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Paddle-js
未验证 提交 6c40834f 编写于 作者: W wangqun 提交者： GitHub
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Merge pull request #6 from wangqunbaidu/master 

[d][change] 支持paddle op融合pass
上级 af4e9f7d cec3497d
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README.md
浏览文件 @ 6c40834f
...@@ -33,52 +33,52 @@ If the original model was a SavedModel, use paddle.load(). ...@@ -33,52 +33,52 @@ If the original model was a SavedModel, use paddle.load().
```bash ```bash
import Paddle from 'paddlejs'; import Paddle from 'paddlejs';
let feed = io.process({ let feed = io.process({
input: document.getElementById('image'), input: document.getElementById('image'),
params: { params: {
gapFillWith: '#000', // What to use to fill the square part after zooming gapFillWith: '#000', // What to use to fill the square part after zooming
targetSize: { targetSize: {
height: fw, height: fw,
width: fh width: fh
}, },
targetShape: [1, 3, fh, fw], // Target shape changed its name to be compatible with previous logic targetShape: [1, 3, fh, fw], // Target shape changed its name to be compatible with previous logic
// shape: [3, 608, 608], // Preset sensor shape // shape: [3, 608, 608], // Preset sensor shape
mean: [117.001, 114.697, 97.404], // Preset mean mean: [117.001, 114.697, 97.404], // Preset mean
// std: [0.229, 0.224, 0.225] // Preset std // std: [0.229, 0.224, 0.225] // Preset std
} }
}); });
const MODEL_CONFIG = { const MODEL_CONFIG = {
dir: `/${path}/`, // model URL dir: `/${path}/`, // model URL
main: 'model.json', // main graph main: 'model.json', // main graph
}; };
const paddle = new Paddle({ const paddle = new Paddle({
urlConf: MODEL_CONFIG, urlConf: MODEL_CONFIG,
options: {
multipart: true,
dataType: 'binary',
options: { options: {
multipart: true, fileCount: 1, // How many model have been cut
dataType: 'binary', getFileName(i) {
options: { return 'chunk_' + i + '.dat';
fileCount: 1, // How many model have been cut
getFileName(i) {
return 'chunk_' + i + '.dat';
}
} }
} }
}); }
});
model = await paddle.load(); model = await paddle.load();
// //
let inst = model.execute({ let inst = model.execute({
input: feed input: feed
}); });
// There should be a fetch execution call or a fetch output // There should be a fetch execution call or a fetch output
let result = await inst.read(); let result = await inst.read();
``` ```
......
examples/mobileNet/index.es6
浏览文件 @ 6c40834f
...@@ -4,6 +4,9 @@ import IO from '../../src/feed/imageFeed'; ...@@ -4,6 +4,9 @@ import IO from '../../src/feed/imageFeed';
import Utils from '../../src/utils/utils'; import Utils from '../../src/utils/utils';
// 获取map表 // 获取map表
import Map from '../../test/data/map'; import Map from '../../test/data/map';
const fileDownload = require('js-file-download');
/** /**
* @file model demo 入口文件 * @file model demo 入口文件
* @author wangqun@baidu.com * @author wangqun@baidu.com
...@@ -11,25 +14,21 @@ import Map from '../../test/data/map'; ...@@ -11,25 +14,21 @@ import Map from '../../test/data/map';
*/ */
// 模型feed数据 // 模型feed数据
const feedShape = { const feedShape = {
'608': { 'mobilenetv2': {
fw: 608, fw: 224,
fh: 608 fh: 224
},
'320': {
fw: 320,
fh: 320
},
'320fused': {
fw: 320,
fh: 320
},
'separate': {
fw: 244,
fh: 244
} }
}; };
const modelType = 'separate';
// 模型fetch数据
const fetchShape = {
'mobilenetv2': [1, 1000, 1, 1]
};
const modelType = 'mobilenetv2';
const {fw, fh} = feedShape[modelType]; const {fw, fh} = feedShape[modelType];
const outputShape = fetchShape[modelType];
// 统计参数 // 统计参数
let loaded = false; let loaded = false;
let model = {}; let model = {};
...@@ -37,19 +36,21 @@ window.statistic = []; ...@@ -37,19 +36,21 @@ window.statistic = [];
async function run(input) { async function run(input) {
// const input = document.getElementById('mobilenet'); // const input = document.getElementById('mobilenet');
const io = new IO(); const io = new IO();
let feed = io.process({ let feed = io.process({
input: input, input: input,
params: { params: {
targetShape: [1, 3, fh, fw], // 目标形状 为了兼容之前的逻辑所以改个名 gapFillWith: '#000', // 缩放后用什么填充不足方形部分
targetSize: {
height: fh,
width: fw
},
scale: 256, // 缩放尺寸 scale: 256, // 缩放尺寸
width: 224, height: 224, // 压缩宽高 targetShape: [1, 3, fh, fw], // 目标形状 为了兼容之前的逻辑所以改个名
shape: [3, 224, 224], // 预设tensor形状 mean: [0.485, 0.456, 0.406],
mean: [0.485, 0.456, 0.406], // 预设期望 std: [0.229, 0.224, 0.225]
std: [0.229, 0.224, 0.225] // 预设方差 }
}}); });
console.log('feed', feed);
const path = 'model/mobileNet'; const path = 'model/mobileNet';
if (!loaded) { if (!loaded) {
...@@ -62,31 +63,45 @@ async function run(input) { ...@@ -62,31 +63,45 @@ async function run(input) {
urlConf: MODEL_CONFIG, urlConf: MODEL_CONFIG,
options: { options: {
multipart: true, multipart: true,
dataType: 'json' dataType: 'binary',
options: {
fileCount: 4, // 切成了多少文件
getFileName(i) { // 获取第i个文件的名称
return 'chunk_' + i + '.dat';
}
},
feed
} }
}); });
model = await paddle.load(); model = await paddle.load();
} }
let inst = model.execute({ let inst = model.execute({
input: feed input: feed
}); });
// 其实这里应该有个fetch的执行调用或者fetch的输出
let result = await inst.read(); let result = await inst.read();
console.dir(['result', result]); let N = outputShape[0];
// let maxItem = Utils.getMaxItem(result); let C = outputShape[1];
// document.getElementById('txt').innerHTML = Map['' + maxItem.index]; let H = outputShape[2];
// console.log('识别出的结果是' + Map['' + maxItem.index]); let W = outputShape[3];
// console.dir(['每个op耗时', window.statistic]); console.log(outputShape);
// let total = statistic.reduce((all, cur) => { let nhwcShape = [N, H, W, C];
// return all + cur.runTime; console.log(nhwcShape);
// }, 0); console.log(result.length);
// console.log('op total = ' + total);
let nchwData = Utils.nhwc2nchw(result, nhwcShape);
Utils.stridePrint(nchwData);
Utils.continuousPrint(nchwData);
// for test
// fileDownload(nchwData, "paddlejs-0.txt");
let maxItem = Utils.getMaxItem(nchwData);
console.log(maxItem);
document.getElementById('txt').innerHTML = Map['' + maxItem.index];
console.log('识别出的结果是' + Map['' + maxItem.index]);
}; };
var image = ''; var image = '';
function selectImage(file) { function selectImage(file) {
......
examples/mobileNet/index.html
浏览文件 @ 6c40834f
...@@ -3,64 +3,12 @@ ...@@ -3,64 +3,12 @@
<head> <head>
<meta charset="utf-8"> <meta charset="utf-8">
<title>paddle web demo</title> <title>paddle web demo</title>
<meta name="viewport" content="width=device-width,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no,initial-scale=1,viewport-fit=cover"> <meta name="viewport" content="width=device-width,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no">
<style>
p {
display: block;
margin-block-start: 1em;
margin-block-end: 1em;
margin-inline-start: 0;
margin-inline-end: 0;
}
#uploadImg {
border: solid 1px #808080;
width: 100%;
padding: 10px;
background-color: #cabfbf;
color: #FFF;
font-size: 16px;
}
p.section-head {
font-variant: small-caps;
text-transform: uppercase;
letter-spacing: .17em;
line-height: 1.2em;
font-weight: 500;
margin-top: 2em;
margin-bottom: 1em;
border-left: 1px solid #EF6C00;
padding-left: 24px;
color: #818181;
}
.image-wrap {
position: relative;
}
#image {
width: 100%;
}
#myDiv {
position: absolute;
border: 1px solid #F00;
box-sizing: border-box;
}
</style>
</head> </head>
<body> <body>
<section class="title-area"> <img id="image" src="https://m.baidu.com/se/static/img/iphone/logo.png" style="max-width: 100%;">
<h1>Paddle.js: Using a pretrained mobileNet V2</h1> <input type="file" id="uploadImg">
</section> <div id="txt"></div>
<section>
<p class="section-head">Description</p>
<p>
Please upload a picture to experience online classification.
</p>
</section>
<section>
<img id="image" src="https://m.baidu.com/se/static/img/iphone/logo.png" style="max-width: 100%;">
<input type="file" id="uploadImg">
<div id="txt"></div>
</section>
<script src="index.es6"></script> <script src="index.es6"></script>
</body> </body>
</html> </html>
\ No newline at end of file
examples/tinyYolo/index.es6
浏览文件 @ 6c40834f
...@@ -74,12 +74,12 @@ async function run(input) { ...@@ -74,12 +74,12 @@ async function run(input) {
params: { params: {
gapFillWith: '#000', // 缩放后用什么填充不足方形部分 gapFillWith: '#000', // 缩放后用什么填充不足方形部分
targetSize: { targetSize: {
height: fw, height: fh,
width: fh width: fw
}, },
targetShape: [1, 3, fh, fw], // 目标形状 为了兼容之前的逻辑所以改个名 targetShape: [1, 3, fh, fw], // 目标形状 为了兼容之前的逻辑所以改个名
// shape: [3, 608, 608], // 预设tensor形状 // shape: [3, 608, 608], // 预设tensor形状
mean: [117.001, 114.697, 97.404], // 预设期望 mean: [117.001 / 255, 114.697 / 255, 97.404 / 255], // 预设期望
// std: [0.229, 0.224, 0.225] // 预设方差 // std: [0.229, 0.224, 0.225] // 预设方差
} }
}); });
......
