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Paddle-Lite
未验证 提交 2b9ea6ea 编写于 作者: Z zhangyang0701 提交者： GitHub
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Merge pull request #2 from PaddlePaddle/develop 

Update to the latest one.
上级 711beed5 4be6a2c1
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CMakeLists.txt
浏览文件 @ 2b9ea6ea
cmake_minimum_required(VERSION 3.0)
cmake_minimum_required(VERSION 3.6)
project(paddle-mobile)
option(DEBUGING "enable debug mode" ON)
option(USE_OPENMP "openmp support" OFF)
option(USE_OPENMP "openmp support" ON)
option(USE_EXCEPTION "use std exception" ON)
option(LOG_PROFILE "log profile" ON)
# select the platform to build
option(CPU "armv7 with neon" ON)
option(MALI_GPU "mali gpu" OFF)
option(FPGA "fpga" OFF)
set(DEBUGING ON)
if (ARM_LINUX)
include("${CMAKE_CURRENT_LIST_DIR}/tools/arm-platform.cmake")
endif ()
option(QUANTI "quantification" OFF)
file(GLOB_RECURSE PADDLE_MOBILE_CC src/*.cc src/*.cpp src/*.c src/*.mm)
file(GLOB_RECURSE PADDLE_MOBILE_H src/*.h)
include_directories(src/)
if(IS_IOS)
set(CMAKE_CXX_FLAGS "-mfpu=neon -marm -fobjc-abi-version=2 -fobjc-arc -std=gnu++11 -stdlib=libc++ -O3 -s -isysroot ${CMAKE_OSX_SYSROOT} ${CMAKE_CXX_FLAGS}")
else()
set(CMAKE_CXX_FLAGS "-std=c++14 -O3 -s ${CMAKE_CXX_FLAGS}")
endif()
if (DEBUGING)
message(STATUS "debug")
set(CMAKE_BUILD_TYPE Release)
set(CMAKE_CXX_FLAGS_RELEASE "-DNDEBUG")
add_definitions(-DPADDLE_MOBILE_DEBUG)
else ()
set(CMAKE_BUILD_TYPE Release)
set(CMAKE_CXX_FLAGS_RELEASE "-DNDEBUG")
add_definitions(-fvisibility=hidden -fvisibility-inlines-hidden)
endif ()
if (USE_EXCEPTION)
message(STATUS "use exception")
add_definitions(-DENABLE_EXCEPTION)
add_definitions(-fexceptions)
else()
add_definitions(-fno-exceptions)
endif ()
if (LOG_PROFILE)
add_definitions(-DPADDLE_MOBILE_PROFILE)
endif()
if(USE_OPENMP AND NOT IS_IOS)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fopenmp")
add_definitions(-DPADDLE_MOBILE_USE_OPENMP)
endif()
# platform control
if (ARM_LINUX)
include("${CMAKE_CURRENT_LIST_DIR}/tools/arm-platform.cmake")
endif ()
if (CPU)
add_definitions(-DPADDLE_MOBILE_CPU)
else()
list(REMOVE_ITEM PADDLE_MOBILE_CC ./src/operators/kernel/arm/*.h)
list(REMOVE_ITEM PADDLE_MOBILE_CC ./src/operators/kernel/arm/*.cc)
list(REMOVE_ITEM PADDLE_MOBILE_CC ./src/operators/kernel/arm/*.cpp)
file(GLOB_RECURSE _tmp_list src/operators/kernel/arm/*.cpp src/operators/kernel/arm/*.cc)
foreach(f ${_tmp_list})
list(REMOVE_ITEM PADDLE_MOBILE_CC ${f})
endforeach()
file(GLOB_RECURSE _tmp_list_h src/operators/kernel/arm/*.h)
foreach(f ${_tmp_list_h})
list(REMOVE_ITEM PADDLE_MOBILE_H ${f})
endforeach()
endif()
if (MALI_GPU)
......@@ -55,55 +96,32 @@ endif()
if(FPGA)
add_definitions(-DPADDLE_MOBILE_FPGA)
else()
list(REMOVE_ITEM PADDLE_MOBILE_CC ${CMAKE_CURRENT_SOURCE_DIR}/src/operators/kernel/fpga/*.h)
list(REMOVE_ITEM PADDLE_MOBILE_CC ${CMAKE_CURRENT_SOURCE_DIR}/src/operators/kernel/fpga/*.cc)
list(REMOVE_ITEM PADDLE_MOBILE_CC ${CMAKE_CURRENT_SOURCE_DIR}/src/operators/kernel/fpga/*.cpp)
file(GLOB_RECURSE _tmp_list src/operators/kernel/fpga/*.cpp src/operators/kernel/fpga/*.cc)
foreach(f ${_tmp_list})
list(REMOVE_ITEM PADDLE_MOBILE_CC ${f})
endforeach()
file(GLOB_RECURSE _tmp_list_h src/operators/kernel/fpga/*.h)
foreach(f ${_tmp_list_h})
list(REMOVE_ITEM PADDLE_MOBILE_H ${f})
endforeach()
endif()
set(CMAKE_CXX_FLAGS "-std=c++14 -O3 -s ${CMAKE_CXX_FLAGS}")
if (DEBUGING)
message(STATUS "debug")
set(CMAKE_BUILD_TYPE Debug)
set(CMAKE_CXX_FLAGS_DEBUG "-g -DNDEBUG")
add_definitions(-DPADDLE_MOBILE_DEBUG)
if (ANDROID_NDK_TOOLCHAIN_INCLUDED)
add_definitions(-DARMV7)
if (ANDROID_NDK_TOOLCHAIN_INCLUDED)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -llog")
endif ()
else ()
set(CMAKE_BUILD_TYPE Release)
set(CMAKE_CXX_FLAGS_RELEASE "-DNDEBUG")
add_definitions(-fvisibility=hidden -fvisibility-inlines-hidden)
endif ()
if (USE_EXCEPTION)
message(STATUS "use exception")
add_definitions(-DENABLE_EXCEPTION)
add_definitions(-fexceptions)
else()
add_definitions(-fno-exceptions)
endif ()
if (LOG_PROFILE)
add_definitions(-DPADDLE_MOBILE_PROFILE)
endif()
if(USE_OPENMP)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fopenmp")
add_definitions(-DPADDLE_MOBILE_USE_OPENMP)
endif()
if (NOT ANDROID_NDK_TOOLCHAIN_INCLUDED)
list(REMOVE_ITEM PADDLE_MOBILE_H ${CMAKE_CURRENT_SOURCE_DIR}/src/jni/paddle_mobile_jni.h)
list(REMOVE_ITEM PADDLE_MOBILE_CC ${CMAKE_CURRENT_SOURCE_DIR}/src/jni/paddle_mobile_jni.cpp)
list(REMOVE_ITEM PADDLE_MOBILE_H ${CMAKE_CURRENT_SOURCE_DIR}/src/operators/math/math_func_neon.h)
endif ()
include_directories(src/)
if (IS_IOS)
else()
list(REMOVE_ITEM PADDLE_MOBILE_H ${CMAKE_CURRENT_SOURCE_DIR}/src/ios_io/PaddleMobile.h)
list(REMOVE_ITEM PADDLE_MOBILE_CC ${CMAKE_CURRENT_SOURCE_DIR}/src/ios_io/PaddleMobile.mm)
list(REMOVE_ITEM PADDLE_MOBILE_H ${CMAKE_CURRENT_SOURCE_DIR}/src/ios_io/op_symbols.h)
endif ()
set(CMAKE_VERBOSE_MAKEFILE ON)
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
......@@ -114,26 +132,28 @@ set(CMAKE_RUNTIME_OUTPUT_DIRECTORY build)
# NET default
set(NET "defult" CACHE STRING "select net type")
set_property(CACHE NET PROPERTY STRINGS "defult" "googlenet" "mobilenet" "yolo" "squeezenet")
include("${CMAKE_CURRENT_LIST_DIR}/tools/op.cmake")
if (IS_IOS)
add_library(paddle-mobile STATIC ${PADDLE_MOBILE_CC} ${PADDLE_MOBILE_H})
else()
list(REMOVE_ITEM PADDLE_MOBILE_H ${CMAKE_CURRENT_SOURCE_DIR}/src/ios_io/PaddleMobile.h)
list(REMOVE_ITEM PADDLE_MOBILE_CC ${CMAKE_CURRENT_SOURCE_DIR}/src/ios_io/PaddleMobile.mm)
list(REMOVE_ITEM PADDLE_MOBILE_H ${CMAKE_CURRENT_SOURCE_DIR}/src/ios_io/op_symbols.h)
endif ()
# build library
if (ANDROID_NDK_TOOLCHAIN_INCLUDED)
list(REMOVE_DUPLICATES CMAKE_CXX_FLAGS)
add_library(paddle-mobile SHARED ${PADDLE_MOBILE_CC} ${PADDLE_MOBILE_H})
elseif(IS_IOS)
add_library(paddle-mobile STATIC ${PADDLE_MOBILE_CC} ${PADDLE_MOBILE_H})
else ()
add_library(paddle-mobile SHARED ${PADDLE_MOBILE_CC} ${PADDLE_MOBILE_H})
endif ()
# unit test
if(DEBUGING)
if(IS_IOS)
else()
add_subdirectory(test)
endif()
endif()
if (QUANTI)
add_subdirectory(tools/quantification)
endif ()
Dockerfile
浏览文件 @ 2b9ea6ea
......@@ -32,6 +32,7 @@ RUN cd /tmp && curl -O http://mirrors.neusoft.edu.cn/android/repository/android-
RUN curl -O https://mms-res.cdn.bcebos.com/cmake-3.10.3-Linux-x86_64.tar.gz && \
tar xzf cmake-3.10.3-Linux-x86_64.tar.gz && \
mv cmake-3.10.3-Linux-x86_64 /opt/cmake-3.10 && \
mv /usr/bin/cmake /usr/bin/cmake.bak && ln -s /opt/cmake-3.10/bin/cmake /usr/bin/cmake
mv /usr/bin/cmake /usr/bin/cmake.bak && ln -s /opt/cmake-3.10/bin/cmake /usr/bin/cmake && \
mv /usr/bin/ccmake /usr/bin/ccmake.bak && ln -s /opt/cmake-3.10/bin/ccmake /usr/bin/ccmake
RUN cd /opt && unzip /tmp/android-ndk-r17b-linux-x86_64.zip
ENV NDK_ROOT /opt/android-ndk-r17b
README.md
浏览文件 @ 2b9ea6ea
......@@ -26,8 +26,11 @@ Paddle-Moible是PaddlePaddle组织下的项目，是一个致力于嵌入式平
- **ARM CPU**
![](http://mms-graph.bj.bcebos.com/paddle-mobile%2F2018_07_18.png)
arm cpu是paddle-mobile的主要支持方向，cpu的通用性一直是其优势。嵌入式深度学习，需要大量的cpu汇编实现。我们正在紧锣密鼓的编码，为的是能充分硬件的每一点加速能力。
arm cpu的优化工作还在进行中，现在使用了常规的cpu优化。在arm a73上paddle-mobile现在单核运行一次mobilenet 1.0是160+ms，显然这不是我们的最终目标，我们正在用大量的汇编改写，后续性能仍会有巨大提升空间。
arm cpu的优化工作还在进行中，现在使用了常规的cpu优化。在arm a73上paddle-mobile arm-v7现在单核运行一次mobilenet1.0是110+ms，显然这不是我们的最终目标，我们正在用大量的汇编改写，后续性能仍会有巨大提升空间, 目前只支持armv7, 未来我们也会支持armv8。
- **Mali GPU**
......@@ -66,7 +69,7 @@ Paddle-Moible是PaddlePaddle组织下的项目，是一个致力于嵌入式平
### 开发文档
开发文档主要是关于编译、运行等问题。做为开发者，它可以和贡献文档共同结合使用。
[开发文档]()https://github.com/PaddlePaddle/paddle-mobile/blob/develop/doc/development_doc.md
[开发文档链接](https://github.com/PaddlePaddle/paddle-mobile/blob/develop/doc/development_doc.md)
### 贡献文档
- [贡献文档链接](https://github.com/PaddlePaddle/paddle-mobile/blob/develop/CONTRIBUTING.md)
......@@ -86,10 +89,10 @@ ONNX全称为“Open Neural Network Exchange”，即“开放的神经网络切
目前，百度也在做onnx支持工作。相关转换项目在这里：[paddle-onnx](https://github.com/PaddlePaddle/paddle-onnx)。
![](http://otkwwi4x8.bkt.clouddn.com/2018-07-03-15305875853057.jpg)
![](http://7xop3k.com1.z0.glb.clouddn.com/15311951836000.jpg)
### 4. 部分测试模型下载
[下载链接](https://mms-mis.cdn.bcebos.com/paddle-mobile/models.zip)
### 4. 部分测试模型和测试图片下载
[下载链接](http://mms-graph.bj.bcebos.com/paddle-mobile%2FmodelsAndImages.zip)
## 问题解决
......
demo/ReadMe.md 0 → 100644
浏览文件 @ 2b9ea6ea
## 如何运行demo
- Android demo下载路径
http://mms-graph.bj.bcebos.com/paddle-mobile%2FPaddleMobile_Android.zip
- iOS demo下载路径：
http://mms-graph.bj.bcebos.com/paddle-mobile%2FPaddleMobileDemo_iOS.zip
在demo目录下执行下载demo的脚本
```
sh getDemo.sh
```
demo工程就下载解压到当前目录中了。
\ No newline at end of file
demo/android/PaddleMobile_Android/.gitignore 已删除 100644 → 0
浏览文件 @ 711beed5
*.iml
.gradle
/local.properties
/.idea/workspace.xml
/.idea/libraries
.DS_Store
/build
/captures
.externalNativeBuild
demo/android/PaddleMobile_Android/app/build.gradle 已删除 100644 → 0
浏览文件 @ 711beed5
apply plugin: 'com.android.application'
android {
compileSdkVersion 21
defaultConfig {
applicationId "com.baidu.paddle"
minSdkVersion 15
targetSdkVersion 21
versionCode 1
versionName "1.0"
}
buildTypes {
release {
minifyEnabled false
proguardFiles getDefaultProguardFile('proguard-android.txt'), 'proguard-rules.pro'
}
}
}
dependencies {
implementation fileTree(dir: 'libs', include: ['*.jar'])
implementation 'com.android.support:appcompat-v7:21.0.3'
}
demo/android/PaddleMobile_Android/app/proguard-rules.pro 已删除 100644 → 0
浏览文件 @ 711beed5
# Add project specific ProGuard rules here.
# You can control the set of applied configuration files using the
# proguardFiles setting in build.gradle.
#
# For more details, see
# http://developer.android.com/guide/developing/tools/proguard.html
# If your project uses WebView with JS, uncomment the following
# and specify the fully qualified class name to the JavaScript interface
# class:
#-keepclassmembers class fqcn.of.javascript.interface.for.webview {
# public *;
#}
# Uncomment this to preserve the line number information for
# debugging stack traces.
#-keepattributes SourceFile,LineNumberTable
# If you keep the line number information, uncomment this to
# hide the original source file name.
#-renamesourcefileattribute SourceFile
demo/android/PaddleMobile_Android/app/src/main/AndroidManifest.xml 已删除 100644 → 0
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<manifest xmlns:android="http://schemas.android.com/apk/res/android"
package="com.baidu.paddle">
<!-- 往SDCard写入数据权限 -->
<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE" />
<uses-permission android:name="android.permission.CAMERA" />
<application
android:allowBackup="true"
android:icon="@mipmap/ic_launcher"
android:label="@string/app_name"
android:supportsRtl="true"
android:theme="@style/AppTheme" >
<activity
android:name=".MainActivity"
android:label="@string/app_name">
<intent-filter>
<action android:name="android.intent.action.MAIN" />
<category android:name="android.intent.category.LAUNCHER" />
</intent-filter>
</activity>
</application>
</manifest>
demo/android/PaddleMobile_Android/app/src/main/java/com/baidu/paddle/MainActivity.java 已删除 100755 → 0
浏览文件 @ 711beed5
/*
* Copyright (c) 2016 Baidu, Inc. All Rights Reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated
* documentation files (the "Software"), to deal in the Software without restriction, including without limitation
* the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and
* to permit persons to whom the Software is furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all copies or substantial portions of
* the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
* THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
* CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
* IN THE SOFTWARE.
