{}
var inst FeedInst
for k, v := range int_feed_map {
var tmp Tensor
tmp.Data = int_feed_map[k]
tmp.ElemType = 0
tmp.Shape = handle.FeedNameShape[k]
tensor_array = append(tensor_array, tmp)
}
req := &Request{
Insts: []FeedInst{inst},
FetchVarNames: []string{fetch}}
b, err := json.Marshal(req)
fmt.Println(string(b))
body := bytes.NewBuffer(b)
resp, err := http.Post(url, contentType, body)
if err != nil {
log.Println("Post failed:", err)
return
}
defer resp.Body.Close()
content, err := ioutil.ReadAll(resp.Body)
if err != nil {
log.Println("Read failed:", err)
return
}
log.Println("content:", string(content))
}
......@@ -20,12 +20,13 @@ import (
"io/ioutil"
"log"
"net/http"
"fmt"
pb "general_model"
"github.com/golang/protobuf/proto"
)
type Tensor struct {
Data []byte `json:"data"`
FloatData []float32 `json:"float_data"`
IntData []int64 `json:"int_data"`
ElemType int `json:"elem_type"`
Shape []int `json:"shape"`
......@@ -46,14 +47,16 @@ type Request struct {
type Response struct {
Insts []FetchInst `json:"insts"`
MeanInferUs float32 `json:"mean_infer_us"`
}
type Handle struct {
Url string
Port int
Port string
FeedAliasNameMap map[string]string
FeedShapeMap map[string][]int
FeedNameMap map[string]int
FeedAliasNames []string
FetchNameMap map[string]int
FetchAliasNameMap map[string]string
}
......@@ -67,16 +70,24 @@ func LoadModelConfig(config string) Handle {
if err := proto.Unmarshal(in, general_model_config); err != nil {
log.Fatalln("Failed to parse GeneralModelConfig: ", err)
}
log.Println("read protobuf succeed")
handle := Handle{}
handle.FeedNameMap = map[string]int{}
handle.FeedAliasNameMap = map[string]string{}
handle.FeedShapeMap = map[string][]int{}
handle.FetchNameMap = map[string]int{}
handle.FetchAliasNameMap = map[string]string{}
handle.FeedAliasNames = []string{}
for i, v := range general_model_config.FeedVar {
handle.FeedNameMap[*v.Name] = i
// handle.FeedShapeMap[*v.Name] := []int
tmp_array := []int{}
for _, vv := range v.Shape {
tmp_array = append(tmp_array, int(vv))
}
handle.FeedShapeMap[*v.Name] = tmp_array
handle.FeedAliasNameMap[*v.AliasName] = *v.Name
handle.FeedAliasNames = append(handle.FeedAliasNames, *v.AliasName)
}
for i, v := range general_model_config.FetchVar {
......@@ -87,7 +98,7 @@ func LoadModelConfig(config string) Handle {
return handle
}
func Connect(url string, port int, handle Handle) Handle {
func Connect(url string, port string, handle Handle) Handle {
handle.Url = url
handle.Port = port
return handle
......@@ -98,24 +109,38 @@ func Predict(handle Handle, int_feed_map map[string][]int64, fetch []string) map
var tensor_array []Tensor
var inst FeedInst
for k, _ := range int_feed_map {
var tmp Tensor
tmp.IntData = int_feed_map[k]
tensor_array = []Tensor{}
inst = FeedInst{}
for i := 0; i < len(handle.FeedAliasNames); i++ {
key_i := handle.FeedAliasNames[i]
var tmp Tensor
tmp.IntData = []int64{}
tmp.Shape = []int{}
tmp.IntData = int_feed_map[key_i]
tmp.ElemType = 0
tmp.Shape = handle.FeedShapeMap[k]
tmp.Shape = handle.FeedShapeMap[key_i]
tensor_array = append(tensor_array, tmp)
}
inst.TensorArray = tensor_array
req := &Request{
Insts: []FeedInst{inst},
FetchVarNames: fetch}
b, err := json.Marshal(req)
fmt.Println(string(b))
body := bytes.NewBuffer(b)
resp, err := http.Post(handle.Url, contentType, body)
var post_address bytes.Buffer
post_address.WriteString("http://")
post_address.WriteString(handle.Url)
post_address.WriteString(":")
post_address.WriteString(handle.Port)
post_address.WriteString("/GeneralModelService/inference")
resp, err := http.Post(post_address.String(), contentType, body)
if err != nil {
log.Println("Post failed:", err)
}
......@@ -124,11 +149,17 @@ func Predict(handle Handle, int_feed_map map[string][]int64, fetch []string) map
content, err := ioutil.ReadAll(resp.Body)
if err != nil {
log.Println("Read failed:", err)
log.Println("Read failed:", err)
}
log.Println("content:", string(content))
response_json := Response{}
err = json.Unmarshal([]byte(content), &response_json)
var result map[string][]float32
result = map[string][]float32{}
for i, v := range fetch {
result[v] = response_json.Insts[0].TensorArray[i].FloatData
}
return result
}
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