examples/tinyYolo/index.html
浏览文件 @ 6c40834f
...@@ -5,45 +5,44 @@ ...@@ -5,45 +5,44 @@
<title>paddleJS demo</title> <title>paddleJS demo</title>
<meta name="viewport" content="width=device-width,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no,initial-scale=1,viewport-fit=cover"> <meta name="viewport" content="width=device-width,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no,initial-scale=1,viewport-fit=cover">
<style> <style>
p { p {
display: block; display: block;
margin-block-start: 1em; margin-block-start: 1em;
margin-block-end: 1em; margin-block-end: 1em;
margin-inline-start: 0px; margin-inline-start: 0;
margin-inline-end: 0px; margin-inline-end: 0;
} }
#uploadImg { #uploadImg {
border: solid 1px gray; border: solid 1px #808080;
width: 100%; width: 100%;
padding: 10px; padding: 10px;
background-color: #cabfbf; background-color: #cabfbf;
color: white; color: #FFF;
font-size: 16px; font-size: 16px;
} }
p.section-head { p.section-head {
font-variant: small-caps; font-variant: small-caps;
text-transform: uppercase; text-transform: uppercase;
letter-spacing: 0.17em; letter-spacing: .17em;
line-height: 1.2em; line-height: 1.2em;
font-weight: 500; font-weight: 500;
margin-top: 2em; margin-top: 2em;
margin-bottom: 1em; margin-bottom: 1em;
border-left: 1px solid #EF6C00; border-left: 1px solid #EF6C00;
padding-left: 24px; padding-left: 24px;
color: #818181;
color: #818181; }
} .image-wrap {
.image-wrap { position: relative;
position: relative; }
} #image {
#image { width: 100%;
width: 100%; }
} #myDiv {
#myDiv { position: absolute;
position: absolute; border: 1px solid #F00;
border: 1px solid red; box-sizing: border-box;
box-sizing: border-box; }
}
</style> </style>
</head> </head>
<body> <body>
...@@ -62,17 +61,17 @@ ...@@ -62,17 +61,17 @@
<section> <section>
<p class="section-head">Model Output</p> <p class="section-head">Model Output</p>
<div class="image-wrap"> <div class="image-wrap">
<img id="mobilenet" /> <img id="mobilenet">
</div> </div>
<p>原图片</p> <p>原图片</p>
<div class="image-wrap"> <div class="image-wrap">
<img id="image" src=""/> <img id="image" src="data:image/jpeg;base64,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">
<div id="myDiv"></div> <div id="myDiv"></div>
</div> </div>
<p>画布</p> <p>画布</p>
<canvas id="myCanvas"></canvas> <canvas id="myCanvas"></canvas>
<br/> <br>
<input type="file" id="uploadImg"/> <input type="file" id="uploadImg">
<div id="txt"></div> <div id="txt"></div>
</section> </section>
......
examples/tinyYolo/videoDemo.es6
浏览文件 @ 6c40834f
import 'babel-polyfill'; import 'babel-polyfill';
import Runner from '../src/executor/runner'; import Runner from '../../src/executor/runner';
import Camera from '../src/executor/camera'; import Camera from '../../src/executor/camera';
// 调试工具 // 调试工具
// import vConsole from 'vconsole'; // import vConsole from 'vconsole';
// const theConsole = new vConsole(); // const theConsole = new vConsole();
let startBtn = document.getElementById('start'); let startBtn = document.getElementById('start');
let stopBtn = document.getElementById('stop') let stopBtn = document.getElementById('stop')
// 模型输出shape
const outputShapes = {
'608': {
from: [19, 19, 25, 1],
to: [19, 19, 5, 5]
},
'320': {
from: [10, 10, 25, 1],
to: [10, 10, 5, 5]
},
'320fused': {
from: [10, 10, 25, 1],
to: [10, 10, 5, 5]
},
'tinyYolo': {
from: [10, 10, 25, 1],
to: [10, 10, 5, 5]
}
};
// 模型feed数据
const feedShape = {
'608': {
fw: 608,
fh: 608
},
'320': {
fw: 320,
fh: 320
},
'320fused': {
fw: 320,
fh: 320
},
'tinyYolo': {
fw: 320,
fh: 320
}
};
const modelPath = {
'tinyYolo': 'model/tinyYolo'
};
const modelType = 'tinyYolo';
const path = modelPath[modelType];
const runner = new Runner({ const runner = new Runner({
// 用哪个模型 // 用哪个模型
modelName: 'separate' // '608' | '320' | '320fused' | 'separate' modelName: modelType, // '608' | '320' | '320fused' | 'separate'
modelPath: path,
feedShape: feedShape[modelType],
outputShapes: outputShapes[modelType]
}); });
startBtn.disabled = true; startBtn.disabled = true;
runner.preheat() runner.preheat()
.then(() =>{ .then(() =>{
startBtn.disabled = false startBtn.disabled = false;
}); });
const domElement = document.getElementById('video'); const domElement = document.getElementById('video');
const myCanvas = document.getElementById('myDiv'); const myCanvas = document.getElementById('myDiv');
......
examples/tinyYolo/videoDemo.html
浏览文件 @ 6c40834f
...@@ -5,32 +5,59 @@ ...@@ -5,32 +5,59 @@
<meta name="viewport" content="width=device-width, initial-scale=1.0"> <meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta http-equiv="X-UA-Compatible" content="ie=edge"> <meta http-equiv="X-UA-Compatible" content="ie=edge">
<title>识别摄像头里的脸</title> <title>识别摄像头里的脸</title>
<style> <style>
body { body {
margin: 0; margin: 0;
padding: 0; padding: 0;
} }
#myDiv { #myDiv {
position: fixed; position: fixed;
border: 1px solid red; border: 1px solid #F00;
box-sizing: border-box; box-sizing: border-box;
} }
#video { #video {
background: red; background: #F00;
} }
</style> p {
display: block;
margin-block-start: 1em;
margin-block-end: 1em;
margin-inline-start: 0;
margin-inline-end: 0;
}
p.section-head {
font-variant: small-caps;
text-transform: uppercase;
letter-spacing: .17em;
line-height: 1.2em;
font-weight: 500;
margin-top: 2em;
margin-bottom: 1em;
border-left: 1px solid #EF6C00;
padding-left: 24px;
color: #818181;
}
</style>
</head> </head>
<body> <body>
<video id="video"> <section class="title-area">
</video> <h1>Paddle.js: Using a pretrained tinyYolo with WebRTC</h1>
<p> </section>
<button id="start">开始识别</button>
<button id="stop">结束</button>
</p>
<select id="videoSelect"></select>
<p id="tips">tips</p>
<div id="myDiv"></div>
<script src="./videoDemo.es6"></script> <section>
<p class="section-head">Description</p>
<p>Please start the face trace.</p>
</section>
<video id="video">
</video>
<p>
<button type="button" id="start">开始识别</button>
<button type="button" id="stop">结束</button>
</p>
<select id="videoSelect"></select>
<p id="tips">tips</p>
<div id="myDiv"></div>
<script src="./videoDemo.es6"></script>
</body> </body>
</html> </html>
\ No newline at end of file
package.json
浏览文件 @ 6c40834f
...@@ -4,14 +4,19 @@ ...@@ -4,14 +4,19 @@
"description": "paddle", "description": "paddle",
"main": "index.js", "main": "index.js",
"scripts": { "scripts": {
"server": "parcel ./src/index.html",
"mnistdemo": "parcel ./examples/mnist/index.html", "mnistdemo": "parcel ./examples/mnist/index.html",
"mobilenet": "parcel ./examples/mobileNet/index.html", "mobilenet": "parcel ./examples/mobileNet/index.html",
"tinyYolo": "parcel ./examples/tinyYolo/index.html", "tinyYolo": "parcel ./examples/tinyYolo/index.html",
"huangfan": "parcel ./examples/huangfan/index.html", "huangfan": "parcel ./examples/huangfan/index.html",
"terrorModel": "parcel ./examples/terrorModel/index.html",
"humanseg": "parcel ./examples/humanseg/index.html",
"humanStream": "parcel ./examples/humanStream/index.html --port 1234 --https",
"yolo": "parcel ./examples/yolo/index.html", "yolo": "parcel ./examples/yolo/index.html",
"videoDemo": "parcel ./examples/videoDemo.html --port 8123 --https", "videoDemo": "parcel ./examples/videoDemo.html --port 8123 --https",
"unitTest": "parcel ./test/unitTest.html", "unitTest": "parcel ./test/unitTest.html",
"test": "echo \"Error: no test specified\" && exit 1" "test": "echo \"Error: no test specified\" && exit 1",
"build": "webpack -w"
}, },
"devDependencies": { "devDependencies": {
"@babel/core": "^7.7.2", "@babel/core": "^7.7.2",
...@@ -27,6 +32,7 @@ ...@@ -27,6 +32,7 @@
"babel-preset-react": "^6.24.1", "babel-preset-react": "^6.24.1",
"babel-preset-stage-0": "^6.24.1", "babel-preset-stage-0": "^6.24.1",
"babel-runtime": "^6.26.0", "babel-runtime": "^6.26.0",
"less": "^3.11.1",
"parcel-bundler": "^1.10.3", "parcel-bundler": "^1.10.3",
"webpack-cli": "^3.3.6" "webpack-cli": "^3.3.6"
}, },
...@@ -34,7 +40,12 @@ ...@@ -34,7 +40,12 @@
"author": "", "author": "",
"license": "ISC", "license": "ISC",
"dependencies": { "dependencies": {
"js-file-download": "^0.4.5", "@babel/plugin-transform-runtime": "^7.6.2",
"vconsole": "^3.3.2" "@babel/runtime": "^7.7.2",
"extract-text-webpack-plugin": "^4.0.0-beta.0",
"js-file-download": "^0.4.10",
"vconsole": "^3.3.2",
"webpack": "^4.39.2",
"webpack-zepto": "0.0.1"
} }
} }
src/executor/camera.es6
浏览文件 @ 6c40834f
...@@ -26,6 +26,7 @@ export default class Camera { ...@@ -26,6 +26,7 @@ export default class Camera {
} }
// 访问用户媒体设备的兼容方法 // 访问用户媒体设备的兼容方法
// safari在getusermedia之后 才能拿到deviceid
run(deviceId, callback) { run(deviceId, callback) {
if (window.stream) { if (window.stream) {
window.stream.getTracks().forEach(function (track) { window.stream.getTracks().forEach(function (track) {
...@@ -41,7 +42,12 @@ export default class Camera { ...@@ -41,7 +42,12 @@ export default class Camera {
}; };
const error = this.error.bind(this); const error = this.error.bind(this);
if (this.deviceInfos.length) { if (this.deviceInfos.length) {
constraints.video.deviceId= {exact: deviceId || this.deviceInfos[0]}; constraints.video.deviceId = {exact: deviceId || this.deviceInfos[0].deviceId};
}
if (!constraints.video.deviceId) {
constraints = {
video: true
};
} }
if (navigator.mediaDevices && navigator.mediaDevices.getUserMedia) { if (navigator.mediaDevices && navigator.mediaDevices.getUserMedia) {
......