*/
package com.baidu.paddle;
import android.app.Activity;
import android.content.Context;
import android.content.Intent;
import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.graphics.Canvas;
import android.graphics.Color;
import android.graphics.Paint;
import android.net.Uri;
import android.os.AsyncTask;
import android.os.Bundle;
import android.os.Environment;
import android.provider.MediaStore;
import android.util.Log;
import android.view.View;
import android.widget.Button;
import android.widget.ImageView;
import android.widget.TextView;
import android.widget.Toast;
import java.io.BufferedWriter;
import java.io.File;
import java.io.FileOutputStream;
import java.io.FileWriter;
import java.io.IOException;
import java.io.InputStream;
import static android.graphics.Color.blue;
import static android.graphics.Color.green;
import static android.graphics.Color.red;
import static com.baidu.paddle.MainActivity.TYPE.googlenet;
public class MainActivity extends Activity {
public static final int TAKE_PHOTO_REQUEST_CODE = 1001;
private Context mContext = null;
private int inputSize = 224;
enum TYPE {
googlenet
}
private TYPE type = googlenet;
private ImageView imageView;
private TextView tvSpeed;
private Button button;
private Bitmap bmp;
static {
try {
System.loadLibrary("paddle-mobile");
} catch (SecurityException e) {
e.printStackTrace();
} catch (UnsatisfiedLinkError e) {
e.printStackTrace();
} catch (NullPointerException e) {
e.printStackTrace();
}
}
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
mContext = this;
setContentView(R.layout.main_activity);
init();
}
private void init() {
imageView = (ImageView) findViewById(R.id.imageView);
tvSpeed = (TextView) findViewById(R.id.tv_speed);
button = (Button) findViewById(R.id.button);
button.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View view) {
if (!isHasSdCard()) {
Toast.makeText(mContext, R.string.sdcard_not_available,
Toast.LENGTH_LONG).show();
return;
}
Intent intent = new Intent(MediaStore.ACTION_IMAGE_CAPTURE);
// save pic in sdcard
Uri imageUri = Uri.fromFile(getTempImage());
intent.putExtra(MediaStore.EXTRA_OUTPUT, imageUri);
startActivityForResult(intent, TAKE_PHOTO_REQUEST_CODE);
}
});
Button bt_load = (Button) findViewById(R.id.bt_load);
bt_load.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View view) {
String assetPath = "pml_demo";
String sdcardPath = Environment.getExternalStorageDirectory()
+ File.separator + assetPath + File.separator + type;
PML.load(sdcardPath);
}
});
Button bt_clear = (Button) findViewById(R.id.bt_clear);
bt_clear.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View view) {
PML.clear();
}
});
String assetPath = "pml_demo";
String sdcardPath = Environment.getExternalStorageDirectory()
+ File.separator + assetPath;
copyFilesFromAssets(this, assetPath, sdcardPath);
}
public void copyFilesFromAssets(Context context, String oldPath, String newPath) {
try {
String[] fileNames = context.getAssets().list(oldPath);
if (fileNames.length > 0) {
// directory
File file = new File(newPath);
file.mkdirs();
// copy recursivelyC
for (String fileName : fileNames) {
copyFilesFromAssets(context, oldPath + "/" + fileName,
newPath + "/" + fileName);
}
} else {
// file
InputStream is = context.getAssets().open(oldPath);
FileOutputStream fos = new FileOutputStream(new File(newPath));
byte[] buffer = new byte[1024];
int byteCount;
while ((byteCount = is.read(buffer)) != -1) {
fos.write(buffer, 0, byteCount);
}
fos.flush();
is.close();
fos.close();
}
} catch (Exception e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
public File getTempImage() {
if (Environment.getExternalStorageState().equals(
Environment.MEDIA_MOUNTED)) {
File tempFile = new File(Environment.getExternalStorageDirectory(), "temp.jpg");
try {
tempFile.createNewFile();
} catch (IOException e) {
e.printStackTrace();
}
return tempFile;
}
return null;
}
public void onActivityResult(int requestCode, int resultCode, Intent data) {
super.onActivityResult(requestCode, resultCode, data);
switch (requestCode) {
case TAKE_PHOTO_REQUEST_CODE:
if (resultCode == RESULT_OK) {
DetectionTask detectionTask = new DetectionTask();
detectionTask.execute(getTempImage().getPath());
}
break;
default:
break;
}
}
/**
* draw rect on imageView
*
* @param bitmap
* @param predicted
* @param viewWidth
* @param viewHeight
*/
private void drawRect(Bitmap bitmap, float[] predicted, int viewWidth, int viewHeight) {
Canvas canvas = new Canvas(bitmap);
canvas.drawBitmap(bitmap, 0, 0, null);
if (type == googlenet) {
Paint paint = new Paint();
paint.setColor(Color.RED);
paint.setStyle(Paint.Style.STROKE);
paint.setStrokeWidth(3.0f);
float x1 = 0;
float x2 = 0;
float y1 = 0;
float y2 = 0;
// the googlenet result sequence is (left top right top bottom)
x1 = (predicted[0] * viewWidth / 224);
y1 = (predicted[1] * viewHeight / 224);
x2 = (predicted[2] * viewWidth / 224);
y2 = (predicted[3] * viewHeight / 224);
canvas.drawRect(x1, y1, x2, y2, paint);
}
imageView.setImageBitmap(bitmap);
}
float getMaxIndex(float[] predicted) {
float max = 0;
int index = 0;
for (int i = 0; i < predicted.length; i++) {
if (predicted[i] > max) {
max = predicted[i];
index = i;
}
}
return index;
}
public float[] getScaledMatrix(Bitmap bitmap, int desWidth,
int desHeight) {
float[] dataBuf = new float[3 * desWidth * desHeight];
int rIndex;
int gIndex;
int bIndex;
int[] pixels = new int[desWidth * desHeight];
Bitmap bm = Bitmap.createScaledBitmap(bitmap, desWidth, desHeight, false);
bm.getPixels(pixels, 0, desWidth, 0, 0, desWidth, desHeight);
int j = 0;
int k = 0;
for (int i = 0; i < pixels.length; i ++) {
int clr = pixels[i];
j = i / desHeight;
k = i % desWidth;
rIndex = j * desWidth + k;
gIndex = rIndex + desHeight * desWidth;
bIndex = gIndex + desHeight * desWidth;
dataBuf[rIndex] = (float)((clr & 0x00ff0000)>> 16) -148;
dataBuf[gIndex] = (float)((clr & 0x0000ff00)>> 8) - 148;
dataBuf[bIndex] = (float)((clr & 0x000000ff)) -148;
}
if (bm.isRecycled()) {
bm.recycle();
}
return dataBuf;
}
/**
* check whether sdcard is mounted
*
* @return
*/
public boolean isHasSdCard() {
if (Environment.getExternalStorageState().equals(
Environment.MEDIA_MOUNTED)) {
return true;
} else {
return false;
}
}
public void dumpData(float[] results, String filename) {
try {
File writename = new File(filename);
writename.createNewFile();
BufferedWriter out = new BufferedWriter(new FileWriter(writename));
for (float result : results) {
out.write(result + " ");
}
out.flush();
out.close();
} catch (IOException e) {
e.printStackTrace();
}
}
/**
* scale bitmap in case of OOM
*
* @param ctx
* @param filePath
* @return
*/
public Bitmap getScaleBitmap(Context ctx, String filePath) {
BitmapFactory.Options opt = new BitmapFactory.Options();
opt.inJustDecodeBounds = true;
BitmapFactory.decodeFile(filePath, opt);
int bmpWidth = opt.outWidth;
int bmpHeight = opt.outHeight;
int maxSize = 500;
opt.inSampleSize = 1;
while (true) {
if (bmpWidth / opt.inSampleSize < maxSize || bmpHeight / opt.inSampleSize < maxSize) {
break;
}
opt.inSampleSize *= 2;
}
opt.inJustDecodeBounds = false;
Bitmap bmp = BitmapFactory.decodeFile(filePath, opt);
return bmp;
}
@Override
public void onBackPressed() {
super.onBackPressed();
Log.d("mdl", "mdl clear");
// clear mdl
PML.clear();
}
class DetectionTask extends AsyncTask<String, Void, float[]> {
private long time;
public DetectionTask() {
super();
}
@Override
protected void onPreExecute() {
super.onPreExecute();
if (type == googlenet) {
inputSize = 224;
}
}
@Override
protected void onPostExecute(float[] result) {
super.onPostExecute(result);
try {
Bitmap src = Bitmap.createScaledBitmap(bmp, imageView.getWidth(),
imageView.getHeight(), false);
drawRect(src, result, imageView.getWidth(), imageView.getHeight());
tvSpeed.setText("detection cost：" + time + "ms");
} catch (Exception e) {
e.printStackTrace();
}
}
@Override
protected void onProgressUpdate(Void... values) {
super.onProgressUpdate(values);
}
@Override
protected void onCancelled() {
super.onCancelled();
}
@Override
protected float[] doInBackground(String... strings) {
bmp = getScaleBitmap(mContext, strings[0]);
float[] inputData = getScaledMatrix(bmp, inputSize, inputSize);
float[] result = null;
try {
long start = System.currentTimeMillis();
result = PML.predict(inputData);
long end = System.currentTimeMillis();
time = end - start;
} catch (Exception e) {
e.printStackTrace();
}
return result;
}
}
}
demo/android/PaddleMobile_Android/app/src/main/java/com/baidu/paddle/PML.java 已删除 100644 → 0
浏览文件 @ 711beed5
package com.baidu.paddle;
public class PML {
/**
* Load
* @param modelPath
* @return
*/
public static native boolean load(String modelPath);
/**
* object detection
*
* @param buf
* @return
*/
public static native float[] predict(float[] buf);
public static native void clear();
}
demo/android/PaddleMobile_Android/app/src/main/res/drawable/ic_launcher_background.xml 已删除 100644 → 0
浏览文件 @ 711beed5
<?xml version="1.0" encoding="utf-8"?>
<vector xmlns:android="http://schemas.android.com/apk/res/android"
android:width="108dp"
android:height="108dp"
android:viewportHeight="108"
android:viewportWidth="108">
<path
android:fillColor="#26A69A"
android:pathData="M0,0h108v108h-108z" />
<path
android:fillColor="#00000000"
android:pathData="M9,0L9,108"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M19,0L19,108"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M29,0L29,108"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M39,0L39,108"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M49,0L49,108"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M59,0L59,108"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M69,0L69,108"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M79,0L79,108"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M89,0L89,108"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M99,0L99,108"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M0,9L108,9"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M0,19L108,19"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M0,29L108,29"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M0,39L108,39"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M0,49L108,49"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M0,59L108,59"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M0,69L108,69"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M0,79L108,79"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M0,89L108,89"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M0,99L108,99"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M19,29L89,29"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M19,39L89,39"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M19,49L89,49"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M19,59L89,59"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M19,69L89,69"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M19,79L89,79"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M29,19L29,89"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M39,19L39,89"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M49,19L49,89"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M59,19L59,89"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M69,19L69,89"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
<path
android:fillColor="#00000000"
android:pathData="M79,19L79,89"
android:strokeColor="#33FFFFFF"
android:strokeWidth="0.8" />
</vector>
demo/android/PaddleMobile_Android/app/src/main/res/layout/main_activity.xml 已删除 100644 → 0
浏览文件 @ 711beed5
<?xml version="1.0" encoding="utf-8"?>
<RelativeLayout xmlns:android="http://schemas.android.com/apk/res/android"
android:orientation="vertical" android:layout_width="match_parent"
android:layout_height="match_parent">
<LinearLayout
android:id="@+id/ll_bottom"
android:layout_width="match_parent"
android:layout_height="wrap_content"
android:orientation="horizontal"
android:layout_alignParentBottom="true"
android:background="@android:color/background_light">
<TextView
android:id="@+id/tv_speed"
android:layout_width="match_parent"
android:layout_weight="1"
android:layout_height="wrap_content"
android:textColor="@android:color/background_dark"
android:text="@string/time_cost"/>
<Button
android:id="@+id/button"
android:layout_width="match_parent"
android:layout_height="50dp"
android:text="take photo"
android:layout_weight="1"
/>
</LinearLayout>
<LinearLayout
android:id="@+id/ll_test"
android:layout_above="@id/ll_bottom"
android:layout_width="match_parent"
android:layout_height="wrap_content"
android:orientation="horizontal">
<Button
android:id="@+id/bt_load"
android:layout_width="0dp"
android:layout_height="wrap_content"
android:layout_weight="1"
android:text="load"/>
<Button
android:layout_width="0dp"
android:layout_height="wrap_content"
android:id="@+id/bt_clear"
android:layout_weight="1"
android:text="clear"/>
</LinearLayout>
<ImageView
android:id="@+id/imageView"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:scaleType="centerInside"
android:layout_above="@id/ll_test"
android:background="@android:color/background_light"/>
</RelativeLayout>
\ No newline at end of file
demo/android/PaddleMobile_Android/app/src/main/res/values/colors.xml 已删除 100644 → 0
浏览文件 @ 711beed5
<?xml version="1.0" encoding="utf-8"?>
<resources>
<color name="colorPrimary">#3F51B5</color>
<color name="colorPrimaryDark">#303F9F</color>
<color name="colorAccent">#FF4081</color>
</resources>
demo/android/PaddleMobile_Android/app/src/main/res/values/strings.xml 已删除 100644 → 0
浏览文件 @ 711beed5
<resources>
<string name="app_name">PaddleMobile_Android</string>
<string name="sdcard_not_available">sdcard not available</string>
<string name="time_cost">detection cost:</string>
</resources>
demo/android/PaddleMobile_Android/app/src/main/res/values/styles.xml 已删除 100644 → 0
浏览文件 @ 711beed5
<resources>
<!-- Base application theme. -->
<style name="AppTheme" parent="Theme.AppCompat.Light.DarkActionBar">
<!-- Customize your theme here. -->
<item name="colorPrimary">@color/colorPrimary</item>
<item name="colorPrimaryDark">@color/colorPrimaryDark</item>
<item name="colorAccent">@color/colorAccent</item>
</style>
</resources>
demo/android/PaddleMobile_Android/build.gradle 已删除 100644 → 0
浏览文件 @ 711beed5
// Top-level build file where you can add configuration options common to all sub-projects/modules.