src/executor/executor.es6
浏览文件 @ 6c40834f
...@@ -38,6 +38,9 @@ export default class GraphExecutor { ...@@ -38,6 +38,9 @@ export default class GraphExecutor {
else if (this.type === 'elementwise_add') { else if (this.type === 'elementwise_add') {
return this.inputs.X.concat(this.inputs.Y); return this.inputs.X.concat(this.inputs.Y);
} }
else if (this.type === 'concat') {
return this.inputs.X.concat(this.inputs.Y);
}
else if (this.type === 'relu' || this.type === 'leaky_relu') { else if (this.type === 'relu' || this.type === 'leaky_relu') {
return this.inputs.X; return this.inputs.X;
} }
...@@ -60,7 +63,13 @@ export default class GraphExecutor { ...@@ -60,7 +63,13 @@ export default class GraphExecutor {
} }
get outputsName() { get outputsName() {
if (this.type === 'conv2d') { if (this.outputs.Output) {
return this.outputs.Output;
}
else if (this.outputs.out) {
return this.outputs.out;
}
else if (this.type === 'conv2d') {
return this.outputs.Output; return this.outputs.Output;
} }
else if (this.type === 'depthwise_conv2d') { else if (this.type === 'depthwise_conv2d') {
......
src/factory/fshader/ops.es6
浏览文件 @ 6c40834f
...@@ -39,12 +39,15 @@ import softmax_conf from '../../shader/softmax/conf'; ...@@ -39,12 +39,15 @@ import softmax_conf from '../../shader/softmax/conf';
import batchnorm_params from '../../shader/batchnorm/params'; import batchnorm_params from '../../shader/batchnorm/params';
import batchnorm_func from '../../shader/batchnorm/main'; import batchnorm_func from '../../shader/batchnorm/main';
import batchnorm_conf from '../../shader/batchnorm/conf'; import batchnorm_conf from '../../shader/batchnorm/conf';
import reshape_params from '../../shader/reshape/params'; import reshape2_params from '../../shader/reshape2/params';
import reshape_func from '../../shader/reshape/main'; import reshape2_func from '../../shader/reshape2/main';
import reshape_conf from '../../shader/reshape/conf'; import reshape2_conf from '../../shader/reshape2/conf';
import transpose_params from '../../shader/transpose/params'; import bilinear_interp_params from '../../shader/bilinear_interp/params';
import transpose_func from '../../shader/transpose/main'; import bilinear_interp_func from '../../shader/bilinear_interp/main';
import transpose_conf from '../../shader/transpose/conf'; import bilinear_interp_conf from '../../shader/bilinear_interp/conf';
import transpose2_params from '../../shader/transpose2/params';
import transpose2_func from '../../shader/transpose2/main';
import transpose2_conf from '../../shader/transpose2/conf';
import conv2d_elementwise_add_params from '../../shader/conv2d_elementwise_add/params'; import conv2d_elementwise_add_params from '../../shader/conv2d_elementwise_add/params';
import conv2d_elementwise_add_func from '../../shader/conv2d_elementwise_add/main'; import conv2d_elementwise_add_func from '../../shader/conv2d_elementwise_add/main';
...@@ -183,15 +186,20 @@ export default { ...@@ -183,15 +186,20 @@ export default {
func: batchnorm_func, func: batchnorm_func,
confs: batchnorm_conf confs: batchnorm_conf
}, },
reshape: { reshape2: {
params: reshape_params, params: reshape2_params,
func: reshape_func, func: reshape2_func,
confs: reshape_conf confs: reshape2_conf
}, },
transpose: { bilinear_interp: {
params: transpose_params, params: bilinear_interp_params,
func: transpose_func, func: bilinear_interp_func,
confs: transpose_conf confs: bilinear_interp_conf
},
transpose2: {
params: transpose2_params,
func: transpose2_func,
confs: transpose2_conf
} }
}, },
atoms: { atoms: {
......
src/feed/ImageFeed.es6
浏览文件 @ 6c40834f
...@@ -108,6 +108,7 @@ export default class imageFeed { ...@@ -108,6 +108,7 @@ export default class imageFeed {
result[offset] = data[a] / 255; result[offset] = data[a] / 255;
result[offset] -= mean[k]; result[offset] -= mean[k];
result[offset] /= std[k]; result[offset] /= std[k];
//result[offset] = 0.5;
offset++; offset++;
} }
} }
...@@ -116,6 +117,46 @@ export default class imageFeed { ...@@ -116,6 +117,46 @@ export default class imageFeed {
return result; return result;
}; };
/**
* 全部转bgr * H * W
* @param shape
*/
allReshapeToBGR(imageData, opt, scaleSize) {
//const {sw, sh} = scaleSize;
const [b, c, h, w] = opt.targetShape;
let data = imageData.data || imageData;
// mean和std是介于0-1之间的
let mean = opt.mean;
let std = opt.std;
let dataLength = data.length;
// let result = new Float32Array(dataLength * 3);
let result = this.result;
// let offsetR = 0;
// let offsetG = dataLength / 4;
// let offsetB = dataLength / 2;
let offset = 0;
let size = h * w;
// h w c
for (let i = 0; i < h; ++i) {
let iw = i * w;
for (let j = 0; j < w; ++j) {
let iwj = iw + j;
for (let k = 0; k < c; ++k) {
let a = iwj * 4 + (2-k);
result[offset] = data[a];
result[offset] -= mean[2-k];
result[offset] /= std[2-k];
//result[offset] = 0.5;
offset++;
}
}
}
console.log('this is the end of reshapetorgb !!!');
console.dir(result);
return result;
};
/** /**
* 根据scale缩放图像 * 根据scale缩放图像
* @param image * @param image
...@@ -138,6 +179,8 @@ export default class imageFeed { ...@@ -138,6 +179,8 @@ export default class imageFeed {
sh = params.scale; sh = params.scale;
sw = Math.round(sh * width / height); sw = Math.round(sh * width / height);
} }
sw = params.scale;
sh = params.scale;
this.fromPixels2DContext.canvas.width = sw; this.fromPixels2DContext.canvas.width = sw;
this.fromPixels2DContext.canvas.height = sh; this.fromPixels2DContext.canvas.height = sh;
this.fromPixels2DContext.drawImage( this.fromPixels2DContext.drawImage(
...@@ -285,15 +328,16 @@ export default class imageFeed { ...@@ -285,15 +328,16 @@ export default class imageFeed {
data2 = this.fromPixels2DContext2.getImageData(0, 0, this.pixelWidth, this.pixelHeight); data2 = this.fromPixels2DContext2.getImageData(0, 0, this.pixelWidth, this.pixelHeight);
} }
else if (opt.scale) { // 兼容以前的，如果有scale就是短边缩放到scale模式 else if (opt.scale) { // 兼容以前的，如果有scale就是短边缩放到scale模式
scaleSize = this.reSize(pixels, opt); scaleSize = this.reSize(pixels, opt);
console.dir(scaleSize); console.dir(scaleSize);
console.dir(pixels); console.dir(pixels);
data = this.getImageData(opt, 0, 0, scaleSize); data = this.getImageData(opt, 0, 0, scaleSize);
data2 = this.fromPixels2DContext2.getImageData(0, 0, this.pixelWidth, this.pixelHeight); data2 = this.fromPixels2DContext2.getImageData(0, 0, this.pixelWidth, this.pixelHeight);
} }
else if (opt.targetSize) { // 如果有targetSize，就是装在目标宽高里的模式 TinyYolo的情况 else if (opt.targetSize) { // 如果有targetSize，就是装在目标宽高里的模式 TinyYolo的情况
scaleSize = this.fitToTargetSize(pixels, opt); scaleSize = this.fitToTargetSize(pixels, opt);
data = this.getImageData(opt, 0, 0, scaleSize); data = this.getImageData(opt, 0, 0, scaleSize);
data2 = this.fromPixels2DContext2.getImageData(0, 0, this.pixelWidth, this.pixelHeight); data2 = this.fromPixels2DContext2.getImageData(0, 0, this.pixelWidth, this.pixelHeight);
...@@ -309,7 +353,10 @@ export default class imageFeed { ...@@ -309,7 +353,10 @@ export default class imageFeed {
data = this.reshape(data, opt, scaleSize); data = this.reshape(data, opt, scaleSize);
} }
if (opt.targetShape) { if (opt.bgr) {
data = this.allReshapeToBGR(data, opt, scaleSize);
}
else if (opt.targetShape) {
data = this.allReshapeToRGB(data, opt, scaleSize); data = this.allReshapeToRGB(data, opt, scaleSize);
} }
return [{data: data, shape: opt.shape || opt.targetShape, name: 'image', canvas: data2}]; return [{data: data, shape: opt.shape || opt.targetShape, name: 'image', canvas: data2}];
......