buildscript {
repositories {
google()
jcenter()
}
dependencies {
classpath 'com.android.tools.build:gradle:3.1.3'
// NOTE: Do not place your application dependencies here; they belong
// in the individual module build.gradle files
}
}
allprojects {
repositories {
google()
jcenter()
}
}
task clean(type: Delete) {
delete rootProject.buildDir
}
demo/android/PaddleMobile_Android/gradle.properties 已删除 100644 → 0
浏览文件 @ 711beed5
# Project-wide Gradle settings.
# IDE (e.g. Android Studio) users:
# Gradle settings configured through the IDE *will override*
# any settings specified in this file.
# For more details on how to configure your build environment visit
# http://www.gradle.org/docs/current/userguide/build_environment.html
# Specifies the JVM arguments used for the daemon process.
# The setting is particularly useful for tweaking memory settings.
org.gradle.jvmargs=-Xmx1536m
android.injected.testOnly=false
# When configured, Gradle will run in incubating parallel mode.
# This option should only be used with decoupled projects. More details, visit
# http://www.gradle.org/docs/current/userguide/multi_project_builds.html#sec:decoupled_projects
# org.gradle.parallel=true
demo/android/PaddleMobile_Android/gradle/wrapper/gradle-wrapper.properties 已删除 100644 → 0
浏览文件 @ 711beed5
#Mon Jul 02 13:58:58 CST 2018
distributionBase=GRADLE_USER_HOME
distributionPath=wrapper/dists
zipStoreBase=GRADLE_USER_HOME
zipStorePath=wrapper/dists
distributionUrl=https\://services.gradle.org/distributions/gradle-4.4-all.zip
demo/android/PaddleMobile_Android/gradlew 已删除 100755 → 0
浏览文件 @ 711beed5
#!/usr/bin/env bash
##############################################################################
##
## Gradle start up script for UN*X
##
##############################################################################
# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
DEFAULT_JVM_OPTS=""
APP_NAME="Gradle"
APP_BASE_NAME=`basename "$0"`
# Use the maximum available, or set MAX_FD != -1 to use that value.
MAX_FD="maximum"
warn ( ) {
echo "$*"
}
die ( ) {
echo
echo "$*"
echo
exit 1
}
# OS specific support (must be 'true' or 'false').
cygwin=false
msys=false
darwin=false
case "`uname`" in
CYGWIN* )
cygwin=true
;;
Darwin* )
darwin=true
;;
MINGW* )
msys=true
;;
esac
# Attempt to set APP_HOME
# Resolve links: $0 may be a link
PRG="$0"
# Need this for relative symlinks.
while [ -h "$PRG" ] ; do
ls=`ls -ld "$PRG"`
link=`expr "$ls" : '.*-> \(.*\)$'`
if expr "$link" : '/.*' > /dev/null; then
PRG="$link"
else
PRG=`dirname "$PRG"`"/$link"
fi
done
SAVED="`pwd`"
cd "`dirname \"$PRG\"`/" >/dev/null
APP_HOME="`pwd -P`"
cd "$SAVED" >/dev/null
CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar
# Determine the Java command to use to start the JVM.
if [ -n "$JAVA_HOME" ] ; then
if [ -x "$JAVA_HOME/jre/sh/java" ] ; then
# IBM's JDK on AIX uses strange locations for the executables
JAVACMD="$JAVA_HOME/jre/sh/java"
else
JAVACMD="$JAVA_HOME/bin/java"
fi
if [ ! -x "$JAVACMD" ] ; then
die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME
Please set the JAVA_HOME variable in your environment to match the
location of your Java installation."
fi
else
JAVACMD="java"
which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
Please set the JAVA_HOME variable in your environment to match the
location of your Java installation."
fi
# Increase the maximum file descriptors if we can.
if [ "$cygwin" = "false" -a "$darwin" = "false" ] ; then
MAX_FD_LIMIT=`ulimit -H -n`
if [ $? -eq 0 ] ; then
if [ "$MAX_FD" = "maximum" -o "$MAX_FD" = "max" ] ; then
MAX_FD="$MAX_FD_LIMIT"
fi
ulimit -n $MAX_FD
if [ $? -ne 0 ] ; then
warn "Could not set maximum file descriptor limit: $MAX_FD"
fi
else
warn "Could not query maximum file descriptor limit: $MAX_FD_LIMIT"
fi
fi
# For Darwin, add options to specify how the application appears in the dock
if $darwin; then
GRADLE_OPTS="$GRADLE_OPTS \"-Xdock:name=$APP_NAME\" \"-Xdock:icon=$APP_HOME/media/gradle.icns\""
fi
# For Cygwin, switch paths to Windows format before running java
if $cygwin ; then
APP_HOME=`cygpath --path --mixed "$APP_HOME"`
CLASSPATH=`cygpath --path --mixed "$CLASSPATH"`
JAVACMD=`cygpath --unix "$JAVACMD"`
# We build the pattern for arguments to be converted via cygpath
ROOTDIRSRAW=`find -L / -maxdepth 1 -mindepth 1 -type d 2>/dev/null`
SEP=""
for dir in $ROOTDIRSRAW ; do
ROOTDIRS="$ROOTDIRS$SEP$dir"
SEP="|"
done
OURCYGPATTERN="(^($ROOTDIRS))"
# Add a user-defined pattern to the cygpath arguments
if [ "$GRADLE_CYGPATTERN" != "" ] ; then
OURCYGPATTERN="$OURCYGPATTERN|($GRADLE_CYGPATTERN)"
fi
# Now convert the arguments - kludge to limit ourselves to /bin/sh
i=0
for arg in "$@" ; do
CHECK=`echo "$arg"|egrep -c "$OURCYGPATTERN" -`
CHECK2=`echo "$arg"|egrep -c "^-"` ### Determine if an option
if [ $CHECK -ne 0 ] && [ $CHECK2 -eq 0 ] ; then ### Added a condition
eval `echo args$i`=`cygpath --path --ignore --mixed "$arg"`
else
eval `echo args$i`="\"$arg\""
fi
i=$((i+1))
done
case $i in
(0) set -- ;;
(1) set -- "$args0" ;;
(2) set -- "$args0" "$args1" ;;
(3) set -- "$args0" "$args1" "$args2" ;;
(4) set -- "$args0" "$args1" "$args2" "$args3" ;;
(5) set -- "$args0" "$args1" "$args2" "$args3" "$args4" ;;
(6) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" ;;
(7) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" ;;
(8) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" ;;
(9) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" "$args8" ;;
esac
fi
# Split up the JVM_OPTS And GRADLE_OPTS values into an array, following the shell quoting and substitution rules
function splitJvmOpts() {
JVM_OPTS=("$@")
}
eval splitJvmOpts $DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS
JVM_OPTS[${#JVM_OPTS[*]}]="-Dorg.gradle.appname=$APP_BASE_NAME"
exec "$JAVACMD" "${JVM_OPTS[@]}" -classpath "$CLASSPATH" org.gradle.wrapper.GradleWrapperMain "$@"
demo/android/PaddleMobile_Android/gradlew.bat 已删除 100644 → 0
浏览文件 @ 711beed5
@if "%DEBUG%" == "" @echo off
@rem ##########################################################################
@rem
@rem Gradle startup script for Windows
@rem
@rem ##########################################################################
@rem Set local scope for the variables with windows NT shell
if "%OS%"=="Windows_NT" setlocal
@rem Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
set DEFAULT_JVM_OPTS=
set DIRNAME=%~dp0
if "%DIRNAME%" == "" set DIRNAME=.
set APP_BASE_NAME=%~n0
set APP_HOME=%DIRNAME%
@rem Find java.exe
if defined JAVA_HOME goto findJavaFromJavaHome
set JAVA_EXE=java.exe
%JAVA_EXE% -version >NUL 2>&1
if "%ERRORLEVEL%" == "0" goto init
echo.
echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
echo.
echo Please set the JAVA_HOME variable in your environment to match the
echo location of your Java installation.
goto fail
:findJavaFromJavaHome
set JAVA_HOME=%JAVA_HOME:"=%
set JAVA_EXE=%JAVA_HOME%/bin/java.exe
if exist "%JAVA_EXE%" goto init
echo.
echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME%
echo.
echo Please set the JAVA_HOME variable in your environment to match the
echo location of your Java installation.
goto fail
:init
@rem Get command-line arguments, handling Windowz variants
if not "%OS%" == "Windows_NT" goto win9xME_args
if "%@eval[2+2]" == "4" goto 4NT_args
:win9xME_args
@rem Slurp the command line arguments.
set CMD_LINE_ARGS=
set _SKIP=2
:win9xME_args_slurp
if "x%~1" == "x" goto execute
set CMD_LINE_ARGS=%*
goto execute
:4NT_args
@rem Get arguments from the 4NT Shell from JP Software
set CMD_LINE_ARGS=%$
:execute
@rem Setup the command line
set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
@rem Execute Gradle
"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %CMD_LINE_ARGS%
:end
@rem End local scope for the variables with windows NT shell
if "%ERRORLEVEL%"=="0" goto mainEnd
:fail
rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of
rem the _cmd.exe /c_ return code!
if not "" == "%GRADLE_EXIT_CONSOLE%" exit 1
exit /b 1
:mainEnd
if "%OS%"=="Windows_NT" endlocal
:omega
demo/getDemo.sh 0 → 100644
浏览文件 @ 2b9ea6ea
#!/usr/bin/env bash
wget http://mms-graph.bj.bcebos.com/paddle-mobile%2FPaddleMobile_Android.zip
wget http://mms-graph.bj.bcebos.com/paddle-mobile%2FPaddleMobileDemo_iOS.zip
unzip paddle-mobile%2FPaddleMobile_Android.zip
unzip paddle-mobile%2FPaddleMobileDemo_iOS.zip
rm -rf paddle-mobile%2FPaddleMobile_Android.zip
rm -rf paddle-mobile%2FPaddleMobileDemo_iOS.zip
rm -rf __MACOSX
\ No newline at end of file
demo/ios/PaddleMobileDemo/PaddleMobileDemo.xcodeproj/project.pbxproj 已删除 100644 → 0
浏览文件 @ 711beed5
// !$*UTF8*$!
{
archiveVersion = 1;
classes = {
};
objectVersion = 50;
objects = {
/* Begin PBXBuildFile section */
FC12E93320EB6B2800807EF4 /* AppDelegate.m in Sources */ = {isa = PBXBuildFile; fileRef = FC12E93220EB6B2800807EF4 /* AppDelegate.m */; };
FC12E93620EB6B2800807EF4 /* ViewController.m in Sources */ = {isa = PBXBuildFile; fileRef = FC12E93520EB6B2800807EF4 /* ViewController.m */; };
FC12E93920EB6B2800807EF4 /* Main.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = FC12E93720EB6B2800807EF4 /* Main.storyboard */; };
FC12E93B20EB6B2900807EF4 /* Assets.xcassets in Resources */ = {isa = PBXBuildFile; fileRef = FC12E93A20EB6B2900807EF4 /* Assets.xcassets */; };
FC12E93E20EB6B2900807EF4 /* LaunchScreen.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = FC12E93C20EB6B2900807EF4 /* LaunchScreen.storyboard */; };
FC12E94120EB6B2900807EF4 /* main.m in Sources */ = {isa = PBXBuildFile; fileRef = FC12E94020EB6B2900807EF4 /* main.m */; };
FC12E94A20EB6B6800807EF4 /* libpaddle-mobile.a in Frameworks */ = {isa = PBXBuildFile; fileRef = FC12E94820EB6B6800807EF4 /* libpaddle-mobile.a */; };
FC12E94D20EB6BBB00807EF4 /* libstdc++.tbd in Frameworks */ = {isa = PBXBuildFile; fileRef = FC12E94C20EB6BBB00807EF4 /* libstdc++.tbd */; };
FC12E95120EB6BED00807EF4 /* params in Resources */ = {isa = PBXBuildFile; fileRef = FC12E94F20EB6BED00807EF4 /* params */; };
FC12E95220EB6BED00807EF4 /* model in Resources */ = {isa = PBXBuildFile; fileRef = FC12E95020EB6BED00807EF4 /* model */; };
FC12E95420EB6C0D00807EF4 /* apple.jpg in Resources */ = {isa = PBXBuildFile; fileRef = FC12E95320EB6C0D00807EF4 /* apple.jpg */; };
/* End PBXBuildFile section */
/* Begin PBXFileReference section */
FC12E92E20EB6B2800807EF4 /* PaddleMobileDemo.app */ = {isa = PBXFileReference; explicitFileType = wrapper.application; includeInIndex = 0; path = PaddleMobileDemo.app; sourceTree = BUILT_PRODUCTS_DIR; };
FC12E93120EB6B2800807EF4 /* AppDelegate.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = AppDelegate.h; sourceTree = "<group>"; };
FC12E93220EB6B2800807EF4 /* AppDelegate.m */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.objc; path = AppDelegate.m; sourceTree = "<group>"; };
FC12E93420EB6B2800807EF4 /* ViewController.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = ViewController.h; sourceTree = "<group>"; };
FC12E93520EB6B2800807EF4 /* ViewController.m */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.objc; path = ViewController.m; sourceTree = "<group>"; };
FC12E93820EB6B2800807EF4 /* Base */ = {isa = PBXFileReference; lastKnownFileType = file.storyboard; name = Base; path = Base.lproj/Main.storyboard; sourceTree = "<group>"; };
FC12E93A20EB6B2900807EF4 /* Assets.xcassets */ = {isa = PBXFileReference; lastKnownFileType = folder.assetcatalog; path = Assets.xcassets; sourceTree = "<group>"; };
FC12E93D20EB6B2900807EF4 /* Base */ = {isa = PBXFileReference; lastKnownFileType = file.storyboard; name = Base; path = Base.lproj/LaunchScreen.storyboard; sourceTree = "<group>"; };
FC12E93F20EB6B2900807EF4 /* Info.plist */ = {isa = PBXFileReference; lastKnownFileType = text.plist.xml; path = Info.plist; sourceTree = "<group>"; };
FC12E94020EB6B2900807EF4 /* main.m */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.objc; path = main.m; sourceTree = "<group>"; };
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demo/ios/PaddleMobileDemo/PaddleMobileDemo.xcodeproj/project.xcworkspace/contents.xcworkspacedata 已删除 100644 → 0
浏览文件 @ 711beed5
<?xml version="1.0" encoding="UTF-8"?>
<Workspace
version = "1.0">
<FileRef
location = "self:PaddleMobileDemo.xcodeproj">
</FileRef>
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demo/ios/PaddleMobileDemo/PaddleMobileDemo.xcodeproj/project.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist 已删除 100644 → 0
浏览文件 @ 711beed5
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demo/ios/PaddleMobileDemo/PaddleMobileDemo.xcodeproj/xcuserdata/liuruilong.xcuserdatad/xcschemes/xcschememanagement.plist 已删除 100644 → 0
浏览文件 @ 711beed5
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
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</dict>
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demo/ios/PaddleMobileDemo/PaddleMobileDemo/AppDelegate.m 已删除 100644 → 0
浏览文件 @ 711beed5
/* Copyright (c) 2018 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. */
#import "AppDelegate.h"
@interface AppDelegate ()
@end
@implementation AppDelegate
- (BOOL)application:(UIApplication *)application didFinishLaunchingWithOptions:(NSDictionary *)launchOptions {
// Override point for customization after application launch.
return YES;
}
- (void)applicationWillResignActive:(UIApplication *)application {
// Sent when the application is about to move from active to inactive state. This can occur for certain types of temporary interruptions (such as an incoming phone call or SMS message) or when the user quits the application and it begins the transition to the background state.
// Use this method to pause ongoing tasks, disable timers, and invalidate graphics rendering callbacks. Games should use this method to pause the game.
}
- (void)applicationDidEnterBackground:(UIApplication *)application {
// Use this method to release shared resources, save user data, invalidate timers, and store enough application state information to restore your application to its current state in case it is terminated later.
// If your application supports background execution, this method is called instead of applicationWillTerminate: when the user quits.
}
- (void)applicationWillEnterForeground:(UIApplication *)application {
// Called as part of the transition from the background to the active state; here you can undo many of the changes made on entering the background.