src/graph/graph.es6
浏览文件 @ 6c40834f
...@@ -14,6 +14,7 @@ import Utils from '../utils/utils'; ...@@ -14,6 +14,7 @@ import Utils from '../utils/utils';
const factory = new Factory({}); const factory = new Factory({});
// 获取op的输入配置 // 获取op的输入配置
const opConfs = factory.getOpConfs(); const opConfs = factory.getOpConfs();
let opindex = 0;
export default class Graph { export default class Graph {
constructor(options) { constructor(options) {
...@@ -27,12 +28,19 @@ export default class Graph { ...@@ -27,12 +28,19 @@ export default class Graph {
this.feedOp = null; this.feedOp = null;
this.feedItem = null; this.feedItem = null;
this.test = false; this.test = false;
this.formatLayout = 'NCHW';
this.isExecuted = false; this.isExecuted = false;
// 网络层数 // 网络层数
this.iLayer = 0; this.iLayer = 0;
if (this.options && this.options.options && this.options.options.test === true) { if (this.options && this.options.options ) {
this.test = true; if (this.options.options.test === true) {
this.test = true;
}
if (this.options.options.formatLayout) {
this.formatLayout = this.options.options.formatLayout;
}
} }
if (!this.inst) { if (!this.inst) {
...@@ -83,6 +91,9 @@ export default class Graph { ...@@ -83,6 +91,9 @@ export default class Graph {
if (executor.type === 'fetch') { if (executor.type === 'fetch') {
return; return;
} }
opindex++;
// console.log(opindex);
//if (executor.opData) console.log(executor.opData.iLayer);
executor.execute(this.inst, this.isExecuted); executor.execute(this.inst, this.isExecuted);
if (executor.next) { if (executor.next) {
const id = executor.next; const id = executor.next;
...@@ -187,6 +198,106 @@ export default class Graph { ...@@ -187,6 +198,106 @@ export default class Graph {
return item; return item;
}); });
} }
execute_try(temp, ops, idtoindex, executed, inline, prev){
console.log('execute_try!first look at this op');
console.log(ops[temp]);
let canrun = this.checkifcanrun(temp, ops, idtoindex, executed);
if (canrun === false) {
// console.log('canrun === false!');
var a = inline.pop();
this.execute_try(idtoindex[a.id], ops, idtoindex, executed, inline, prev);
return;
}
if (prev >=0) {
ops[prev].next = ops[temp].id;
}
ops[temp].outputsName.forEach(function(item, index) {
executed[item] = true;
})
let next = this.getNextByOp(ops, ops[temp]);
// console.log('this is its next:');
// console.dir(next);
while (next.length === 1) {
let flag = true;
for (let i = 0; i < next[0].inputsName.length; i++){
if (executed[next[0].inputsName[i]] === false) flag = false;
}
if (flag === false) {
// console.log('can not execute next now! jump to another op:');
if (inline.length === 0) return;
prev = temp;
let a = inline.pop();
// console.dir(a);
ops[temp].next = a.id;
temp = idtoindex[a.id];
this.execute_try(temp, ops, idtoindex, executed, inline, prev);
return;
}
else {
// console.log('now execute next op! it is');
ops[temp].next = next[0].id;
temp = idtoindex[next[0].id];
// console.dir(ops[temp]);
next = this.getNextByOp(ops, ops[temp]);
// console.log('its next is: ');
ops[temp].outputsName.forEach(function(item, index) {
executed[item] = true;
})
// console.dir(next);
}
}
if (next.length > 1){
// console.log('next.length > 1!!!');
for (let i = next.length - 1; i >=0 ; i--){
inline.push(next[i]);
}
var a = inline.pop();
this.execute_try(idtoindex[a.id], ops, idtoindex, executed, inline, temp);
}
return;
}
arrangeMap(ops) {
// console.log('arrangeMap!');
// console.dir(ops);
var idtoindex = {};
var executed = {};
var inline = [];
let temp = 0;
// console.log('graph ops:');
// console.dir(ops);
let ops1 = ops;
ops1.forEach(function(item, index) {
idtoindex[item.id] = index;
// console.dir(item);
item.outputsName.forEach(function(i, idx){
executed[i] = false;
})
});
//ops[0].inputsName[0] = {name : "feed"};
// ops[0].outputsName[0] = {name : "image"};
this.execute_try(temp, ops, idtoindex, executed, inline, -1);
return ops;
}
checkifcanrun(temp, ops, executed){
if (!ops[temp].inputsName) return true;
for (let i = 0; i < ops[temp].inputsName.length; i++){
if (executed[ops[temp].inputsName[i]] === false) return false;
}
return true;
}
/** /**
* Get Ops Nets Start Node * Get Ops Nets Start Node
* @param ops * @param ops
...@@ -222,12 +333,23 @@ export default class Graph { ...@@ -222,12 +333,23 @@ export default class Graph {
return item; return item;
}); });
} }
formatWeight(vars) {
if (this.formatLayout === 'NHWC') {
vars.map((item) => {
if (item.data && item.shape) {
item.data = Utils.nhwc2nchw(item.data, item.shape);
}
});
}
};
/** /**
* Create Ops Executor Object Map * Create Ops Executor Object Map
* @param ops * @param ops
* @returns {*} * @returns {*}
*/ */
createOpsMap(ops) { createOpsMap(ops) {
// console.log('ops!!');
// console.dir(ops);
return ops.map((item, idx) => { return ops.map((item, idx) => {
item.idx = idx; item.idx = idx;
const graphExecutor = new GraphExecutor(item); const graphExecutor = new GraphExecutor(item);
...@@ -250,6 +372,17 @@ export default class Graph { ...@@ -250,6 +372,17 @@ export default class Graph {
}); });
} }
getNextByOp(ops, op) {
return ops.filter((item, key) => {
for (let i = 0; i < item.inputsName.length; i++) {
for(let j = 0; j < op.outputsName.length; j++) {
if (item.inputsName[i] === op.outputsName[j]) {
return true;
}
}
}
});
}
/** /**
* dispose * dispose
*/ */
......
src/ops/dummy.js 0 → 100644
浏览文件 @ 6c40834f
module.exports.create = function (args, scope, gl) {
const output = scope[args.outputs.Out[0]]
return {
inferShape() {
output.dim = output.dim.forEach(d => d === -1 ? 1 : d)
},
compute() {
console.log(output)
}
}
}
\ No newline at end of file
src/ops/feed.js 0 → 100644
浏览文件 @ 6c40834f
module.exports.create = function (args, scope, gl) {
const output = scope[args.outputs.Out[0]]
const input = scope[args.inputs.X[0]]
return {
inferShape() {
output.dim = output.dim.map(d => d === -1 ? 1 : d)
},
compute() {
console.log(input)
console.log(output)
}
}
}
src/ops/fetch.js 0 → 100644
浏览文件 @ 6c40834f
module.exports.create = function (args, scope, gl) {
// const output = scope[args.outputs.Out[0]]
return {
inferShape() {
// output.dim = output.dim.forEach(d => d === -1 ? 1 : d)
},
compute() {
console.log(`${args.type} is going to be implemented`)
}
}
}
\ No newline at end of file
src/paddle/paddle.es6
浏览文件 @ 6c40834f
...@@ -47,8 +47,15 @@ export default class Paddle { ...@@ -47,8 +47,15 @@ export default class Paddle {
const graph = new Graph(that.options); const graph = new Graph(that.options);
that.graph = graph; that.graph = graph;
that.graph.data = artifacts.data; that.graph.data = artifacts.data;
that.graph.formatWeight(that.graph.data.vars);
const opsMap = that.graph.createOpsMap(that.graph.data.ops, that.graph.data.vars); const opsMap = that.graph.createOpsMap(that.graph.data.ops, that.graph.data.vars);
that.graph.weightMap = that.graph.constructOpsMap(opsMap); const opsMap1 = that.graph.constructOpsMap(opsMap);
// console.log('opsMap1!');
// console.dir(opsMap1);
const opsMap2 = that.graph.arrangeMap(opsMap1);
// console.log('opsMap2!');
// console.dir(opsMap2);
that.graph.weightMap = opsMap2;
} }
/** /**
* Executes inference for the model for given input tensors. * Executes inference for the model for given input tensors.
......
src/runtime/runtime.es6
浏览文件 @ 6c40834f
...@@ -2,9 +2,9 @@ ...@@ -2,9 +2,9 @@
import Gpu from '../gpu/gpu'; import Gpu from '../gpu/gpu';
import getMaxUniforms from '../test/getMaxUniforms'; import getMaxUniforms from '../test/getMaxUniforms';
import Factory from '../factory/fshader/factory'; import Factory from '../factory/fshader/factory';
import {getTextureShapeInfo} from '../utils/opData'; // import {getTextureShapeInfo} from '../utils/opData';
// 生成factory实例 // 生成factory实例
const factory = new Factory({}); // const factory = new Factory({});
/** /**
* @file gpu运行时 * @file gpu运行时
* @author wangqun@baidu.com, yangmingming@baidu.com * @author wangqun@baidu.com, yangmingming@baidu.com
...@@ -48,7 +48,7 @@ export default { ...@@ -48,7 +48,7 @@ export default {
gpu.attachFrameBuffer(opData.iLayer, outTensorId); gpu.attachFrameBuffer(opData.iLayer, outTensorId);
// let end = +Date.now(); // let end = +Date.now();
let bufferStatus = gpu.frameBufferIsComplete(); let bufferStatus = gpu.frameBufferIsComplete();
if (bufferStatus.isComplete) { // if (bufferStatus.isComplete) {
// start = +Date.now(); // start = +Date.now();
// timeObj['buferstatus-time'] = start - end; // timeObj['buferstatus-time'] = start - end;
// gpu.attachShader(opData.fshader); // gpu.attachShader(opData.fshader);
...@@ -62,7 +62,7 @@ export default { ...@@ -62,7 +62,7 @@ export default {
// 开始计算，执行 gl.drawArrays // 开始计算，执行 gl.drawArrays
this.gpu.render(opData.renderData, opData.iLayer, isRendered); this.gpu.render(opData.renderData, opData.iLayer, isRendered);
} // }
}); });
}, },
...@@ -86,6 +86,7 @@ export default { ...@@ -86,6 +86,7 @@ export default {
// 其实这里应该有个fetch的执行调用或者fetch的输出 // 其实这里应该有个fetch的执行调用或者fetch的输出
// log.start('后处理-读取数据'); // log.start('后处理-读取数据');
// 开始读数据 // 开始读数据
// window.log.end('执行时间');
return this.gpu.downloadFoat32TensorFromBuffer(pbo); return this.gpu.downloadFoat32TensorFromBuffer(pbo);
}, },
......
src/shader/concat/main.es6
浏览文件 @ 6c40834f
...@@ -8,15 +8,15 @@ export default ` ...@@ -8,15 +8,15 @@ export default `
void main(void) { void main(void) {
ivec4 oPos = getOutputTensorPos(); ivec4 oPos = getOutputTensorPos();
// 输出坐标转换为输入坐标 // 输出坐标转换为输入坐标
int sumVal = oPos.g + oPos.a * channel_out + oPos.b * channel_out * width_shape_out + oPos.r * channel_out * width_shape_out * height_shape_out; // int sumVal = oPos.g + oPos.a * channel_out + oPos.b * channel_out * width_shape_out + oPos.r * channel_out * width_shape_out * height_shape_out;
ivec4 new_oPos = transferFromNHWCtoNCHW(sumVal, channel_out, width_shape_out, height_shape_out, total_shape_out); // ivec4 new_oPos = transferFromNHWCtoNCHW(sumVal, channel_out, width_shape_out, height_shape_out, total_shape_out);
float o = 0.0; float o = 0.0;
if (new_oPos[dim] > inputs_dim[0] - 1) { if (oPos[dim] > inputs_dim[0] - 1) {
new_oPos[dim] = new_oPos[dim] - inputs_dim[0]; oPos[dim] = oPos[dim] - inputs_dim[0];
o = getValueFromTensorPos_counter(new_oPos.r, new_oPos.g, new_oPos.b, new_oPos.a); o = getValueFromTensorPos_counter(oPos.r, oPos.g, oPos.b, oPos.a);
} }
else { else {
o = getValueFromTensorPos_origin(new_oPos.r, new_oPos.g, new_oPos.b, new_oPos.a); o = getValueFromTensorPos_origin(oPos.r, oPos.g, oPos.b, oPos.a);
} }
setOutput(float(o)); setOutput(float(o));
} }
......
src/shader/conv2d_elementwise_add/main.es6
浏览文件 @ 6c40834f
...@@ -7,8 +7,8 @@ export default ` ...@@ -7,8 +7,8 @@ export default `
// start函数 // start函数
void main(void) { void main(void) {
ivec4 oPos = getOutputTensorPosLIMIT_OUT(); ivec4 oPos = getOutputTensorPosLIMIT_OUT();
int sumVal = oPos.g + oPos.a * channel_out + oPos.b * channel_out * width_shape_out; //int sumVal = oPos.g + oPos.a * channel_out + oPos.b * channel_out * width_shape_out;
ivec4 new_oPos = transferFromNHWCtoNCHW(sumVal, channel_out, width_shape_out, height_shape_out, total_shape_out); //ivec4 new_oPos = transferFromNHWCtoNCHW(sumVal, channel_out, width_shape_out, height_shape_out, total_shape_out);
int x = oPos.a; int x = oPos.a;
int c = oPos.g; int c = oPos.g;
int y = oPos.b; int y = oPos.b;
......