}
- (void)applicationDidBecomeActive:(UIApplication *)application {
// Restart any tasks that were paused (or not yet started) while the application was inactive. If the application was previously in the background, optionally refresh the user interface.
}
- (void)applicationWillTerminate:(UIApplication *)application {
// Called when the application is about to terminate. Save data if appropriate. See also applicationDidEnterBackground:.
}
@end
demo/ios/PaddleMobileDemo/PaddleMobileDemo/Assets.xcassets/AppIcon.appiconset/Contents.json 已删除 100644 → 0
浏览文件 @ 711beed5
{
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},
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],
"info" : {
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"author" : "xcode"
}
}
\ No newline at end of file
demo/ios/PaddleMobileDemo/PaddleMobileDemo/Assets.xcassets/Contents.json 已删除 100644 → 0
浏览文件 @ 711beed5
{
"info" : {
"version" : 1,
"author" : "xcode"
}
}
\ No newline at end of file
demo/ios/PaddleMobileDemo/PaddleMobileDemo/Base.lproj/LaunchScreen.storyboard 已删除 100644 → 0
浏览文件 @ 711beed5
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="13122.16" systemVersion="17A277" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" launchScreen="YES" useTraitCollections="YES" useSafeAreas="YES" colorMatched="YES" initialViewController="01J-lp-oVM">
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</document>
demo/ios/PaddleMobileDemo/PaddleMobileDemo/Base.lproj/Main.storyboard 已删除 100644 → 0
浏览文件 @ 711beed5
<?xml version="1.0" encoding="UTF-8"?>
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="13122.16" systemVersion="17A277" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" useTraitCollections="YES" useSafeAreas="YES" colorMatched="YES" initialViewController="BYZ-38-t0r">
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</document>
demo/ios/PaddleMobileDemo/PaddleMobileDemo/Info.plist 已删除 100644 → 0
浏览文件 @ 711beed5
<?xml version="1.0" encoding="UTF-8"?>
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<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>APPL</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleVersion</key>
<string>1</string>
<key>LSRequiresIPhoneOS</key>
<true/>
<key>UILaunchStoryboardName</key>
<string>LaunchScreen</string>
<key>UIMainStoryboardFile</key>
<string>Main</string>
<key>UIRequiredDeviceCapabilities</key>
<array>
<string>armv7</string>
</array>
<key>UISupportedInterfaceOrientations</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
<string>UIInterfaceOrientationLandscapeLeft</string>
<string>UIInterfaceOrientationLandscapeRight</string>
</array>
<key>UISupportedInterfaceOrientations~ipad</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
<string>UIInterfaceOrientationPortraitUpsideDown</string>
<string>UIInterfaceOrientationLandscapeLeft</string>
<string>UIInterfaceOrientationLandscapeRight</string>
</array>
</dict>
</plist>
demo/ios/PaddleMobileDemo/PaddleMobileDemo/PaddleMobile/PaddleMobile.h 已删除 100644 → 0
浏览文件 @ 711beed5
/* Copyright (c) 2018 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. */
#import <CoreImage/CoreImage.h>
#import <Foundation/Foundation.h>
@interface PaddleMobile : NSObject
- (instancetype)init;
- (BOOL)load:(NSString *)modelPath andWeightsPath:(NSString *)weighsPath;
- (NSArray *)predict:(CGImageRef)image dim:(NSArray<NSNumber *> *)dim means:(NSArray<NSNumber *> *)means scale:(float)scale;
- (NSArray *)predict:(CGImageRef)image dim:(NSArray<NSNumber *> *)dim;
- (void)clear;
@end
demo/ios/PaddleMobileDemo/PaddleMobileDemo/ViewController.m 已删除 100644 → 0
浏览文件 @ 711beed5
/* Copyright (c) 2018 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. */
#import "PaddleMobile.h"
#import "ViewController.h"
@interface ViewController ()
@end
@implementation ViewController
- (void)viewDidLoad {
[super viewDidLoad];
PaddleMobile *pam = [[PaddleMobile alloc] init];
NSString *modelPath = [[NSBundle mainBundle] pathForResource:@"model" ofType:nil];
NSString *paramPath = [[NSBundle mainBundle] pathForResource:@"params" ofType:nil];
if (modelPath.length == 0 || paramPath.length == 0) {
NSLog(@" need model and param");
return;
}
if ([pam load:modelPath andWeightsPath:paramPath]) {
NSLog(@"load success");
UIImage *inputImage = [UIImage imageNamed:@"apple.jpg"];
if (!inputImage) {
NSLog(@" input image is nil");
return;
}
NSDate *beforeDate = [NSDate date];
NSArray *res = [pam predict:inputImage.CGImage dim:@[@1, @3, @224, @224] means:@[@148, @148, @148] scale:1.0];
NSLog(@"res: %@", res);
NSLog(@"elapsed time: %f", [[NSDate date] timeIntervalSinceDate:beforeDate]);
}
}
@end
demo/ios/PaddleMobileDemo/PaddleMobileDemo/main.m 已删除 100644 → 0
浏览文件 @ 711beed5
/* Copyright (c) 2018 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. */
#import <UIKit/UIKit.h>
#import "AppDelegate.h"
int main(int argc, char * argv[]) {
@autoreleasepool {
return UIApplicationMain(argc, argv, nil, NSStringFromClass([AppDelegate class]));
}
}
doc/build.md
浏览文件 @ 2b9ea6ea
......@@ -19,9 +19,14 @@ paddle-mobile dev 33b146787711 45 hours ago 372MB
```
$ docker run -it --mount type=bind,source=$PWD,target=/paddle-mobile paddle-mobile:dev
root@5affd29d4fc5:/ # cd /paddle-mobile
###
### paddle-mobile 支持 arm 架构下的各种平台，包括 android 以及 linux 等，可以使用不同的
### toolchain 文件生成满足需要的 makefile
###
# 生成构建 android 产出的 Makefile
root@5affd29d4fc5:/ # rm CMakeCache.txt
root@5affd29d4fc5:/ # cmake -DCMAKE_TOOLCHAIN_FILE=tools/toolchains/arm-android-neon.cmake
# 生成构建 linux 产出的 Makefile
root@5affd29d4fc5:/ # rm CMakeCache.txt
root@5affd29d4fc5:/ # cmake -DCMAKE_TOOLCHAIN_FILE=tools/toolchains/arm-linux-gnueabi.cmake
......
doc/development_doc.md
浏览文件 @ 2b9ea6ea
......@@ -4,9 +4,11 @@
## 编译
### 一. 使用 build.sh 编译
```sh
# 在 paddle-mobile 目录下:
cd tools
sh build.sh ios
# 如果只想编译某个特定模型的 op, 则需执行以下命令
......@@ -16,10 +18,14 @@ sh build.sh ios googlenet
cd ../build/release/ios/build
```
#### 常见问题:
1. No iOS SDK's found in default search path ...
### 二. 集成
这个问题是因为 tools/ios-cmake/ios.toolchain.cmake 找不到你最近使用的 iOS SDK 路径, 所以需要自己进行指定,
以我当前的环境为例: 在 tools/ios-cmake/ios.toolchain.cmake 143行前添加我本地的 iOS SDK 路径: set(CMAKE_IOS_SDK_ROOT "/Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS.sdk")
#### 如使用 oc 接口
## 集成
```
将上一步生成的:
......@@ -28,7 +34,11 @@ libpaddle-mobile.a
/src/ios_io/ 下的
PaddleMobile.h
```
拖入工程, 接口如下:
拖入工程
#### oc 接口
接口如下:
```
/*
......@@ -133,11 +143,16 @@ root@5affd29d4fc5:/ # make
##### 下载Android NDK
从源码交叉编译paddle-mobile,用户需要提前准备好交叉编译环境。Android平台使用的C/C++交叉编译工具链是[Android NDK](https://developer.android.com/ndk/)，用户可以自行前往下载，也可以通过以下命令获取：
- Mac平台
```
wget https://dl.google.com/android/repository/android-ndk-r17b-darwin-x86_64.zip
unzip android-ndk-r17b-darwin-x86_64.zip
```
- Linux平台
```
wget https://dl.google.com/android/repository/android-ndk-r17b-linux-x86_64.zip
unzip android-ndk-r17b-linux-x86_64.zip
```
##### 设置环境变量
......@@ -183,26 +198,50 @@ which to test :
Android应用可通过JNI接口调用底层C/C++，paddle-mobile对外提供的JNI接口如下：
##### 1 load接口 加载模型参数
- 用于加载参数文件分散的模型
```
/*
*@param modelPath 模型文件路径
*@return jboolean
*/
JNIEXPORT jboolean JNICALL Java_com_baidu_paddle_PML_load(JNIEnv *env,
jclass thiz,
jstring modelPath);
/**
* Load seperated parameters
* @param modelDir
* @return
*/
public static native boolean load(String modelDir);
```
- 用于加载参数文件合并的模型文件
```
/**
* Load combined parameters
* @param modelPath
* @param paramPath
* @return
*/
public static native boolean loadCombined(String modelPath,String paramPath);
```
##### 2 predict接口 执行预测
- 接受预处理过的RGB数组的predict接口
```
/**
*@param buf 输入数据
*@return 输出数据
JNIEXPORT jfloatArray JNICALL Java_com_baidu_paddle_PML_predict(
JNIEXPORT jfloatArray JNICALL Java_com_baidu_paddle_PML_predictImage(
JNIEnv *env, jclass thiz, jfloatArray buf);
```
- 接受原始yuv数据的predict接口
```
/**
*
* @param buf yuv420格式的字节数组
* @param imgWidth yuv数据的宽
* @param imgHeight yuv数据的高
* @param ddims 输入数据的形状
* @param meanValues 模型训练时各通道的均值
* @return
*/
public static native float[] predictYuv(byte[] buf, int imgWidth, int imgHeight, int[] ddims, float[]meanValues);
```
##### 3 clear接口 销毁实例、清理内存操作
```
......
src/common/types.cpp
浏览文件 @ 2b9ea6ea
......@@ -24,6 +24,8 @@ const std::string G_OP_TYPE_CONCAT = "concat";
const std::string G_OP_TYPE_ELEMENTWISE_ADD = "elementwise_add";
const std::string G_OP_TYPE_FUSION_CONV_ADD_RELU = "fusion_conv_add_relu";
const std::string G_OP_TYPE_FUSION_CONV_ADD_BN_RELU = "fusion_conv_add_bn_relu";
const std::string G_OP_TYPE_FUSION_DWCONV_BN_RELU = "fusion_dwconv_bn_relu";
const std::string G_OP_TYPE_FUSION_CONV_BN_RELU = "fusion_conv_bn_relu";
const std::string G_OP_TYPE_FC = "fusion_fc";
const std::string G_OP_TYPE_FUSION_CONV_ADD = "fusion_conv_add";
const std::string G_OP_TYPE_LRN = "lrn";
......@@ -47,6 +49,8 @@ std::unordered_map<
std::string, std::pair<std::vector<std::string>, std::vector<std::string>>>
op_input_output_key = {
{G_OP_TYPE_CONV, {{"Input"}, {"Output"}}},
{G_OP_TYPE_FUSION_DWCONV_BN_RELU, {{"Input"}, {"Out"}}},
{G_OP_TYPE_FUSION_CONV_BN_RELU, {{"Input"}, {"Out"}}},
{G_OP_TYPE_FUSION_CONV_ADD, {{"Input"}, {"Out"}}},
{G_OP_TYPE_RELU, {{"X"}, {"Out"}}},
{G_OP_TYPE_SOFTMAX, {{"X"}, {"Out"}}},
......
src/common/types.h
浏览文件 @ 2b9ea6ea
......@@ -16,6 +16,7 @@ limitations under the License. */
#include <string>
#include <unordered_map>
#include <utility>
#include <vector>
namespace paddle_mobile {
......@@ -81,6 +82,8 @@ extern const std::string G_OP_TYPE_FUSION_CONV_ADD_RELU;
extern const std::string G_OP_TYPE_FC;
extern const std::string G_OP_TYPE_FUSION_CONV_ADD;
extern const std::string G_OP_TYPE_FUSION_CONV_ADD_BN_RELU;
extern const std::string G_OP_TYPE_FUSION_DWCONV_BN_RELU;
extern const std::string G_OP_TYPE_FUSION_CONV_BN_RELU;
extern const std::string G_OP_TYPE_LRN;
extern const std::string G_OP_TYPE_MUL;
......
src/common/variant.h
浏览文件 @ 2b9ea6ea
......@@ -12,6 +12,8 @@ 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. */
#include <cstdlib>
#include "common/enforce.h"
#include "common/log.h"
......@@ -82,7 +84,7 @@ struct Variant {
if (type_id == typeid(T).hash_code()) {
return *const_cast<T *>(reinterpret_cast<const T *>(&data));
} else {
PADDLE_MOBILE_THROW_EXCEPTION(" bad cast in variant ");
PADDLE_MOBILE_THROW_EXCEPTION(" bad cast in variant");
exit(0);
}
}
......
src/framework/attribute.h
浏览文件 @ 2b9ea6ea
......@@ -14,6 +14,7 @@ limitations under the License. */
#pragma once
#include <cstdlib>
#include <string>
#include <typeinfo>
#include <unordered_map>
......
src/framework/data_layout.h
浏览文件 @ 2b9ea6ea
......@@ -15,6 +15,7 @@ limitations under the License. */
#pragma once
#include <cctype>
#include <cstdlib>
#include <string>
namespace paddle_mobile {
......
src/framework/ddim.h
浏览文件 @ 2b9ea6ea
......@@ -14,9 +14,11 @@ limitations under the License. */
#pragma once
#include <cstdlib>
#include <initializer_list>
#include <typeinfo>
#include <vector>
#include "common/enforce.h"
#include "common/variant.h"
#include "dim.h"
......
src/framework/dim.h
浏览文件 @ 2b9ea6ea
......@@ -14,6 +14,7 @@ limitations under the License. */
#pragma once
#include <cstdlib>
#include "common/enforce.h"
namespace paddle_mobile {
namespace framework {
......
src/framework/operator.cpp
浏览文件 @ 2b9ea6ea
......@@ -28,6 +28,16 @@ vector<string> OperatorBase<Dtype>::GetOutKeys() const {
return it->second.second;
}
template <typename Dtype>
vector<string> OperatorBase<Dtype>::GetInputKeys() const {
auto it = op_input_output_key.find(type_);
if (it == op_input_output_key.end()) {
DLOG << type_ << " has no outputs";
return {};
}
return it->second.first;
}
template <typename Dtype>
OperatorBase<Dtype>::OperatorBase(const std::string &type,
const VariableNameMap &inputs,
......@@ -49,6 +59,11 @@ template <typename Dtype>
void OperatorBase<Dtype>::Run() const {
RunImpl();
#ifdef PADDLE_MOBILE_DEBUG
vector<string> input_keys = GetInputKeys();
for (const auto key : input_keys) {
Tensor *input = GetVarValue<framework::LoDTensor>(key, inputs_, *scope_);
DLOG << type_ << " input- " << key << "=" << *input;
}
vector<string> output_keys = GetOutKeys();
for (const auto key : output_keys) {
Tensor *out_ = GetVarValue<framework::LoDTensor>(key, outputs_, *scope_);
......