src/shader/conv2d_transpose/main.es6
浏览文件 @ 6c40834f
...@@ -12,7 +12,12 @@ export default ` ...@@ -12,7 +12,12 @@ export default `
int y = oPos.b; int y = oPos.b;
int b = oPos.r; int b = oPos.r;
float res = 0.0; float res = 0.0;
int temp_x = 0;
int temp_y = 0;
float o = 0.0;
float f = 0.0;
if (x % 2 == 1) x = x - 2;
if (y % 2 == 1) y = y - 2;
// 重排遍历顺序 // 重排遍历顺序
//int sumVal = oPos.g + oPos.a * channel_out + oPos.b * channel_out * width_shape_out; //int sumVal = oPos.g + oPos.a * channel_out + oPos.b * channel_out * width_shape_out;
//int new_a = sumVal % width_shape_out; //int new_a = sumVal % width_shape_out;
...@@ -22,41 +27,37 @@ export default ` ...@@ -22,41 +27,37 @@ export default `
//int c = new_g; //int c = new_g;
//int y = new_b; //int y = new_b;
// 获取output的坐标 // 获取output的坐标
int oTensorChannel = (c / (channel_out / groups)) * channel_filter; int oTensorChannel = int(c * groups / channel_out) * channel_origin;
int oy = y;
int oy = y * 1 - padTop;
for (int fy = 0; fy < height_shape_filter; fy++) { for (int fy = 0; fy < height_shape_filter; fy++) {
if (oy >= height_shape_origin) {
break;
}
if (oy < 0) { if (oy < 0) {
oy += dilation_v; oy += dilation_v;
continue; continue;
} }
int ox = x * 1 - padLeft; int ox = x;
for (int fx = 0; fx < width_shape_filter; fx++) { for (int fx = 0; fx < width_shape_filter; fx++) {
if (ox >= width_shape_origin) {
break;
}
if (ox < 0) { if (ox < 0) {
ox += dilation_h; ox += dilation_h;
continue; continue;
} }
// channel计算 // channel计算
for (int j = 0; j < channel_filter; j++) { for (int j = 0; j < channel_origin; j++) {
float o = 0.0;
if (ox % stride_h == 0 && oy % stride_v == 0) { if (ox % stride_h == 0 && oy % stride_v == 0) {
int temp_x = int(ox / stride_h); temp_x = int(floor(float(ox) / float(stride_h)));
int temp_y = int(oy / stride_v); temp_y = int(floor(float(oy) / float(stride_v)));
o = getValueFromTensorPosLIMIT_ORIGIN_origin(b, oTensorChannel + j, temp_y, temp_x); if (temp_x < width_shape_origin && temp_y < height_shape_origin){
o = getValueFromTensorPosLIMIT_ORIGIN_origin(b, j, temp_y, temp_x);
f = getValueFromTensorPosLIMIT_FILTER_filter(j, c, fy, fx);
res += f * o;
}
} }
float f = getValueFromTensorPosLIMIT_FILTER_filter(c, j, fy, fx);
res += f * o;
} }
ox += dilation_h; ox += dilation_h;
} }
oy += dilation_v; oy += dilation_v;
} }
setOutput(res); setOutput(float(res));
} }
`; `;
src/shader/conv2d_transpose/params.es6
浏览文件 @ 6c40834f
...@@ -28,11 +28,13 @@ export default ` ...@@ -28,11 +28,13 @@ export default `
const int stride_h = int(STRIDES_X); const int stride_h = int(STRIDES_X);
const int stride_v = int(STRIDES_Y); const int stride_v = int(STRIDES_Y);
// padding的数目 // padding的数目
const int padLeft = width_shape_filter - PADDINGS_X - 1; //const int padLeft = width_shape_filter - PADDINGS_X - 1;
const int padTop = height_shape_filter - PADDINGS_Y - 1; //const int padTop = height_shape_filter - PADDINGS_Y - 1;
const int padLeft = PADDINGS_X;
const int padTop = PADDINGS_Y;
// dilation膨胀系数 // dilation膨胀系数
const int dilation_h = DILATION_H; const int dilation_h = DILATIONS_X;
const int dilation_v = DILATION_V; const int dilation_v = DILATIONS_Y;
// groups // groups
const int groups = GROUPS; const int groups = GROUPS;
......
src/shader/elementwise_add/main.es6
浏览文件 @ 6c40834f
...@@ -8,22 +8,23 @@ export default ` ...@@ -8,22 +8,23 @@ export default `
void main(void) { void main(void) {
// 输出数据 // 输出数据
ivec4 oPos = getOutputTensorPos(); ivec4 oPos = getOutputTensorPos();
int sumVal = oPos.g + oPos.a * channel_origin + oPos.b * channel_origin * width_shape_origin + oPos.r * channel_origin * width_shape_origin * height_shape_origin;
float o = getValueFromTensorPos_origin(oPos.r, oPos.g, oPos.b, oPos.a); float o = getValueFromTensorPos_origin(oPos.r, oPos.g, oPos.b, oPos.a);
ivec4 pos_counter; ivec4 pos_counter;
pos_counter.r = channel_out; float c = 0.0;
pos_counter.g = height_shape_origin;
pos_counter.b = width_shape_origin; if (axis == 1){
pos_counter.a = 1; c = getValueFromTensorPos_counter(0, oPos.r, oPos.g, oPos.b);
int index = 0; }
for (int i = 4 - length_shape_origin + axis; i < 4 - length_shape_origin + axis + length_shape_counter; i++ ){ else if (axis == 2){
if (index > 0) { c = getValueFromTensorPos_counter(0, 0, oPos.r, oPos.g);
index = index * pos_counter[i]; }
} else if (axis == 3){
index += oPos[i]; c = getValueFromTensorPos_counter(0, 0, 0, oPos.r);
} }
float c = getValueFromTensorPos_counter(oPos.r, oPos.g, oPos.b, oPos.a); else {
c = getValueFromTensorPos_counter(oPos.r, oPos.g, oPos.b, oPos.a);
}
float res = c + o; float res = c + o;
setOutput(res); setOutput(float(res));
} }
`; `;
src/shader/pool2d_max/main.es6
浏览文件 @ 6c40834f
...@@ -5,7 +5,7 @@ ...@@ -5,7 +5,7 @@
export default ` export default `
// start函数 // start函数
void main(void) { void main(void) {
float res = (-1.0 / exp(-20.0)); float res = 0.0;
// 获取output的坐标 // 获取output的坐标
ivec4 out_pos = getOutputTensorPosLIMIT_OUT(); ivec4 out_pos = getOutputTensorPosLIMIT_OUT();
int b = out_pos[0]; int b = out_pos[0];
......
src/shader/reshape2/conf.es6 0 → 100644
浏览文件 @ 6c40834f
/* eslint-disable */
/**
* @file batchnorm的配置文件
* @author chenhaoze
*/
export default {
dep: [
{
func: 'getValueFromTensorPos',
conf: {
TENSOR_NAME: 'origin'
}
},
{
func: 'transferFromNHWCtoNCHW',
conf:{
}
}
],
conf: [
'WIDTH_SHAPE_ORIGIN',
'HEIGHT_SHAPE_ORIGIN',
'LENGTH_SHAPE_ORIGIN',
'WIDTH_TEXTURE_ORIGIN',
'HEIGHT_TEXTURE_ORIGIN',
'CHANNEL_ORIGIN',
'WIDTH_SHAPE_OUT',
'HEIGHT_SHAPE_OUT',
'WIDTH_TEXTURE_OUT',
'HEIGHT_TEXTURE_OUT',
'CHANNEL_OUT',
'OFFSET_Y_OUT',
'MULTI_VALUE',
'BIAS_VALUE',
'ACTIVE_FUNCTION'
],
input: [
{
tensor: 'origin',
variable: 'texture',
setter: 'initTexture',
type: 'texture'
}
]
};
src/shader/reshape2/main.es6 0 → 100644
浏览文件 @ 6c40834f
/* eslint-disable */
/**
* @file reshape主函数
* @author chenhaoze
*/
export default `
// start函数
void main(void) {
// 输出数据
ivec4 oPos = getOutputTensorPos();
// 输出坐标转换为输入坐标
int sumVal = oPos.a + oPos.b * width_shape_out + oPos.g * height_shape_out * width_shape_out + oPos.r * channel_out * width_shape_out * height_shape_out;
ivec4 new_oPos = transferFromNHWCtoNCHW(sumVal, channel_origin, width_shape_origin, height_shape_origin, total_shape_origin);
float o = getValueFromTensorPos_origin(new_oPos.r, new_oPos.g, new_oPos.b, new_oPos.a);
setOutput(float(o));
}
`;
src/shader/reshape2/params.es6 0 → 100644
浏览文件 @ 6c40834f
/* eslint-disable */
/**
* @file batchnorm参数文件
* @author chenhaoze
*/
export default `
// 输入数据
const int width_shape_origin = WIDTH_SHAPE_ORIGIN;
const int height_shape_origin = HEIGHT_SHAPE_ORIGIN;
const int length_shape_origin = LENGTH_SHAPE_ORIGIN;
const int width_texture_origin = WIDTH_TEXTURE_ORIGIN;
const int height_texture_origin = HEIGHT_TEXTURE_ORIGIN;
const int channel_origin = CHANNEL_ORIGIN;
const int total_shape_origin = TOTAL_SHAPE_ORIGIN;
// 输入数据
uniform sampler2D texture_origin;
`;
src/shader/split/main.es6
浏览文件 @ 6c40834f
...@@ -9,10 +9,10 @@ void main(void) { ...@@ -9,10 +9,10 @@ void main(void) {
int length = int(target_value.length() / num); int length = int(target_value.length() / num);
ivec4 oPos = getOutputTensorPos(); ivec4 oPos = getOutputTensorPos();
// 输出坐标转换为输入坐标 // 输出坐标转换为输入坐标
int sumVal = oPos.g + oPos.a * channel_out + oPos.b * channel_out * width_shape_out + oPos.r * channel_out * width_shape_out * height_shape_out; //int sumVal = oPos.g + oPos.a * channel_out + oPos.b * channel_out * width_shape_out + oPos.r * channel_out * width_shape_out * height_shape_out;
ivec4 new_oPos = transferFromNHWCtoNCHW(sumVal, channel_out, width_shape_out, height_shape_out, total_shape_out); //ivec4 new_oPos = transferFromNHWCtoNCHW(sumVal, channel_out, width_shape_out, height_shape_out, total_shape_out);
new_oPos[dim] = new_oPos[dim] + layer_run_time * length; oPos[dim] = oPos[dim] + layer_run_time * length;
float o = getValueFromTensorPos_origin(new_oPos.r, new_oPos.g, new_oPos.b, new_oPos.a); float o = getValueFromTensorPos_origin(oPos.r, oPos.g, oPos.b, oPos.a);
setOutput(float(o)); setOutput(float(o));
} }
`; `;
src/shader/transpose2/conf.es6 0 → 100644
浏览文件 @ 6c40834f
/* eslint-disable */
/**
* @file batchnorm的配置文件
* @author chenhaoze
*/
export default {
dep: [
{
func: 'getValueFromTensorPos',
conf: {
TENSOR_NAME: 'origin'
}
},
{
func: 'transferFromNHWCtoNCHW',
conf:{
}
}
],
conf: [
'WIDTH_SHAPE_ORIGIN',
'HEIGHT_SHAPE_ORIGIN',
'LENGTH_SHAPE_ORIGIN',
'WIDTH_TEXTURE_ORIGIN',
'HEIGHT_TEXTURE_ORIGIN',
'CHANNEL_ORIGIN',
'WIDTH_SHAPE_OUT',
'HEIGHT_SHAPE_OUT',
'WIDTH_TEXTURE_OUT',
'HEIGHT_TEXTURE_OUT',
'CHANNEL_OUT',
'OFFSET_Y_OUT',
'MULTI_VALUE',
'BIAS_VALUE',
'ACTIVE_FUNCTION'
],
input: [
{
tensor: 'origin',
variable: 'texture',
setter: 'initTexture',
type: 'texture'
}
]
};
src/shader/transpose2/main.es6 0 → 100644
浏览文件 @ 6c40834f
/* eslint-disable */
/**
* @file transpose主函数
* @author chenhaoze
*/
export default `
// start函数
void main(void) {
// 输出数据
ivec4 oPos = getOutputTensorPos();
// 重排遍历顺序
//int sumVal = oPos.g + oPos.a * channel_out + oPos.b * channel_out * width_shape_out + oPos.r * channel_out * width_shape_out * height_shape_out;
//ivec4 new_oPos = transferFromNHWCtoNCHW(sumVal, channel_out, width_shape_out, height_shape_out, total_shape_origin);
// 转置 坐标变换
//oPos = new_oPos;
float o = 0.0;
if (perm_size == 1) {
o = getValueFromTensorPos_origin(oPos[0], oPos[1], oPos[2], oPos[3]);
}
else if (perm_size == 2) {
o = getValueFromTensorPos_origin(oPos[0], oPos[1], oPos[min(2 + perm_0, 3)], oPos[min(2 + perm_1, 3)]);
}
else if (perm_size == 3) {
o = getValueFromTensorPos_origin(oPos[0], oPos[min(1 + perm_0, 3)], oPos[min(1 + perm_1, 3)], oPos[min(1 + perm_2, 3)]);
}
else if (perm_size == 4) {
o = getValueFromTensorPos_origin(oPos[perm_0], oPos[perm_1], oPos[perm_2], oPos[perm_3]);
}
setOutput(float(o));
}
`;
src/shader/transpose2/params.es6 0 → 100644
浏览文件 @ 6c40834f
/* eslint-disable */
/**
* @file batchnorm参数文件
* @author chenhaoze
*/
export default `
// 输入数据
const int width_shape_origin = WIDTH_SHAPE_ORIGIN;
const int height_shape_origin = HEIGHT_SHAPE_ORIGIN;
const int length_shape_origin = LENGTH_SHAPE_ORIGIN;
const int width_texture_origin = WIDTH_TEXTURE_ORIGIN;
const int height_texture_origin = HEIGHT_TEXTURE_ORIGIN;
const int channel_origin = CHANNEL_ORIGIN;
const int total_shape_origin = TOTAL_SHAPE_ORIGIN;
const int perm_size = PERM_SIZE;
const int perm_0 = PERM_0;
const int perm_1 = PERM_1;
const int perm_2 = PERM_2;
const int perm_3 = PERM_3;
// 输入数据
uniform sampler2D texture_origin;
`;
src/utils/opData.es6
浏览文件 @ 6c40834f
...@@ -65,8 +65,8 @@ const opBehavior = { ...@@ -65,8 +65,8 @@ const opBehavior = {
'mergeTensor' 'mergeTensor'
], ],
elementwise_add: [ elementwise_add: [
'needBatch', 'processAxis',
'processAxis' 'needBatch'
], ],
conv2d_elementwise_add: [ conv2d_elementwise_add: [
'mergeAttrs', 'mergeAttrs',
...@@ -95,11 +95,14 @@ const opBehavior = { ...@@ -95,11 +95,14 @@ const opBehavior = {
'reshape', 'reshape',
'needBatch' 'needBatch'
], ],
reshape: [ bilinear_interp:[
'needBatch'
],
reshape2: [
'needBatch', 'needBatch',
'inferShape' 'inferShape'
], ],
transpose: [ transpose2: [
'needBatch', 'needBatch',
'setPerm' 'setPerm'
], ],
...@@ -122,6 +125,7 @@ const mergeType = 'conv2d-elementwise_add'; ...@@ -122,6 +125,7 @@ const mergeType = 'conv2d-elementwise_add';
export default class OpData { export default class OpData {
constructor(name, input = {}, output = {}, attrs = {}) { constructor(name, input = {}, output = {}, attrs = {}) {
// console.dir(this);
this.realName = name; this.realName = name;
this.name = name; this.name = name;
this.attrs = attrs; this.attrs = attrs;
...@@ -150,7 +154,7 @@ export default class OpData { ...@@ -150,7 +154,7 @@ export default class OpData {
} }
inferShape(){ inferShape(){
if (this.name == 'reshape'){ if (this.name == 'reshape2'){
let inputShape = this.input.X[0].shape; let inputShape = this.input.X[0].shape;
let targetShape = this.attrs.new_shape; let targetShape = this.attrs.new_shape;
for (let i = 0; i < targetShape.length; i++){ for (let i = 0; i < targetShape.length; i++){
...@@ -201,6 +205,7 @@ export default class OpData { ...@@ -201,6 +205,7 @@ export default class OpData {
// 默认取第一个数据 // 默认取第一个数据
const data = this.output[key] || [{}]; const data = this.output[key] || [{}];
if (tensorName[key.toLowerCase()]) { if (tensorName[key.toLowerCase()]) {
// console.dir(this);
data.forEach(item => { data.forEach(item => {
item.tensorName = tensorName[key.toLowerCase()]; item.tensorName = tensorName[key.toLowerCase()];
tensorData.push(item); tensorData.push(item);
...@@ -276,6 +281,7 @@ export default class OpData { ...@@ -276,6 +281,7 @@ export default class OpData {
this.outputTensors.forEach(outTensor => { this.outputTensors.forEach(outTensor => {
const params = JSON.parse(JSON.stringify(this.data)); const params = JSON.parse(JSON.stringify(this.data));
// 获取output tensor的数据 // 获取output tensor的数据
tensorAttrs.forEach(attr => { tensorAttrs.forEach(attr => {
params[attr+ '_' + outTensor.name] = outTensor[attr]; params[attr+ '_' + outTensor.name] = outTensor[attr];
}); });
...@@ -289,7 +295,7 @@ export default class OpData { ...@@ -289,7 +295,7 @@ export default class OpData {
} }
setPerm(tensorData = []){ setPerm(tensorData = []){
let arrayPerm = this.attrs['perm']; let arrayPerm = this.attrs['axis'];
let l = arrayPerm.length; let l = arrayPerm.length;
if (l == 3) { if (l == 3) {
if (arrayPerm == [2,0,1]) { if (arrayPerm == [2,0,1]) {
...@@ -430,7 +436,15 @@ export default class OpData { ...@@ -430,7 +436,15 @@ export default class OpData {
} }
normalizeDim() { normalizeDim() {
const origin_shape = this.input.X[0].shape; let origin_shape_temp = this.input.X[0].shape;
if (origin_shape_temp.length < 4) {
let batch = [];
for (let i = 0; i < (4 - origin_shape_temp.length); i++) {
batch.push(1);
}
origin_shape_temp = batch.concat(origin_shape_temp);
}
const origin_shape = origin_shape_temp;
const axis = this.attrs.axis > -1 ? this.attrs.axis : origin_shape.length + this.attrs.axis; const axis = this.attrs.axis > -1 ? this.attrs.axis : origin_shape.length + this.attrs.axis;
const dim_value = []; const dim_value = [];
for (let index = 0; index < origin_shape[axis]; index++) { for (let index = 0; index < origin_shape[axis]; index++) {
...@@ -445,19 +459,14 @@ export default class OpData { ...@@ -445,19 +459,14 @@ export default class OpData {
processAxis() { processAxis() {
let shape_x = this.input.X[0].shape; let shape_x = this.input.X[0].shape;
let shape_y = this.input.Y[0].shape; let shape_y = this.input.Y[0].shape;
let y_length = shape_y.length; let axis_temp = this.attrs['axis'];
for (let i = shape_y.length - 1; i >=0 ;i--){ if (axis_temp == -1) {
if (shape_y[i] == 1) { this.attrs['axis'] = shape_x.length - shape_y.length;
y_length -= 1; }
} else {
} this.attrs['axis'] = 4 - shape_y.length - axis_temp;
let axis_temp = this.attrs['axis']; }
if (axis_temp == -1) {
this.attrs['axis'] = shape_x.length - y_length;
}
this.attrs['shape_length_origin'] = shape_x.length;
this.attrs['shape_length_counter'] = y_length;
} }
reshape(tensorData = []) { reshape(tensorData = []) {
......
src/utils/tensor.es6
浏览文件 @ 6c40834f
...@@ -57,13 +57,6 @@ export default class Tensor { ...@@ -57,13 +57,6 @@ export default class Tensor {
} }
this.data = data; this.data = data;
} }
else {
if (opts.data.length > this.total) {
opts.data = opts.data.slice(0, this.total);
}
this.data = new Float32Array(opts.data);
debugger;
}
} else { } else {
// batchnorm的scale // batchnorm的scale
......