src/framework/operator.h
浏览文件 @ 2b9ea6ea
......@@ -61,6 +61,7 @@ class OperatorBase {
virtual ~OperatorBase() {}
void Run() const;
std::vector<string> GetOutKeys() const;
std::vector<string> GetInputKeys() const;
virtual void RunImpl() const = 0;
virtual void Init() = 0;
......@@ -118,6 +119,10 @@ class OperatorWithKernel : public OperatorBase<Dtype> {
virtual void InferShape() const = 0;
void Init() {
// for (auto i : this->inputs_) {
// DLOG << i.first;
// DLOG << i.second;
// }
PADDLE_MOBILE_ENFORCE(kernel_.Init(&param_), " %s kernel init failed",
this->type_.c_str());
}
......@@ -146,7 +151,7 @@ class OpKernelBase {
}
#endif
virtual void Compute(const P &para) const = 0;
virtual bool Init(P *para) { return true; };
virtual bool Init(P *para) { return true; }
virtual ~OpKernelBase() = default;
private:
......
src/framework/program/program-optimize/fusion_op_register.h
浏览文件 @ 2b9ea6ea
......@@ -42,8 +42,17 @@ class FusionOpRegister {
matchers_[matcher->Type()] = shared_matcher;
}
const std::map<std::string, std::shared_ptr<FusionOpMatcher>> Matchers() {
return matchers_;
const std::vector<std::shared_ptr<FusionOpMatcher>> Matchers() {
std::vector<std::shared_ptr<FusionOpMatcher>> matchers;
for (const auto& match : matchers_) {
matchers.push_back(match.second);
}
std::sort(matchers.begin(), matchers.end(),
[](std::shared_ptr<FusionOpMatcher> first,
std::shared_ptr<FusionOpMatcher> second) {
return first->BeginNode().Depth() > second->BeginNode().Depth();
});
return matchers;
}
private:
......
src/framework/program/program-optimize/node.cpp
浏览文件 @ 2b9ea6ea
......@@ -44,23 +44,6 @@ bool Node::operator==(const Node &in) {
return true;
}
std::vector<std::shared_ptr<framework::OpDesc>> Node::OpDescs(int size) {
std::vector<std::shared_ptr<framework::OpDesc>> op_descs;
OpDescs(size - 1, &op_descs);
return op_descs;
}
void Node::OpDescs(int index,
std::vector<std::shared_ptr<framework::OpDesc>> *op_desc) {
if (index == 0) {
return;
}
op_desc->push_back(this->op_desc_);
for (auto &output : outputs_) {
output->OpDescs(index, op_desc);
}
}
std::shared_ptr<Node> Node::To(int size) {
std::shared_ptr<Node> node = std::make_shared<Node>();
this->To(size - 1, node);
......
src/framework/program/program-optimize/node.h
浏览文件 @ 2b9ea6ea
......@@ -47,13 +47,10 @@ class Node {
std::map<std::string, std::vector<std::pair<std::string, std::string>>>
change,
std::vector<std::shared_ptr<Node>> *removed_nodes);
std::vector<std::shared_ptr<framework::OpDesc>> OpDescs(int size);
std::shared_ptr<framework::OpDesc> OpDescOfNode() { return op_desc_; }
std::string Type() { return type_; }
private:
void OpDescs(int size,
std::vector<std::shared_ptr<framework::OpDesc>> *op_desc);
void To(int index, std::shared_ptr<Node>);
void Folder(
std::shared_ptr<framework::OpDesc> op_desc,
......
src/framework/program/program-optimize/program_optimize.cpp
浏览文件 @ 2b9ea6ea
......@@ -78,9 +78,8 @@ std::shared_ptr<ProgramDesc> ProgramOptimize::FusionOptimize(
}
for (auto &registed : FusionOpRegister::Instance()->Matchers()) {
std::string fusion_type = registed.first;
std::shared_ptr<FusionOpMatcher> matcher = registed.second;
// DLOG << " registed node \n " << matcher->BeginNode();
std::string fusion_type = registed->Type();
std::shared_ptr<FusionOpMatcher> matcher = registed;
auto match_vector = type_map[matcher->BeginType()];
......
src/framework/program/program.h
浏览文件 @ 2b9ea6ea
......@@ -30,6 +30,7 @@ class Program {
std::string model_path;
std::string para_path;
bool combined = false;
bool quantification = false;
private:
};
......
src/framework/tensor.h
浏览文件 @ 2b9ea6ea
......@@ -152,7 +152,7 @@ class Tensor {
if (holder_ != nullptr) {
holder_->set_type(type);
}
PADDLE_MOBILE_ENFORCE(numel() >= 0, "the Tensor'snumel must >=0.")
PADDLE_MOBILE_ENFORCE(numel() >= 0, "the Tensor's numel must >=0.")
int64_t size = numel() * SizeOfType(type);
if (holder_ == nullptr || holder_->size() < size + offset_) {
holder_.reset(new PlaceholderImpl(size, type));
......
src/io/executor.cpp
浏览文件 @ 2b9ea6ea
......@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "io/executor.h"
#include <operators/math/gemm.h>
#include <algorithm>
#include <vector>
#include "common/enforce.h"
......@@ -153,7 +154,7 @@ void Executor<Dtype, P>::LoadMemory(const framework::VarDesc var_desc,
tensor->Resize(framework::make_ddim(desc.Dims()));
void *memory = tensor;
void *memory = nullptr;
int type_size = 0;
switch (desc.DataType()) {
case framework::VARTYPE_TYPE_FP16:
......@@ -178,11 +179,25 @@ void Executor<Dtype, P>::LoadMemory(const framework::VarDesc var_desc,
default:
break;
}
if (program_.quantification) {
float min_value;
float max_value;
memcpy(&min_value, *data, sizeof(float));
memcpy(&max_value, *data + sizeof(float), sizeof(float));
*data += 2 * sizeof(float);
const float factor = (max_value - min_value) / 255.0;
uint8_t *uint8_data = (uint8_t *)(*data);
for (int k = 0; k < memory_size; ++k) {
static_cast<float *>(memory)[k] = uint8_data[k] * factor + min_value;
}
*data += (memory_size * sizeof(uint8_t));
} else {
for (int n = 0; n < memory_size * type_size; ++n) {
static_cast<char *>(memory)[n] = (*data)[n];
}
(*data) += (sizeof(char) * memory_size * type_size);
}
}
template <typename Dtype, Precision P>
......
src/io/loader.cpp
浏览文件 @ 2b9ea6ea
......@@ -44,26 +44,29 @@ static size_t ReadBuffer(const char *file_name, uint8_t **out) {
template <typename Dtype, Precision P>
const framework::Program<Dtype, P> Loader<Dtype, P>::Load(
const std::string &dirname, bool optimize, bool can_add_split) {
auto program =
this->LoadProgram(dirname + "/__model__", optimize, can_add_split);
const std::string &dirname, bool optimize, bool quantification,
bool can_add_split) {
auto program = this->LoadProgram(dirname + "/__model__", optimize,
quantification, can_add_split);
program.model_path = dirname;
return program;
}
template <typename Dtype, Precision P>
const framework::Program<Dtype, P> Loader<Dtype, P>::Load(
const std::string &model_path, const std::string &para_path,
bool optimize) {
const std::string &model_path, const std::string &para_path, bool optimize,
bool quantification) {
auto program = this->LoadProgram(model_path, optimize);
program.para_path = para_path;
program.combined = true;
program.quantification = quantification;
return program;
}
template <typename Dtype, Precision P>
const framework::Program<Dtype, P> Loader<Dtype, P>::LoadProgram(
const std::string &model_path, bool optimize, bool can_add_split) {
const std::string &model_path, bool optimize, bool quantification,
bool can_add_split) {
std::string model_filename = model_path;
PaddleMobile__Framework__Proto__ProgramDesc *c_program;
uint8_t *buf = NULL;
......@@ -82,6 +85,7 @@ const framework::Program<Dtype, P> Loader<Dtype, P>::LoadProgram(
framework::Program<Dtype, P> program;
program.originProgram = originProgramDesc;
program.quantification = quantification;
auto scope = std::make_shared<framework::Scope>();
program.scope = scope;
......
src/io/loader.h
浏览文件 @ 2b9ea6ea
......@@ -30,6 +30,7 @@ class Loader {
* */
const framework::Program<Dtype, P> Load(const std::string &dirname,
bool optimize = false,
bool quantification = false,
bool can_add_split = false);
/*
......@@ -38,11 +39,13 @@ class Loader {
* */
const framework::Program<Dtype, P> Load(const std::string &model_path,
const std::string &para_path,
bool optimize = false);
bool optimize = false,
bool quantification = false);
private:
const framework::Program<Dtype, P> LoadProgram(const std::string &model_path,
bool optimize = false,
bool quantification = false,
bool can_add_split = false);
};
......
src/io/paddle_mobile.cpp
浏览文件 @ 2b9ea6ea
......@@ -16,9 +16,17 @@ limitations under the License. */
namespace paddle_mobile {
template <typename Dtype, Precision P>
void PaddleMobile<Dtype, P>::SetThreadNum(int num) {
#ifdef _OPENMP
// omp_set_dynamic(0);
omp_set_num_threads(num);
#endif
};
template <typename Dtype, Precision P>
bool PaddleMobile<Dtype, P>::Load(const std::string &dirname, bool optimize,
int batch_size) {
bool quantification, int batch_size) {
if (loader_.get() == nullptr) {
loader_ = std::make_shared<Loader<Dtype, P>>();
} else {
......@@ -27,7 +35,7 @@ bool PaddleMobile<Dtype, P>::Load(const std::string &dirname, bool optimize,
if (executor_.get() == nullptr) {
executor_ = std::make_shared<Executor<Dtype, P>>(
loader_->Load(dirname, optimize), batch_size, optimize);
loader_->Load(dirname, optimize, quantification), batch_size, optimize);
} else {
LOG(kLOG_INFO) << "executor inited";
}
......@@ -38,7 +46,7 @@ bool PaddleMobile<Dtype, P>::Load(const std::string &dirname, bool optimize,
template <typename Dtype, Precision P>
bool PaddleMobile<Dtype, P>::Load(const std::string &model_path,
const std::string &para_path, bool optimize,
int batch_size) {
bool quantification, int batch_size) {
if (loader_.get() == nullptr) {
loader_ = std::make_shared<Loader<Dtype, P>>();
} else {
......@@ -47,7 +55,8 @@ bool PaddleMobile<Dtype, P>::Load(const std::string &model_path,
if (executor_.get() == nullptr) {
executor_ = std::make_shared<Executor<Dtype, P>>(
loader_->Load(model_path, para_path, optimize), batch_size, optimize);
loader_->Load(model_path, para_path, optimize, quantification),
batch_size, optimize);
} else {
LOG(kLOG_INFO) << "executor inited";
}
......@@ -81,7 +90,9 @@ PaddleMobile<Dtype, P>::~PaddleMobile() {
}
template class PaddleMobile<CPU, Precision::FP32>;
template class PaddleMobile<FPGA, Precision::FP32>;
template class PaddleMobile<GPU_MALI, Precision::FP32>;
} // namespace paddle_mobile
src/io/paddle_mobile.h
浏览文件 @ 2b9ea6ea
......@@ -17,6 +17,9 @@ limitations under the License. */
#include <memory>
#include <string>
#include <vector>
#ifdef _OPENMP
#include <omp.h>
#endif // _OPENMP
#include "common/types.h"
#include "framework/tensor.h"
......@@ -36,14 +39,19 @@ class PaddleMobile {
* @b 加载分开形式的 fluid 模型
* */
bool Load(const std::string &dirname, bool optimize = false,
int batch_size = 1);
bool quantification = false, int batch_size = 1);
/*
* @b load combine format fluid mode
* @b 加载结合在一起格式的模型
* */
bool Load(const std::string &model_path, const std::string &para_path,
bool optimize = false, int batch_size = 1);
bool optimize = false, bool quantification = false,
int batch_size = 1);
/*
* @b 设置线程数, 当 cmake 中开启 openmp 时生效
* */
void SetThreadNum(int num);
/*
* @b to predict
......
src/ios_io/PaddleMobile.h
浏览文件 @ 2b9ea6ea
......@@ -19,10 +19,34 @@
@interface PaddleMobile : NSObject
/*
创建对象
*/
- (instancetype)init;
/*
load 模型, 开辟内存
*/
- (BOOL)load:(NSString *)modelPath andWeightsPath:(NSString *)weighsPath;
/*
加载散开形式的模型, 需传入模型的目录
*/
- (BOOL)load:(NSString *)modelAndWeightPath;
/*
进行预测, means 和 scale 为训练模型时的预处理参数, 如训练时没有做这些预处理则直接使用 predict
*/
- (NSArray *)predict:(CGImageRef)image dim:(NSArray<NSNumber *> *)dim means:(NSArray<NSNumber *> *)means scale:(float)scale;
/*
进行预测
*/
- (NSArray *)predict:(CGImageRef)image dim:(NSArray<NSNumber *> *)dim;
/*
清理内存
*/
- (void)clear;
@end
src/ios_io/PaddleMobile.mm
浏览文件 @ 2b9ea6ea
......@@ -62,6 +62,15 @@ static std::mutex shared_mutex;
}
}
- (BOOL)load:(NSString *)modelAndWeightPath{
std::string model_path_str = std::string([modelAndWeightPath UTF8String]);
if (loaded_ = pam_->Load(model_path_str)) {
return YES;
} else {
return NO;
}
}
-(void)preprocess:(const UInt8 *)input output:(float *)output imageWidth:(int)imageWidth imageHeight:(int)imageHeight imageChannels:(int)imageChannels means:(NSArray<NSNumber *> *)means scale:(float)scale dim:(std::vector<int64_t>)dim{
if (means == nil) {
means = @[@0, @0, @0];
......
src/jni/paddle_mobile_jni.cpp
浏览文件 @ 2b9ea6ea
......@@ -15,6 +15,7 @@ limitations under the License. */
#ifdef ANDROID
#include "paddle_mobile_jni.h"
#include <cmath>
#include "common/log.h"
#include "framework/tensor.h"
#include "io/paddle_mobile.h"
......@@ -60,8 +61,26 @@ JNIEXPORT jboolean JNICALL Java_com_baidu_paddle_PML_load(JNIEnv *env,
optimize);
}
JNIEXPORT jfloatArray JNICALL
Java_com_baidu_paddle_PML_predict(JNIEnv *env, jclass thiz, jfloatArray buf) {
JNIEXPORT jboolean JNICALL Java_com_baidu_paddle_PML_loadCombined(
JNIEnv *env, jclass thiz, jstring modelPath, jstring paramPath) {
ANDROIDLOGI("loadCombined invoked");
bool optimize = true;
return getPaddleMobileInstance()->Load(jstring2cppstring(env, modelPath),
jstring2cppstring(env, paramPath),
optimize);
}
JNIEXPORT jfloatArray JNICALL Java_com_baidu_paddle_PML_predictImage(
JNIEnv *env, jclass thiz, jfloatArray buf, jintArray ddims) {
ANDROIDLOGI("predictImage invoked");
jsize ddim_size = env->GetArrayLength(ddims);
if (ddim_size != 4) {
ANDROIDLOGE("ddims size not equal to 4");
}
jint *ddim_ptr = env->GetIntArrayElements(ddims, NULL);
framework::DDim ddim = framework::make_ddim(
{ddim_ptr[0], ddim_ptr[1], ddim_ptr[2], ddim_ptr[3]});
int length = framework::product(ddim);
jfloatArray result = NULL;
int count = 0;
float *dataPointer = nullptr;
......@@ -69,17 +88,102 @@ Java_com_baidu_paddle_PML_predict(JNIEnv *env, jclass thiz, jfloatArray buf) {
dataPointer = env->GetFloatArrayElements(buf, NULL);
}
framework::Tensor input;
framework::DDim ddim = framework::make_ddim({1, 3, 224, 224});
input.Resize(ddim);
auto input_ptr = input.mutable_data<float>();
for (int i = 0; i < framework::product(ddim); i++) {
for (int i = 0; i < length; i++) {
input_ptr[i] = dataPointer[i];
}
auto output = shared_paddle_mobile_instance->Predict(input);
count = output->numel();
result = env->NewFloatArray(count);
env->SetFloatArrayRegion(result, 0, count, output->data<float>());
ANDROIDLOGI("predict finished");
env->ReleaseIntArrayElements(ddims, ddim_ptr, 0);
ANDROIDLOGI("predictImage finished");
return result;
}
inline int yuv_to_rgb(int y, int u, int v, float *r, float *g, float *b) {
int r1 = (int)(y + 1.370705 * (v - 128));
int g1 = (int)(y - 0.698001 * (u - 128) - 0.703125 * (v - 128));
int b1 = (int)(y + 1.732446 * (u - 128));
r1 = (int)fminf(255, fmaxf(0, r1));
g1 = (int)fminf(255, fmaxf(0, g1));
b1 = (int)fminf(255, fmaxf(0, b1));
*r = r1;
*g = g1;
*b = b1;
return 0;
}
void convert_nv21_to_matrix(uint8_t *nv21, float *matrix, int width, int height,
int targetWidth, int targetHeight, float *means) {
const uint8_t *yData = nv21;
const uint8_t *vuData = nv21 + width * height;
const int yRowStride = width;
const int vuRowStride = width;
float scale_x = width * 1.0 / targetWidth;
float scale_y = height * 1.0 / targetHeight;
for (int j = 0; j < targetHeight; ++j) {
int y = j * scale_y;
const uint8_t *pY = yData + y * yRowStride;
const uint8_t *pVU = vuData + (y >> 1) * vuRowStride;
for (int i = 0; i < targetWidth; ++i) {
int x = i * scale_x;
const int offset = ((x >> 1) << 1);
float r = 0;
float g = 0;
float b = 0;
yuv_to_rgb(pY[x], pVU[offset + 1], pVU[offset], &r, &g, &b);
int r_index = j * targetWidth + i;
int g_index = r_index + targetWidth * targetHeight;
int b_index = g_index + targetWidth * targetHeight;
matrix[r_index] = r - means[0];
matrix[g_index] = g - means[1];
matrix[b_index] = b - means[2];
}
}
}
JNIEXPORT jfloatArray JNICALL Java_com_baidu_paddle_PML_predictYuv(
JNIEnv *env, jclass thiz, jbyteArray yuv_, jint imgwidth, jint imgHeight,
jintArray ddims, jfloatArray meanValues) {
ANDROIDLOGI("predictYuv invoked");
jsize ddim_size = env->GetArrayLength(ddims);
if (ddim_size != 4) {
ANDROIDLOGE("ddims size not equal to 4");
}
jint *ddim_ptr = env->GetIntArrayElements(ddims, NULL);
framework::DDim ddim = framework::make_ddim(
{ddim_ptr[0], ddim_ptr[1], ddim_ptr[2], ddim_ptr[3]});
int length = framework::product(ddim);
float matrix[length];
jbyte *yuv = env->GetByteArrayElements(yuv_, NULL);
float *meansPointer = nullptr;
if (nullptr != meanValues) {
meansPointer = env->GetFloatArrayElements(meanValues, NULL);
}
convert_nv21_to_matrix((uint8_t *)yuv, matrix, imgwidth, imgHeight, ddim[3],
ddim[2], meansPointer);
jfloatArray result = NULL;
int count = 0;
framework::Tensor input;
input.Resize(ddim);
auto input_ptr = input.mutable_data<float>();
for (int i = 0; i < length; i++) {
input_ptr[i] = matrix[i];
}
auto output = shared_paddle_mobile_instance->Predict(input);
count = output->numel();
result = env->NewFloatArray(count);
env->SetFloatArrayRegion(result, 0, count, output->data<float>());
env->ReleaseByteArrayElements(yuv_, yuv, 0);
env->ReleaseIntArrayElements(ddims, ddim_ptr, 0);
env->ReleaseFloatArrayElements(meanValues, meansPointer, 0);
ANDROIDLOGI("predictYuv finished");
return result;
}
......
src/jni/paddle_mobile_jni.h
浏览文件 @ 2b9ea6ea
......@@ -22,11 +22,29 @@ extern "C" {
namespace paddle_mobile {
namespace jni {
/**
* load model & params of the net for android
* load separated model for android
*/
JNIEXPORT jboolean JNICALL Java_com_baidu_paddle_PML_load(JNIEnv *env,
jclass thiz,
jstring modelPath);
/**
* load combined model for android
*/
JNIEXPORT jboolean JNICALL Java_com_baidu_paddle_PML_loadCombined(
JNIEnv *env, jclass thiz, jstring modelPath, jstring paramPath);
/**
* object detection for anroid
*/
JNIEXPORT jfloatArray JNICALL Java_com_baidu_paddle_PML_predictImage(
JNIEnv *env, jclass thiz, jfloatArray buf, jintArray ddims);
/**
* object detection for anroid
*/
JNIEXPORT jfloatArray JNICALL Java_com_baidu_paddle_PML_predictYuv(
JNIEnv *env, jclass thiz, jbyteArray yuv, jint imgwidth, jint imgHeight,
jintArray ddims, jfloatArray meanValues);
/**
* object detection for anroid
......
src/operators/batchnorm_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -26,7 +26,7 @@ void BatchNormOp<Dtype, T>::InferShape() const {
auto x_dims = this->param_.InputX()->dims();
this->param_.OutputY()->Resize(x_dims);
}
template class BatchNormOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/box_coder_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -47,7 +47,7 @@ void BoxCoderOp<Dtype, T>::InferShape() const {
this->param_.OutputBox()->Resize(framework::make_ddim(
{input_targetbox_dims[0], input_priorbox_dims[0], 4}));
}
template class BoxCoderOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/concat_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -56,7 +56,6 @@ void ConcatOp<Dtype, T>::InferShape() const {
this->param_.Out()->Resize(out_dims);
}
template class ConcatOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/conv_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -48,8 +48,6 @@ void ConvOp<Dtype, T>::InferShape() const {
this->param_.Output()->Resize(ddim);
}
template class ConvOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/depthwise_conv_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -49,8 +49,6 @@ void DepthwiseConvOp<Dtype, T>::InferShape() const {
this->param_.Output()->Resize(ddim);
}
template class DepthwiseConvOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/dropout_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -22,7 +22,7 @@ void DropoutOp<Dtype, T>::InferShape() const {
auto input_dims = this->param_.InputX()->dims();
this->param_.Out()->Resize(input_dims);
}
template class DropoutOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/elementwise_add_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -24,7 +24,7 @@ void ElementwiseAddOp<Dtype, T>::InferShape() const {
auto x_dim = this->param_.InputX()->dims();
this->param_.Out()->Resize(x_dim);
}
template class ElementwiseAddOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/feed_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -14,10 +14,7 @@ limitations under the License. */
#include "feed_op.h"
namespace paddle_mobile {
namespace operators {
template class FeedOp<CPU, float>;
}
namespace operators {}
} // namespace paddle_mobile
namespace ops = paddle_mobile::operators;
......
src/operators/fetch_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -14,10 +14,7 @@ limitations under the License. */
#include "fetch_op.h"
namespace paddle_mobile {
namespace operators {
template class FetchOp<CPU, float>;
}
namespace operators {}
} // namespace paddle_mobile
namespace ops = paddle_mobile::operators;
......
src/operators/fusion_conv_add.cpp
浏览文件 @ 2b9ea6ea
......@@ -45,7 +45,6 @@ void FusionConvAddOp<Dtype, T>::InferShape() const {
this->param_.Output()->Resize(ddim);
}
template class FusionConvAddOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/fusion_conv_add.h
浏览文件 @ 2b9ea6ea
......@@ -36,8 +36,6 @@ class FusionConvAddMatcher : public framework::FusionOpMatcher {
void FolderNodes(
framework::Node *node,
std::vector<std::shared_ptr<framework::Node>> *removed_nodes) {
vector<std::shared_ptr<framework::OpDesc>> origin_descs =
node->OpDescs(node_.Depth());
node->Folder(node_.Depth(), Type(),
{{G_OP_TYPE_ELEMENTWISE_ADD, {{"Y", "Y"}}}}, removed_nodes);
}
......
src/operators/fusion_conv_add_bn_relu_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -44,7 +44,7 @@ void FusionConvAddBNReluOp<Dtype, T>::InferShape() const {
framework::DDim ddim = framework::make_ddim(output_shape);
this->param_.Output()->Resize(ddim);
}
template class FusionConvAddBNReluOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/fusion_conv_add_bn_relu_op.h
浏览文件 @ 2b9ea6ea
......@@ -39,8 +39,6 @@ class FusionConvAddBNReluMatcher : public framework::FusionOpMatcher {
void FolderNodes(
framework::Node *node,
std::vector<std::shared_ptr<framework::Node>> *removed_nodes) {
vector<std::shared_ptr<framework::OpDesc>> origin_descs =
node->OpDescs(node_.Depth());
node->Folder(node_.Depth(), Type(),
{{G_OP_TYPE_ELEMENTWISE_ADD, {{"Y", "Y"}}},
{G_OP_TYPE_BATCHNORM,
......@@ -79,11 +77,11 @@ class FusionConvAddBNReluOp
#ifdef PADDLE_MOBILE_CPU
//#ifndef FUSION_CONV_ADD_BN_RELU_REGISTER
// static framework::FusionOpRegistrar fusion_conv_add_bn_relu_registrar(
// new FusionConvAddBNReluMatcher());
//#define FUSION_CONV_ADD_BN_RELU_REGISTER
//#endif
#ifndef FUSION_CONV_ADD_BN_RELU_REGISTER
static framework::FusionOpRegistrar fusion_conv_add_bn_relu_registrar(
new FusionConvAddBNReluMatcher());
#define FUSION_CONV_ADD_BN_RELU_REGISTER
#endif
#endif
......
src/operators/fusion_conv_bn_relu_op.cpp 0 → 100644
浏览文件 @ 2b9ea6ea
/* Copyright (c) 2018 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. */
#ifdef FUSION_CONVBNRELU_OP
#include "operators/fusion_conv_bn_relu_op.h"
#include "operators/math/conv_func.h"
namespace paddle_mobile {
namespace operators {
template <typename Dtype, typename T>
void FusionConvBNReluOp<Dtype, T>::InferShape() const {
auto in_dims = this->param_.Input()->dims();
auto filter_dims = this->param_.Filter()->dims();
const std::vector<int> &strides = this->param_.Strides();
std::vector<int> paddings = this->param_.Paddings();
int groups = this->param_.Groups();
std::vector<int> dilations = this->param_.Dilations();
PADDLE_MOBILE_ENFORCE((in_dims.size() == filter_dims.size() &&
dilations.size() == paddings.size() &&
paddings.size() == strides.size()),
"ConvParam is not suitable");
std::vector<int64_t> output_shape({in_dims[0], filter_dims[0]});
for (size_t i = 0; i < strides.size(); ++i) {
output_shape.push_back(
math::ConvOutputSize(in_dims[i + 2], filter_dims[i + 2], dilations[i],
paddings[i], strides[i]));
}
framework::DDim ddim = framework::make_ddim(output_shape);
this->param_.Output()->Resize(ddim);
}
} // namespace operators
} // namespace paddle_mobile
namespace ops = paddle_mobile::operators;
#ifdef PADDLE_MOBILE_CPU
REGISTER_OPERATOR_CPU(fusion_conv_bn_relu, ops::FusionConvBNReluOp);
#endif
#ifdef PADDLE_MOBILE_MALI_GPU
#endif
#ifdef PADDLE_MOBILE_FPGA
#endif
#endif
src/operators/fusion_conv_bn_relu_op.h 0 → 100644
浏览文件 @ 2b9ea6ea
/* Copyright (c) 2018 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. */
#ifdef FUSION_CONVBNRELU_OP
#pragma once
#include <string>
#include <vector>
#include "framework/operator.h"
#include "framework/program/program-optimize/fusion_op_register.h"
#include "operators/kernel/conv_bn_relu_kernel.h"
#include "operators/op_param.h"
namespace paddle_mobile {
namespace operators {
using std::string;
using std::vector;
class FusionConvBNReluMatcher : public framework::FusionOpMatcher {
public:
FusionConvBNReluMatcher() {
node_ = framework::Node(G_OP_TYPE_CONV);
node_ > std::make_shared<framework::Node>(G_OP_TYPE_BATCHNORM) >
std::make_shared<framework::Node>(G_OP_TYPE_RELU);
}
void FolderNodes(
framework::Node *node,
std::vector<std::shared_ptr<framework::Node>> *removed_nodes) {
node->Folder(node_.Depth(), Type(),
{{G_OP_TYPE_BATCHNORM,
{{"Scale", "Scale"},
{"Mean", "Mean"},
{"Bias", "Bias"},
{"Variance", "Variance"}}}},
removed_nodes);
}
std::string Type() { return G_OP_TYPE_FUSION_CONV_BN_RELU; }
};
template <typename DeviceType, typename T>
class FusionConvBNReluOp : public framework::OperatorWithKernel<
DeviceType, FusionConvBNReluParam,
operators::ConvBNReluKernel<DeviceType, T>> {
public:
FusionConvBNReluOp(const string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs,
const framework::AttributeMap &attrs,
std::shared_ptr<framework::Scope> scope)
: framework::OperatorWithKernel<
DeviceType, FusionConvBNReluParam,
operators::ConvBNReluKernel<DeviceType, T>>(type, inputs, outputs,
attrs, scope) {}
using framework::OperatorWithKernel<
DeviceType, FusionConvBNReluParam,
operators::ConvBNReluKernel<DeviceType, T>>::OperatorWithKernel;
void InferShape() const override;
protected:
};
#ifdef PADDLE_MOBILE_CPU
#ifndef FUSION_CONV_BN_RELU_REGISTER
static framework::FusionOpRegistrar fusion_conv_bn_relu_registrar(
new FusionConvBNReluMatcher());
#define FUSION_CONV_BN_RELU_REGISTER
#endif
#endif
#ifdef PADDLE_MOBILE_MALI_GPU
#endif
#ifdef PADDLE_MOBILE_FPGA
#endif
} // namespace operators
} // namespace paddle_mobile
#ifdef PADDLE_MOBILE_CPU
USE_OP_CPU(fusion_conv_bn_relu);
#endif
#ifdef PADDLE_MOBILE_MALI_GPU
#endif
#ifdef PADDLE_MOBILE_FPGA
#endif
#endif
src/operators/fusion_dwconv_bn_relu_op.cpp 0 → 100644
浏览文件 @ 2b9ea6ea
/* Copyright (c) 2018 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. */
#ifdef FUSION_DWCONVBNRELU_OP
#include "operators/fusion_dwconv_bn_relu_op.h"
#include "operators/math/conv_func.h"
namespace paddle_mobile {
namespace operators {
template <typename Dtype, typename T>
void FusionDWConvBNReluOp<Dtype, T>::InferShape() const {
auto in_dims = this->param_.Input()->dims();
auto filter_dims = this->param_.Filter()->dims();
const std::vector<int> &strides = this->param_.Strides();
std::vector<int> paddings = this->param_.Paddings();
int groups = this->param_.Groups();
std::vector<int> dilations = this->param_.Dilations();
PADDLE_MOBILE_ENFORCE((in_dims.size() == filter_dims.size() &&
dilations.size() == paddings.size() &&
paddings.size() == strides.size()),
"ConvParam is not suitable");
std::vector<int64_t> output_shape({in_dims[0], filter_dims[0]});
for (size_t i = 0; i < strides.size(); ++i) {
output_shape.push_back(
math::ConvOutputSize(in_dims[i + 2], filter_dims[i + 2], dilations[i],
paddings[i], strides[i]));
}
framework::DDim ddim = framework::make_ddim(output_shape);
this->param_.Output()->Resize(ddim);
}
} // namespace operators
} // namespace paddle_mobile
namespace ops = paddle_mobile::operators;
#ifdef PADDLE_MOBILE_CPU
REGISTER_OPERATOR_CPU(fusion_dwconv_bn_relu, ops::FusionDWConvBNReluOp);
#endif
#ifdef PADDLE_MOBILE_MALI_GPU
#endif
#ifdef PADDLE_MOBILE_FPGA
#endif
#endif
src/operators/fusion_dwconv_bn_relu_op.h 0 → 100644
浏览文件 @ 2b9ea6ea
/* Copyright (c) 2018 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. */
#ifdef FUSION_DWCONVBNRELU_OP
#pragma once
#include <string>
#include <vector>
#include "framework/operator.h"
#include "framework/program/program-optimize/fusion_op_register.h"
#include "op_param.h"
#include "operators/kernel/dwconv_bn_relu_kernel.h"
namespace paddle_mobile {
namespace operators {
using std::string;
using std::vector;
class FusionDWConvBNReluMatcher : public framework::FusionOpMatcher {
public:
FusionDWConvBNReluMatcher() {
node_ = framework::Node(G_OP_TYPE_DEPTHWISE_CONV);
node_ > std::make_shared<framework::Node>(G_OP_TYPE_BATCHNORM) >
std::make_shared<framework::Node>(G_OP_TYPE_RELU);
}
void FolderNodes(
framework::Node *node,
std::vector<std::shared_ptr<framework::Node>> *removed_nodes) {
node->Folder(node_.Depth(), Type(),
{{G_OP_TYPE_BATCHNORM,
{{"Scale", "Scale"},
{"Mean", "Mean"},
{"Bias", "Bias"},
{"Variance", "Variance"}}}},
removed_nodes);
}
std::string Type() { return G_OP_TYPE_FUSION_DWCONV_BN_RELU; }
};
template <typename DeviceType, typename T>
class FusionDWConvBNReluOp : public framework::OperatorWithKernel<
DeviceType, FusionDWConvBNReluParam,
operators::DWConvBNReluKernel<DeviceType, T>> {
public:
FusionDWConvBNReluOp(const string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs,
const framework::AttributeMap &attrs,
std::shared_ptr<framework::Scope> scope)
: framework::OperatorWithKernel<
DeviceType, FusionDWConvBNReluParam,
operators::DWConvBNReluKernel<DeviceType, T>>(type, inputs, outputs,
attrs, scope) {}
using framework::OperatorWithKernel<
DeviceType, FusionDWConvBNReluParam,
operators::DWConvBNReluKernel<DeviceType, T>>::OperatorWithKernel;
void InferShape() const override;
protected:
};
#ifdef PADDLE_MOBILE_CPU
#ifndef FUSION_DWCONV_BN_RELU_REGISTER
static framework::FusionOpRegistrar fusion_dwconv_bn_relu_registrar(
new FusionDWConvBNReluMatcher());
#define FUSION_DWCONV_BN_RELU_REGISTER
#endif
#endif
#ifdef PADDLE_MOBILE_MALI_GPU
#ifndef FUSION_DWCONV_BN_RELU_REGISTER
static framework::FusionOpRegistrar fusion_dwconv_bn_relu_registrar(
new FusionDWConvBNReluMatcher());
#define FUSION_DWCONV_BN_RELU_REGISTER
#endif
#endif
#ifdef PADDLE_MOBILE_FPGA
#endif
} // namespace operators
} // namespace paddle_mobile
#ifdef PADDLE_MOBILE_CPU
USE_OP_CPU(fusion_dwconv_bn_relu);
#endif
#ifdef PADDLE_MOBILE_MALI_GPU
#endif
#ifdef PADDLE_MOBILE_FPGA
#endif
#endif
src/operators/fusion_fc_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -50,7 +50,6 @@ void FusionFcOp<Dtype, T>::InferShape() const {
this->param_.Out()->Resize(ddim);
}
template class FusionFcOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/im2sequence_op.cpp
浏览文件 @ 2b9ea6ea
......@@ -47,8 +47,6 @@ void Im2SequenceOp<Dtype, T>::InferShape() const {
this->param_.Output()->Resize(ddim);
}
template class Im2SequenceOp<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
......