src/utils/utils.es6
浏览文件 @ 6c40834f
...@@ -283,6 +283,29 @@ export default { ...@@ -283,6 +283,29 @@ export default {
numbers.push(i + ": " + data[i]); numbers.push(i + ": " + data[i]);
} }
console.log(numbers) console.log(numbers)
},
softmax(nchwData) {
let result = new Float32Array(nchwData.length);
let maxValue = nchwData[0];
let tempValue = 0.0;
let sumValue = 0.0;
for (let i = 1; i < nchwData.lenght; i++) {
tempValue = nchwData[i];
if (maxValue < tempValue) {
maxValue = tempValue;
}
}
for (let i = 0; i < nchwData.length; i++) {
tempValue = Math.exp(nchwData[i] - maxValue);
result[i] = tempValue;
sumValue = sumValue + tempValue;
}
for (let i = 0; i < nchwData.length; i++) {
result[i] = result[i] / sumValue;
}
return result;
} }
}; };
/* eslint-enable */ /* eslint-enable */
test/data/map.json 0 → 100644
浏览文件 @ 6c40834f
{0: 'tench, Tinca tinca',
1: 'goldfish, Carassius auratus',
2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
3: 'tiger shark, Galeocerdo cuvieri',
4: 'hammerhead, hammerhead shark',
5: 'electric ray, crampfish, numbfish, torpedo',
6: 'stingray',
7: 'cock',
8: 'hen',
9: 'ostrich, Struthio camelus',
10: 'brambling, Fringilla montifringilla',
11: 'goldfinch, Carduelis carduelis',
12: 'house finch, linnet, Carpodacus mexicanus',
13: 'junco, snowbird',
14: 'indigo bunting, indigo finch, indigo bird, Passerina cyanea',
15: 'robin, American robin, Turdus migratorius',
16: 'bulbul',
17: 'jay',
18: 'magpie',
19: 'chickadee',
20: 'water ouzel, dipper',
21: 'kite',
22: 'bald eagle, American eagle, Haliaeetus leucocephalus',
23: 'vulture',
24: 'great grey owl, great gray owl, Strix nebulosa',
25: 'European fire salamander, Salamandra salamandra',
26: 'common newt, Triturus vulgaris',
27: 'eft',
28: 'spotted salamander, Ambystoma maculatum',
29: 'axolotl, mud puppy, Ambystoma mexicanum',
30: 'bullfrog, Rana catesbeiana',
31: 'tree frog, tree-frog',
32: 'tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui',
33: 'loggerhead, loggerhead turtle, Caretta caretta',
34: 'leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea',
35: 'mud turtle',
36: 'terrapin',
37: 'box turtle, box tortoise',
38: 'banded gecko',
39: 'common iguana, iguana, Iguana iguana',
40: 'American chameleon, anole, Anolis carolinensis',
41: 'whiptail, whiptail lizard',
42: 'agama',
43: 'frilled lizard, Chlamydosaurus kingi',
44: 'alligator lizard',
45: 'Gila monster, Heloderma suspectum',
46: 'green lizard, Lacerta viridis',
47: 'African chameleon, Chamaeleo chamaeleon',
48: 'Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis',
49: 'African crocodile, Nile crocodile, Crocodylus niloticus',
50: 'American alligator, Alligator mississipiensis',
51: 'triceratops',
52: 'thunder snake, worm snake, Carphophis amoenus',
53: 'ringneck snake, ring-necked snake, ring snake',
54: 'hognose snake, puff adder, sand viper',
55: 'green snake, grass snake',
56: 'king snake, kingsnake',
57: 'garter snake, grass snake',
58: 'water snake',
59: 'vine snake',
60: 'night snake, Hypsiglena torquata',
61: 'boa constrictor, Constrictor constrictor',
62: 'rock python, rock snake, Python sebae',
63: 'Indian cobra, Naja naja',
64: 'green mamba',
65: 'sea snake',
66: 'horned viper, cerastes, sand viper, horned asp, Cerastes cornutus',
67: 'diamondback, diamondback rattlesnake, Crotalus adamanteus',
68: 'sidewinder, horned rattlesnake, Crotalus cerastes',
69: 'trilobite',
70: 'harvestman, daddy longlegs, Phalangium opilio',
71: 'scorpion',
72: 'black and gold garden spider, Argiope aurantia',
73: 'barn spider, Araneus cavaticus',
74: 'garden spider, Aranea diademata',
75: 'black widow, Latrodectus mactans',
76: 'tarantula',
77: 'wolf spider, hunting spider',
78: 'tick',
79: 'centipede',
80: 'black grouse',
81: 'ptarmigan',
82: 'ruffed grouse, partridge, Bonasa umbellus',
83: 'prairie chicken, prairie grouse, prairie fowl',
84: 'peacock',
85: 'quail',
86: 'partridge',
87: 'African grey, African gray, Psittacus erithacus',
88: 'macaw',
89: 'sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita',
90: 'lorikeet',
91: 'coucal',
92: 'bee eater',
93: 'hornbill',
94: 'hummingbird',
95: 'jacamar',
96: 'toucan',
97: 'drake',
98: 'red-breasted merganser, Mergus serrator',
99: 'goose',
100: 'black swan, Cygnus atratus',
101: 'tusker',
102: 'echidna, spiny anteater, anteater',
103: 'platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus',
104: 'wallaby, brush kangaroo',
105: 'koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus',
106: 'wombat',
107: 'jellyfish',
108: 'sea anemone, anemone',
109: 'brain coral',
110: 'flatworm, platyhelminth',
111: 'nematode, nematode worm, roundworm',
112: 'conch',
113: 'snail',
114: 'slug',
115: 'sea slug, nudibranch',
116: 'chiton, coat-of-mail shell, sea cradle, polyplacophore',
117: 'chambered nautilus, pearly nautilus, nautilus',
118: 'Dungeness crab, Cancer magister',
119: 'rock crab, Cancer irroratus',
120: 'fiddler crab',
121: 'king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica',
122: 'American lobster, Northern lobster, Maine lobster, Homarus americanus',
123: 'spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish',
124: 'crayfish, crawfish, crawdad, crawdaddy',
125: 'hermit crab',
126: 'isopod',
127: 'white stork, Ciconia ciconia',
128: 'black stork, Ciconia nigra',
129: 'spoonbill',
130: 'flamingo',
131: 'little blue heron, Egretta caerulea',
132: 'American egret, great white heron, Egretta albus',
133: 'bittern',
134: 'crane',
135: 'limpkin, Aramus pictus',
136: 'European gallinule, Porphyrio porphyrio',
137: 'American coot, marsh hen, mud hen, water hen, Fulica americana',
138: 'bustard',
139: 'ruddy turnstone, Arenaria interpres',
140: 'red-backed sandpiper, dunlin, Erolia alpina',
141: 'redshank, Tringa totanus',
142: 'dowitcher',
143: 'oystercatcher, oyster catcher',
144: 'pelican',
145: 'king penguin, Aptenodytes patagonica',
146: 'albatross, mollymawk',
147: 'grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus',
148: 'killer whale, killer, orca, grampus, sea wolf, Orcinus orca',
149: 'dugong, Dugong dugon',
150: 'sea lion',
151: 'Chihuahua',
152: 'Japanese spaniel',
153: 'Maltese dog, Maltese terrier, Maltese',
154: 'Pekinese, Pekingese, Peke',
155: 'Shih-Tzu',
156: 'Blenheim spaniel',
157: 'papillon',
158: 'toy terrier',
159: 'Rhodesian ridgeback',
160: 'Afghan hound, Afghan',
161: 'basset, basset hound',
162: 'beagle',
163: 'bloodhound, sleuthhound',
164: 'bluetick',
165: 'black-and-tan coonhound',
166: 'Walker hound, Walker foxhound',
167: 'English foxhound',
168: 'redbone',
169: 'borzoi, Russian wolfhound',
170: 'Irish wolfhound',
171: 'Italian greyhound',
172: 'whippet',
173: 'Ibizan hound, Ibizan Podenco',
174: 'Norwegian elkhound, elkhound',
175: 'otterhound, otter hound',
176: 'Saluki, gazelle hound',
177: 'Scottish deerhound, deerhound',
178: 'Weimaraner',
179: 'Staffordshire bullterrier, Staffordshire bull terrier',
180: 'American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier',
181: 'Bedlington terrier',
182: 'Border terrier',
183: 'Kerry blue terrier',
184: 'Irish terrier',
185: 'Norfolk terrier',
186: 'Norwich terrier',
187: 'Yorkshire terrier',
188: 'wire-haired fox terrier',
189: 'Lakeland terrier',
190: 'Sealyham terrier, Sealyham',
191: 'Airedale, Airedale terrier',
192: 'cairn, cairn terrier',
193: 'Australian terrier',
194: 'Dandie Dinmont, Dandie Dinmont terrier',
195: 'Boston bull, Boston terrier',
196: 'miniature schnauzer',
197: 'giant schnauzer',
198: 'standard schnauzer',
199: 'Scotch terrier, Scottish terrier, Scottie',
200: 'Tibetan terrier, chrysanthemum dog',
201: 'silky terrier, Sydney silky',
202: 'soft-coated wheaten terrier',
203: 'West Highland white terrier',
204: 'Lhasa, Lhasa apso',
205: 'flat-coated retriever',
206: 'curly-coated retriever',
207: 'golden retriever',
208: 'Labrador retriever',
209: 'Chesapeake Bay retriever',
210: 'German short-haired pointer',
211: 'vizsla, Hungarian pointer',
212: 'English setter',
213: 'Irish setter, red setter',
214: 'Gordon setter',
215: 'Brittany spaniel',
216: 'clumber, clumber spaniel',
217: 'English springer, English springer spaniel',
218: 'Welsh springer spaniel',
219: 'cocker spaniel, English cocker spaniel, cocker',
220: 'Sussex spaniel',
221: 'Irish water spaniel',
222: 'kuvasz',
223: 'schipperke',
224: 'groenendael',
225: 'malinois',
226: 'briard',
227: 'kelpie',
228: 'komondor',
229: 'Old English sheepdog, bobtail',
230: 'Shetland sheepdog, Shetland sheep dog, Shetland',
231: 'collie',
232: 'Border collie',
233: 'Bouvier des Flandres, Bouviers des Flandres',
234: 'Rottweiler',
235: 'German shepherd, German shepherd dog, German police dog, alsatian',
236: 'Doberman, Doberman pinscher',
237: 'miniature pinscher',
238: 'Greater Swiss Mountain dog',
239: 'Bernese mountain dog',
240: 'Appenzeller',
241: 'EntleBucher',
242: 'boxer',
243: 'bull mastiff',
244: 'Tibetan mastiff',
245: 'French bulldog',
246: 'Great Dane',
247: 'Saint Bernard, St Bernard',
248: 'Eskimo dog, husky',
249: 'malamute, malemute, Alaskan malamute',
250: 'Siberian husky',
251: 'dalmatian, coach dog, carriage dog',
252: 'affenpinscher, monkey pinscher, monkey dog',
253: 'basenji',
254: 'pug, pug-dog',
255: 'Leonberg',
256: 'Newfoundland, Newfoundland dog',
257: 'Great Pyrenees',
258: 'Samoyed, Samoyede',
259: 'Pomeranian',
260: 'chow, chow chow',
261: 'keeshond',
262: 'Brabancon griffon',
263: 'Pembroke, Pembroke Welsh corgi',
264: 'Cardigan, Cardigan Welsh corgi',
265: 'toy poodle',
266: 'miniature poodle',
267: 'standard poodle',
268: 'Mexican hairless',