src/operators/kernel/arm/conv_add_bn_relu_kernel.cpp
浏览文件 @ 2b9ea6ea
......@@ -15,7 +15,7 @@ limitations under the License. */
#ifdef FUSION_CONVADDBNRELU_OP
#include "operators/kernel/conv_add_bn_relu_kernel.h"
#include "operators/kernel/central-arm-func/conv_add_bn_relu_func.h"
#include "operators/kernel/central-arm-func/conv_add_bn_relu_arm_func.h"
namespace paddle_mobile {
namespace operators {
......
src/operators/kernel/arm/conv_bn_relu_kernel.cpp 0 → 100644
浏览文件 @ 2b9ea6ea
/* Copyright (c) 2018 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. */
#ifdef FUSION_CONVBNRELU_OP
#include "operators/kernel/conv_bn_relu_kernel.h"
#include "operators/kernel/central-arm-func/conv_bn_relu_arm_func.h"
namespace paddle_mobile {
namespace operators {
template <>
bool ConvBNReluKernel<CPU, float>::Init(FusionConvBNReluParam *param) {
const Tensor *mean = param->InputMean();
const Tensor *variance = param->InputVariance();
const Tensor *scale = param->InputScale();
const Tensor *bias = param->InputBias();
const float epsilon = param->Epsilon();
// DLOG << "variance: " << *variance;
auto mean_ptr = mean->data<float>();
auto variance_ptr = variance->data<float>();
auto scale_ptr = scale->data<float>();
auto bias_ptr = bias->data<float>();
const int C = mean->numel();
float inv_std_ptr[C];
for (int i = 0; i < C; i++) {
inv_std_ptr[i] =
1 / static_cast<float>(pow((variance_ptr[i] + epsilon), 0.5));
}
Tensor *new_scale = new Tensor();
Tensor *new_bias = new Tensor();
auto new_scale_ptr = new_scale->mutable_data<float>({C});
auto new_bias_ptr = new_bias->mutable_data<float>({C});
for (int i = 0; i < C; i++) {
new_scale_ptr[i] = inv_std_ptr[i] * scale_ptr[i];
new_bias_ptr[i] = bias_ptr[i] - mean_ptr[i] * inv_std_ptr[i] * scale_ptr[i];
}
param->SetNewScale(new_scale);
param->SetNewBias(new_bias);
return true;
}
template <>
void ConvBNReluKernel<CPU, float>::Compute(
const FusionConvBNReluParam &param) const {
ConvBNReluCompute<float>(param);
}
template class ConvBNReluKernel<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
#endif
src/operators/kernel/arm/dwconv_bn_relu_kernel.cpp 0 → 100644
浏览文件 @ 2b9ea6ea
/* Copyright (c) 2018 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. */
#ifdef FUSION_DWCONVBNRELU_OP
#include "operators/kernel/dwconv_bn_relu_kernel.h"
#include "operators/kernel/central-arm-func/dwconv_bn_relu_arm_func.h"
namespace paddle_mobile {
namespace operators {
template <>
bool DWConvBNReluKernel<CPU, float>::Init(FusionDWConvBNReluParam *param) {
const Tensor *mean = param->InputMean();
const Tensor *variance = param->InputVariance();
const Tensor *scale = param->InputScale();
const Tensor *bias = param->InputBias();
const float epsilon = param->Epsilon();
auto mean_ptr = mean->data<float>();
auto variance_ptr = variance->data<float>();
auto scale_ptr = scale->data<float>();
auto bias_ptr = bias->data<float>();
const int C = mean->numel();
float inv_std_ptr[C];
for (int i = 0; i < C; i++) {
inv_std_ptr[i] =
1 / static_cast<float>(pow((variance_ptr[i] + epsilon), 0.5));
}
Tensor *new_scale = new Tensor();
Tensor *new_bias = new Tensor();
auto new_scale_ptr = new_scale->mutable_data<float>({C});
auto new_bias_ptr = new_bias->mutable_data<float>({C});
for (int i = 0; i < C; i++) {
new_scale_ptr[i] = inv_std_ptr[i] * scale_ptr[i];
new_bias_ptr[i] = bias_ptr[i] - mean_ptr[i] * inv_std_ptr[i] * scale_ptr[i];
}
param->SetNewScale(new_scale);
param->SetNewBias(new_bias);
return true;
}
template <>
void DWConvBNReluKernel<CPU, float>::Compute(
const FusionDWConvBNReluParam &param) const {
DWConvBNReluCompute<float>(param);
}
template class DWConvBNReluKernel<CPU, float>;
} // namespace operators
} // namespace paddle_mobile
#endif
src/operators/kernel/arm/sigmoid_kernel.cpp
浏览文件 @ 2b9ea6ea
......@@ -16,7 +16,7 @@ limitations under the License. */
#include "../sigmoid_kernel.h"
#include "../central-arm-func/sigmoid_arm_func.h"
#if __ARM_NEON
#ifdef __ARM_NEON
#include "../../math/math_func_neon.h"
#endif
#include <cmath>
......
src/operators/kernel/central-arm-func/batchnorm_arm_func.h
浏览文件 @ 2b9ea6ea
......@@ -54,7 +54,40 @@ void BatchnormCompute(const BatchNormParam &param) {
int HXW = H * W;
#ifdef ARMV7
#if __ARM_NEON
#if __aarch64__
float *inv_std_ptr = new float[C];
for (int i = 0; i < C; i++) {
inv_std_ptr[i] =
1 / static_cast<float>(pow((variance_ptr[i] + epsilon), 0.5));
}
Tensor new_scale;
auto new_scale_ptr = new_scale.mutable_data<float>(framework::make_ddim({C}));
Tensor new_bias;
auto new_bias_ptr = new_bias.mutable_data<float>(framework::make_ddim({C}));
/// ((x - est_mean) * (inv_var) * scale + bias equal to
/// (x * inv_var * scale) + (bias - est_mean * inv_var * scale)
for (int i = 0; i < C; i++) {
new_scale_ptr[i] = inv_std_ptr[i] * scale_ptr[i];
new_bias_ptr[i] = bias_ptr[i] - mean_ptr[i] * inv_std_ptr[i] * scale_ptr[i];
{
for (int n = 0; n < N; n++) {
for (int h = 0; h < H; h++) {
int tmp_index = n * stride0 + i * stride1 + h * stride2;
for (int w = 0; w < W; w++) {
int index = tmp_index + w;
out_ptr[index] =
input_x_ptr[index] * new_scale_ptr[i] + new_bias_ptr[i];
}
}
}
}
}
delete[] inv_std_ptr;
#else
if (HXW > 32) {
int NXC = N * C;
float *inv_std_ptr = new float[NXC * 4];
......@@ -229,6 +262,7 @@ void BatchnormCompute(const BatchNormParam &param) {
delete[] inv_std_ptr;
}
#endif
#else
float *inv_std_ptr = new float[C];
for (int i = 0; i < C; i++) {
......
src/operators/kernel/central-arm-func/conv_add_arm_func.h
浏览文件 @ 2b9ea6ea
......@@ -124,9 +124,15 @@ void ConvAddCompute(const FusionConvAddParam &param) {
} else if (param.Groups() == param.Input()->dims()[1] &&
param.Input()->dims()[1] == param.Output()->dims()[1] &&
param.Filter()->dims()[2] == param.Filter()->dims()[3] &&
param.Filter()->dims()[2] == 3) {
math::DepthwiseConv3x3(param.Input(), param.Strides(), param.Paddings(),
param.Filter(), param.Bias(), param.Output(), true);
param.Filter()->dims()[2] == 3 && param.Strides()[0] == 2) {
// math::DepthwiseConv3x3(param.Input(), param.Strides(),
// param.Paddings(),
// param.Filter(), param.Bias(),
// param.Output(), false);
math::DepthwiseConv3x3s2p1v2(param.Input(), param.Filter(), param.Output(),
*param.Bias(), true);
} else {
ConvAddBasic(param);
}
......
src/operators/kernel/central-arm-func/conv_add_bn_relu_func.h → src/operators/kernel/central-arm-func/conv_add_bn_relu_arm_func.h
浏览文件 @ 2b9ea6ea
......@@ -15,6 +15,8 @@ limitations under the License. */
#ifdef FUSION_CONVADDBNRELU_OP
#pragma once
#include <vector>
#include "operators/math/depthwise_conv_3x3.h"
#include "operators/op_param.h"
......@@ -23,16 +25,9 @@ namespace operators {
void ConvAddBNReluBasic(const FusionConvAddBNReluParam &param) {
const Tensor *input = param.Input();
Tensor filter = *param.Filter();
Tensor bias = *param.Bias();
Tensor new_bias = *param.NewBias();
Tensor new_scale = *param.NewScale();
auto new_bias_ptr = new_bias.data<float>();
auto new_scale_ptr = new_scale.data<float>();
int axis = param.Axis();
Tensor *output = param.Output();
math::expand_bias(bias, axis, output->dims());
output->ShareDataWith(bias);
int groups = param.Groups();
std::vector<int> strides = param.Strides();
std::vector<int> paddings = param.Paddings();
......@@ -106,20 +101,10 @@ void ConvAddBNReluBasic(const FusionConvAddBNReluParam &param) {
// gemm
Tensor out_slice = out_batch.Slice(g * out_step, (g + 1) * out_step);
Tensor filter_slice = filter.Slice(g * out_step, (g + 1) * out_step);
math::matmul<float>(filter_slice, false, col_matrix, false,
static_cast<float>(1), &out_slice,
static_cast<float>(0));
}
}
/// todo : use neon in special case instead of 2for(300ms)
auto output_ptr = output->data<float>();
for (int c = 0; c < output_matrix_shape[0]; c++) {
int start = c * output_matrix_shape[1];
for (int j = 0; j < output_matrix_shape[1]; j++) {
output_ptr[start + j] =
output_ptr[start + j] * new_scale_ptr[c] + new_bias_ptr[c];
output_ptr[start + j] =
output_ptr[start + j] < 0 ? 0 : output_ptr[start + j];
math::matmulWithBn<float>(
filter_slice, false, col_matrix, false, static_cast<float>(1),
&out_slice, static_cast<float>(0), true, &new_scale, &new_bias, g);
}
}
}
......@@ -133,14 +118,17 @@ void ConvAddBNReluCompute(const FusionConvAddBNReluParam &param) {
param.Filter()->dims()[2] == 3 && param.Strides()[0] == 1) {
math::DepthwiseConvAddBNRelu3x3s1p1(param.Input(), param.Filter(),
param.Output(), param.NewScale(),
param.NewBias(), 1);
param.NewBias(), true);
} else if (param.Groups() == param.Input()->dims()[1] &&
param.Input()->dims()[1] == param.Output()->dims()[1] &&
param.Filter()->dims()[2] == param.Filter()->dims()[3] &&
param.Filter()->dims()[2] == 3 && param.Strides()[0] == 2) {
math::DepthwiseConvAddBNRelu3x3s2p1(param.Input(), param.Filter(),
// math::DepthwiseConvAddBNRelu3x3s2p1(param.Input(), param.Filter(),
// param.Output(), param.NewScale(),
// param.NewBias(), 1);
math::DepthwiseConvAddBNRelu3x3s2p1v2(param.Input(), param.Filter(),
param.Output(), param.NewScale(),
param.NewBias(), 1);
param.NewBias(), true);
} else {
ConvAddBNReluBasic(param);
}
......
src/operators/kernel/central-arm-func/conv_bn_relu_arm_func.h 0 → 100644
浏览文件 @ 2b9ea6ea
/* Copyright (c) 2018 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. */
#ifdef FUSION_CONVBNRELU_OP
#pragma once
#include <vector>
#include "operators/math/depthwise_conv_3x3.h"
#include "operators/op_param.h"
namespace paddle_mobile {
namespace operators {
void ConvBNReluBasic(const FusionConvBNReluParam &param) {
const Tensor *input = param.Input();
Tensor filter = *param.Filter();
Tensor new_bias = *param.NewBias();
Tensor new_scale = *param.NewScale();
Tensor *output = param.Output();
int groups = param.Groups();
std::vector<int> strides = param.Strides();
std::vector<int> paddings = param.Paddings();
std::vector<int> dilations = param.Dilations();
const int batch_size = static_cast<int>(input->dims()[0]);
std::vector<int64_t> filter_shape_vec(framework::vectorize(filter.dims()));
std::vector<int64_t> output_shape_vec(framework::vectorize(output->dims()));
size_t data_dim = filter_shape_vec.size() - 2;
std::vector<int64_t> col_shape_vec(1 + 2 * data_dim);
col_shape_vec[0] = input->dims()[1] / groups;
for (size_t j = 0; j < data_dim; ++j) {
col_shape_vec[j + 1] = filter_shape_vec[j + 2];
col_shape_vec[j + 1 + data_dim] = output_shape_vec[j + 2];
}
framework::DDim col_shape(framework::make_ddim(col_shape_vec));
framework::DDim col_matrix_shape =
framework::flatten_to_2d(col_shape, data_dim + 1);
bool is_expand =
math::IsExpand(filter_shape_vec, strides, paddings, dilations);
Tensor col;
Tensor col_matrix;
if (is_expand) {
col.mutable_data<float>(col_shape);
col_matrix.ShareDataWith(col);
col_matrix.Resize(col_matrix_shape);
}
framework::DDim input_shape = framework::slice_ddim(
input->dims(), 1, static_cast<int>(input->dims().size()));
framework::DDim filter_matrix_shape = {filter.dims()[0],
filter.numel() / filter.dims()[0]};
filter.Resize(filter_matrix_shape);
framework::DDim output_matrix_shape = {
output->dims()[1],
output->numel() / (output->dims()[0] * output->dims()[1])};
// convolution operator: im2col(or vol2col) + gemm
int in_step = static_cast<int>(input->dims()[1]) / groups;
int out_step = static_cast<int>(output->dims()[1]) / groups;
math::Vol2ColFunctor<CPU, float> vol2col;
math::Im2ColFunctor<math::ColFormat::kCFO, CPU, float> im2col;
for (int i = 0; i < batch_size; i++) {
Tensor in_batch = input->Slice(i, i + 1).Resize(input_shape);
Tensor out_batch = output->Slice(i, i + 1).Resize(output_matrix_shape);
for (int g = 0; g < groups; g++) {
Tensor in_slice = in_batch.Slice(g * in_step, (g + 1) * in_step);
if (!is_expand) {
col.ShareDataWith(in_slice);
col_matrix.ShareDataWith(col);
col_matrix.Resize(col_matrix_shape);
} else if (data_dim == 2U) {
// im2col
im2col(in_slice, dilations, strides,
std::vector<int>{paddings[0], paddings[1], paddings[0],
paddings[1]},
&col);
} else if (data_dim == 3U) {
// vol2col
vol2col(in_slice, dilations, strides, paddings, &col);
}
// gemm
Tensor out_slice = out_batch.Slice(g * out_step, (g + 1) * out_step);
Tensor filter_slice = filter.Slice(g * out_step, (g + 1) * out_step);
math::matmulWithBn<float>(
filter_slice, false, col_matrix, false, static_cast<float>(1),
&out_slice, static_cast<float>(0), true, &new_scale, &new_bias, g);
}
}
}
template <typename P>
void ConvBNReluCompute(const FusionConvBNReluParam &param) {
if (param.Groups() == param.Input()->dims()[1] &&
param.Input()->dims()[1] == param.Output()->dims()[1] &&
param.Filter()->dims()[2] == param.Filter()->dims()[3] &&
param.Filter()->dims()[2] == 3 && param.Strides()[0] == 1) {
math::DepthwiseConvAddBNRelu3x3s1p1(param.Input(), param.Filter(),
param.Output(), param.NewScale(),
param.NewBias(), true);
} else if (param.Groups() == param.Input()->dims()[1] &&
param.Input()->dims()[1] == param.Output()->dims()[1] &&
param.Filter()->dims()[2] == param.Filter()->dims()[3] &&
param.Filter()->dims()[2] == 3 && param.Strides()[0] == 2) {
// math::DepthwiseConvAddBNRelu3x3s2p1(param.Input(), param.Filter(),
// param.Output(), param.NewScale(),
// param.NewBias(), 1);
math::DepthwiseConvAddBNRelu3x3s2p1v2(param.Input(), param.Filter(),
param.Output(), param.NewScale(),
param.NewBias(), true);
} else {
ConvBNReluBasic(param);
}
}
} // namespace operators
} // namespace paddle_mobile
#endif
src/operators/kernel/central-arm-func/depthwise_conv_arm_func.h
浏览文件 @ 2b9ea6ea
......@@ -37,8 +37,12 @@ void DepthwiseConvCompute(const ConvParam &param) {
param.Input()->dims()[1] == param.Output()->dims()[1] &&
param.Filter()->dims()[2] == param.Filter()->dims()[3] &&
param.Filter()->dims()[2] == 3 && param.Strides()[0] == 2) {
math::DepthwiseConv3x3(param.Input(), param.Strides(), param.Paddings(),
param.Filter(), &Bias, param.Output(), false);
// math::DepthwiseConv3x3(param.Input(), param.Strides(),
// param.Paddings(),
// param.Filter(), &Bias, param.Output(), false);
math::DepthwiseConv3x3s2p1v2(param.Input(), param.Filter(), param.Output(),
Bias, false);
} else {
ConvBasic(param);
}
......
src/operators/kernel/central-arm-func/dwconv_bn_relu_arm_func.h 0 → 100644
浏览文件 @ 2b9ea6ea
/* Copyright (c) 2018 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. */
#ifdef FUSION_DWCONVBNRELU_OP
#pragma once
#include <vector>
#include "operators/math/depthwise_conv_3x3.h"
#include "operators/op_param.h"
namespace paddle_mobile {
namespace operators {
void DWConvBNReluBasic(const FusionDWConvBNReluParam &param) {
const Tensor *input = param.Input();
Tensor filter = *param.Filter();
Tensor new_bias = *param.NewBias();
Tensor new_scale = *param.NewScale();
Tensor *output = param.Output();
int groups = param.Groups();
std::vector<int> strides = param.Strides();
std::vector<int> paddings = param.Paddings();
std::vector<int> dilations = param.Dilations();
const int batch_size = static_cast<int>(input->dims()[0]);
std::vector<int64_t> filter_shape_vec(framework::vectorize(filter.dims()));
std::vector<int64_t> output_shape_vec(framework::vectorize(output->dims()));
size_t data_dim = filter_shape_vec.size() - 2;
std::vector<int64_t> col_shape_vec(1 + 2 * data_dim);
col_shape_vec[0] = input->dims()[1] / groups;
for (size_t j = 0; j < data_dim; ++j) {
col_shape_vec[j + 1] = filter_shape_vec[j + 2];
col_shape_vec[j + 1 + data_dim] = output_shape_vec[j + 2];
}
framework::DDim col_shape(framework::make_ddim(col_shape_vec));
framework::DDim col_matrix_shape =
framework::flatten_to_2d(col_shape, data_dim + 1);
bool is_expand =
math::IsExpand(filter_shape_vec, strides, paddings, dilations);
Tensor col;
Tensor col_matrix;
if (is_expand) {
col.mutable_data<float>(col_shape);
col_matrix.ShareDataWith(col);
col_matrix.Resize(col_matrix_shape);
}
framework::DDim input_shape = framework::slice_ddim(
input->dims(), 1, static_cast<int>(input->dims().size()));
framework::DDim filter_matrix_shape = {filter.dims()[0],
filter.numel() / filter.dims()[0]};
filter.Resize(filter_matrix_shape);
framework::DDim output_matrix_shape = {
output->dims()[1],
output->numel() / (output->dims()[0] * output->dims()[1])};
// convolution operator: im2col(or vol2col) + gemm
int in_step = static_cast<int>(input->dims()[1]) / groups;
int out_step = static_cast<int>(output->dims()[1]) / groups;
math::Vol2ColFunctor<CPU, float> vol2col;
math::Im2ColFunctor<math::ColFormat::kCFO, CPU, float> im2col;
for (int i = 0; i < batch_size; i++) {
Tensor in_batch = input->Slice(i, i + 1).Resize(input_shape);
Tensor out_batch = output->Slice(i, i + 1).Resize(output_matrix_shape);
for (int g = 0; g < groups; g++) {
Tensor in_slice = in_batch.Slice(g * in_step, (g + 1) * in_step);
if (!is_expand) {
col.ShareDataWith(in_slice);
col_matrix.ShareDataWith(col);
col_matrix.Resize(col_matrix_shape);
} else if (data_dim == 2U) {
// im2col
im2col(in_slice, dilations, strides,
std::vector<int>{paddings[0], paddings[1], paddings[0],
paddings[1]},
&col);
} else if (data_dim == 3U) {
// vol2col
vol2col(in_slice, dilations, strides, paddings, &col);
}
// gemm
Tensor out_slice = out_batch.Slice(g * out_step, (g + 1) * out_step);
Tensor filter_slice = filter.Slice(g * out_step, (g + 1) * out_step);
math::matmulWithBn<float>(
filter_slice, false, col_matrix, false, static_cast<float>(1),
&out_slice, static_cast<float>(0), true, &new_scale, &new_bias, g);
}
}
}
template <typename P>
void DWConvBNReluCompute(const FusionDWConvBNReluParam &param) {
if (param.Groups() == param.Input()->dims()[1] &&
param.Input()->dims()[1] == param.Output()->dims()[1] &&
param.Filter()->dims()[2] == param.Filter()->dims()[3] &&
param.Filter()->dims()[2] == 3 && param.Strides()[0] == 1) {
math::DepthwiseConvAddBNRelu3x3s1p1(param.Input(), param.Filter(),
param.Output(), param.NewScale(),
param.NewBias(), true);
} else if (param.Groups() == param.Input()->dims()[1] &&
param.Input()->dims()[1] == param.Output()->dims()[1] &&
param.Filter()->dims()[2] == param.Filter()->dims()[3] &&
param.Filter()->dims()[2] == 3 && param.Strides()[0] == 2) {
// math::DepthwiseConvAddBNRelu3x3s2p1(param.Input(), param.Filter(),
// param.Output(), param.NewScale(),
// param.NewBias(), 1);
math::DepthwiseConvAddBNRelu3x3s2p1v2(param.Input(), param.Filter(),
param.Output(), param.NewScale(),
param.NewBias(), true);
} else {
DWConvBNReluBasic(param);
}
}
} // namespace operators
} // namespace paddle_mobile
#endif
src/operators/kernel/central-arm-func/pool_arm_func.h
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......@@ -76,15 +76,20 @@ void PoolCompute(const PoolParam &param) {
}
} else if (ksize[0] == 2 && ksize[0] == ksize[1]) {
#ifndef IOS
#if __ARM_NEON
#if __aarch64__
PoolBasic(pooling_type, ksize, strides, paddings, in_x, out);
#else
if (pooling_type == "max") {
math::Pool2x2Max(strides, paddings, in_x, out);
} else if (pooling_type == "avg") {
math::Pool2x2Avg(strides, paddings, in_x, out);
}
#endif
#else
PoolBasic(pooling_type, ksize, strides, paddings, in_x, out);
#endif
#endif // __ARM_NEON
} else {
PoolBasic(pooling_type, ksize, strides, paddings, in_x, out);
}
......
src/operators/kernel/central-arm-func/sigmoid_arm_func.h
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......@@ -14,8 +14,10 @@ limitations under the License. */
#ifdef SIGMOID_OP
#pragma once
#include <cmath>
#include "operators/op_param.h"
#if __ARM_NEON
#ifdef __ARM_NEON
#include <arm_neon.h>
#include "operators/math/math_func_neon.h"
#endif
......@@ -24,7 +26,7 @@ namespace paddle_mobile {
namespace operators {
using framework::DDim;
void sigmoid(const Tensor *X, Tensor *Y) {
#if __ARM_NEON
#ifdef __ARM_NEON
const float *input = X->data<float>();
float *output = Y->mutable_data<float>();
const DDim &dDim = X->dims();
......@@ -66,6 +68,7 @@ void sigmoid(const Tensor *X, Tensor *Y) {
input_outer_ptr++;
}
}
#else
#endif
}
......
src/operators/kernel/conv_add_kernel.h
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......@@ -17,7 +17,7 @@ limitations under the License. */
#pragma once
#include <vector>
#if __ARM_NEON
#ifdef __ARM_NEON
#include <arm_neon.h>
#endif
#include "common/common.h"
......
demo/ios/PaddleMobileDemo/PaddleMobileDemo/AppDelegate.h → src/operators/kernel/conv_bn_relu_kernel.h
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......@@ -12,12 +12,34 @@ 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. */
#import <UIKit/UIKit.h>
#pragma once
@interface AppDelegate : UIResponder <UIApplicationDelegate>
#ifdef FUSION_CONVBNRELU_OP
@property (strong, nonatomic) UIWindow *window;
#include <vector>
#include "framework/ddim.h"
#include "framework/operator.h"
#include "operators/math/conv_func.h"
#include "operators/math/im2col.h"
#include "operators/math/math_function.h"
#include "operators/math/vol2col.h"
#include "operators/op_param.h"
namespace paddle_mobile {
namespace operators {
@end
using framework::DDim;
using framework::OpKernelBase;
template <typename DeviceType, typename T>
class ConvBNReluKernel
: public OpKernelBase<DeviceType, FusionConvBNReluParam> {
public:
void Compute(const FusionConvBNReluParam &param) const;
bool Init(FusionConvBNReluParam *param);
};
} // namespace operators
} // namespace paddle_mobile
#endif
demo/ios/PaddleMobileDemo/PaddleMobileDemo/ViewController.h → src/operators/kernel/dwconv_bn_relu_kernel.h
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......@@ -12,10 +12,34 @@ 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. */
#import <UIKit/UIKit.h>
#pragma once
@interface ViewController : UIViewController
#ifdef FUSION_DWCONVBNRELU_OP
#include <vector>
#include "framework/ddim.h"
#include "framework/operator.h"
#include "operators/math/conv_func.h"
#include "operators/math/im2col.h"
#include "operators/math/math_function.h"
#include "operators/math/vol2col.h"
#include "operators/op_param.h"
@end
namespace paddle_mobile {
namespace operators {
using framework::DDim;
using framework::OpKernelBase;
template <typename DeviceType, typename T>
class DWConvBNReluKernel
: public OpKernelBase<DeviceType, FusionDWConvBNReluParam> {
public:
void Compute(const FusionDWConvBNReluParam &param) const;
bool Init(FusionDWConvBNReluParam *param);
};
} // namespace operators
} // namespace paddle_mobile
#endif
src/operators/kernel/lrn_kernel.h
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