269: 'timber wolf, grey wolf, gray wolf, Canis lupus',
270: 'white wolf, Arctic wolf, Canis lupus tundrarum',
271: 'red wolf, maned wolf, Canis rufus, Canis niger',
272: 'coyote, prairie wolf, brush wolf, Canis latrans',
273: 'dingo, warrigal, warragal, Canis dingo',
274: 'dhole, Cuon alpinus',
275: 'African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus',
276: 'hyena, hyaena',
277: 'red fox, Vulpes vulpes',
278: 'kit fox, Vulpes macrotis',
279: 'Arctic fox, white fox, Alopex lagopus',
280: 'grey fox, gray fox, Urocyon cinereoargenteus',
281: 'tabby, tabby cat',
282: 'tiger cat',
283: 'Persian cat',
284: 'Siamese cat, Siamese',
285: 'Egyptian cat',
286: 'cougar, puma, catamount, mountain lion, painter, panther, Felis concolor',
287: 'lynx, catamount',
288: 'leopard, Panthera pardus',
289: 'snow leopard, ounce, Panthera uncia',
290: 'jaguar, panther, Panthera onca, Felis onca',
291: 'lion, king of beasts, Panthera leo',
292: 'tiger, Panthera tigris',
293: 'cheetah, chetah, Acinonyx jubatus',
294: 'brown bear, bruin, Ursus arctos',
295: 'American black bear, black bear, Ursus americanus, Euarctos americanus',
296: 'ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus',
297: 'sloth bear, Melursus ursinus, Ursus ursinus',
298: 'mongoose',
299: 'meerkat, mierkat',
300: 'tiger beetle',
301: 'ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle',
302: 'ground beetle, carabid beetle',
303: 'long-horned beetle, longicorn, longicorn beetle',
304: 'leaf beetle, chrysomelid',
305: 'dung beetle',
306: 'rhinoceros beetle',
307: 'weevil',
308: 'fly',
309: 'bee',
310: 'ant, emmet, pismire',
311: 'grasshopper, hopper',
312: 'cricket',
313: 'walking stick, walkingstick, stick insect',
314: 'cockroach, roach',
315: 'mantis, mantid',
316: 'cicada, cicala',
317: 'leafhopper',
318: 'lacewing, lacewing fly',
319: "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk",
320: 'damselfly',
321: 'admiral',
322: 'ringlet, ringlet butterfly',
323: 'monarch, monarch butterfly, milkweed butterfly, Danaus plexippus',
324: 'cabbage butterfly',
325: 'sulphur butterfly, sulfur butterfly',
326: 'lycaenid, lycaenid butterfly',
327: 'starfish, sea star',
328: 'sea urchin',
329: 'sea cucumber, holothurian',
330: 'wood rabbit, cottontail, cottontail rabbit',
331: 'hare',
332: 'Angora, Angora rabbit',
333: 'hamster',
334: 'porcupine, hedgehog',
335: 'fox squirrel, eastern fox squirrel, Sciurus niger',
336: 'marmot',
337: 'beaver',
338: 'guinea pig, Cavia cobaya',
339: 'sorrel',
340: 'zebra',
341: 'hog, pig, grunter, squealer, Sus scrofa',
342: 'wild boar, boar, Sus scrofa',
343: 'warthog',
344: 'hippopotamus, hippo, river horse, Hippopotamus amphibius',
345: 'ox',
346: 'water buffalo, water ox, Asiatic buffalo, Bubalus bubalis',
347: 'bison',
348: 'ram, tup',
349: 'bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis',
350: 'ibex, Capra ibex',
351: 'hartebeest',
352: 'impala, Aepyceros melampus',
353: 'gazelle',
354: 'Arabian camel, dromedary, Camelus dromedarius',
355: 'llama',
356: 'weasel',
357: 'mink',
358: 'polecat, fitch, foulmart, foumart, Mustela putorius',
359: 'black-footed ferret, ferret, Mustela nigripes',
360: 'otter',
361: 'skunk, polecat, wood pussy',
362: 'badger',
363: 'armadillo',
364: 'three-toed sloth, ai, Bradypus tridactylus',
365: 'orangutan, orang, orangutang, Pongo pygmaeus',
366: 'gorilla, Gorilla gorilla',
367: 'chimpanzee, chimp, Pan troglodytes',
368: 'gibbon, Hylobates lar',
369: 'siamang, Hylobates syndactylus, Symphalangus syndactylus',
370: 'guenon, guenon monkey',
371: 'patas, hussar monkey, Erythrocebus patas',
372: 'baboon',
373: 'macaque',
374: 'langur',
375: 'colobus, colobus monkey',
376: 'proboscis monkey, Nasalis larvatus',
377: 'marmoset',
378: 'capuchin, ringtail, Cebus capucinus',
379: 'howler monkey, howler',
380: 'titi, titi monkey',
381: 'spider monkey, Ateles geoffroyi',
382: 'squirrel monkey, Saimiri sciureus',
383: 'Madagascar cat, ring-tailed lemur, Lemur catta',
384: 'indri, indris, Indri indri, Indri brevicaudatus',
385: 'Indian elephant, Elephas maximus',
386: 'African elephant, Loxodonta africana',
387: 'lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens',
388: 'giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca',
389: 'barracouta, snoek',
390: 'eel',
391: 'coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch',
392: 'rock beauty, Holocanthus tricolor',
393: 'anemone fish',
394: 'sturgeon',
395: 'gar, garfish, garpike, billfish, Lepisosteus osseus',
396: 'lionfish',
397: 'puffer, pufferfish, blowfish, globefish',
398: 'abacus',
399: 'abaya',
400: "academic gown, academic robe, judge's robe",
401: 'accordion, piano accordion, squeeze box',
402: 'acoustic guitar',
403: 'aircraft carrier, carrier, flattop, attack aircraft carrier',
404: 'airliner',
405: 'airship, dirigible',
406: 'altar',
407: 'ambulance',
408: 'amphibian, amphibious vehicle',
409: 'analog clock',
410: 'apiary, bee house',
411: 'apron',
412: 'ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin',
413: 'assault rifle, assault gun',
414: 'backpack, back pack, knapsack, packsack, rucksack, haversack',
415: 'bakery, bakeshop, bakehouse',
416: 'balance beam, beam',
417: 'balloon',
418: 'ballpoint, ballpoint pen, ballpen, Biro',
419: 'Band Aid',
420: 'banjo',
421: 'bannister, banister, balustrade, balusters, handrail',
422: 'barbell',
423: 'barber chair',
424: 'barbershop',
425: 'barn',
426: 'barometer',
427: 'barrel, cask',
428: 'barrow, garden cart, lawn cart, wheelbarrow',
429: 'baseball',
430: 'basketball',
431: 'bassinet',
432: 'bassoon',
433: 'bathing cap, swimming cap',
434: 'bath towel',
435: 'bathtub, bathing tub, bath, tub',
436: 'beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon',
437: 'beacon, lighthouse, beacon light, pharos',
438: 'beaker',
439: 'bearskin, busby, shako',
440: 'beer bottle',
441: 'beer glass',
442: 'bell cote, bell cot',
443: 'bib',
444: 'bicycle-built-for-two, tandem bicycle, tandem',
445: 'bikini, two-piece',
446: 'binder, ring-binder',
447: 'binoculars, field glasses, opera glasses',
448: 'birdhouse',
449: 'boathouse',
450: 'bobsled, bobsleigh, bob',
451: 'bolo tie, bolo, bola tie, bola',
452: 'bonnet, poke bonnet',
453: 'bookcase',
454: 'bookshop, bookstore, bookstall',
455: 'bottlecap',
456: 'bow',
457: 'bow tie, bow-tie, bowtie',
458: 'brass, memorial tablet, plaque',
459: 'brassiere, bra, bandeau',
460: 'breakwater, groin, groyne, mole, bulwark, seawall, jetty',
461: 'breastplate, aegis, egis',
462: 'broom',
463: 'bucket, pail',
464: 'buckle',
465: 'bulletproof vest',
466: 'bullet train, bullet',
467: 'butcher shop, meat market',
468: 'cab, hack, taxi, taxicab',
469: 'caldron, cauldron',
470: 'candle, taper, wax light',
471: 'cannon',
472: 'canoe',
473: 'can opener, tin opener',
474: 'cardigan',
475: 'car mirror',
476: 'carousel, carrousel, merry-go-round, roundabout, whirligig',
477: "carpenter's kit, tool kit",
478: 'carton',
479: 'car wheel',
480: 'cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM',
481: 'cassette',
482: 'cassette player',
483: 'castle',
484: 'catamaran',
485: 'CD player',
486: 'cello, violoncello',
487: 'cellular telephone, cellular phone, cellphone, cell, mobile phone',
488: 'chain',
489: 'chainlink fence',
490: 'chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour',
491: 'chain saw, chainsaw',
492: 'chest',
493: 'chiffonier, commode',
494: 'chime, bell, gong',
495: 'china cabinet, china closet',
496: 'Christmas stocking',
497: 'church, church building',
498: 'cinema, movie theater, movie theatre, movie house, picture palace',
499: 'cleaver, meat cleaver, chopper',
500: 'cliff dwelling',
501: 'cloak',
502: 'clog, geta, patten, sabot',
503: 'cocktail shaker',
504: 'coffee mug',
505: 'coffeepot',
506: 'coil, spiral, volute, whorl, helix',
507: 'combination lock',
508: 'computer keyboard, keypad',
509: 'confectionery, confectionary, candy store',
510: 'container ship, containership, container vessel',
511: 'convertible',
512: 'corkscrew, bottle screw',
513: 'cornet, horn, trumpet, trump',
514: 'cowboy boot',
515: 'cowboy hat, ten-gallon hat',
516: 'cradle',
517: 'crane',
518: 'crash helmet',
519: 'crate',
520: 'crib, cot',
521: 'Crock Pot',
522: 'croquet ball',
523: 'crutch',
524: 'cuirass',
525: 'dam, dike, dyke',
526: 'desk',
527: 'desktop computer',
528: 'dial telephone, dial phone',
529: 'diaper, nappy, napkin',
530: 'digital clock',
531: 'digital watch',
532: 'dining table, board',
533: 'dishrag, dishcloth',
534: 'dishwasher, dish washer, dishwashing machine',
535: 'disk brake, disc brake',
536: 'dock, dockage, docking facility',
537: 'dogsled, dog sled, dog sleigh',
538: 'dome',
539: 'doormat, welcome mat',
540: 'drilling platform, offshore rig',
541: 'drum, membranophone, tympan',
542: 'drumstick',
543: 'dumbbell',
544: 'Dutch oven',
545: 'electric fan, blower',
546: 'electric guitar',
547: 'electric locomotive',
548: 'entertainment center',
549: 'envelope',
550: 'espresso maker',
551: 'face powder',
552: 'feather boa, boa',
553: 'file, file cabinet, filing cabinet',
554: 'fireboat',
555: 'fire engine, fire truck',
556: 'fire screen, fireguard',
557: 'flagpole, flagstaff',
558: 'flute, transverse flute',
559: 'folding chair',
560: 'football helmet',
561: 'forklift',
562: 'fountain',
563: 'fountain pen',
564: 'four-poster',
565: 'freight car',
566: 'French horn, horn',
567: 'frying pan, frypan, skillet',
568: 'fur coat',
569: 'garbage truck, dustcart',
570: 'gasmask, respirator, gas helmet',
571: 'gas pump, gasoline pump, petrol pump, island dispenser',
572: 'goblet',
573: 'go-kart',
574: 'golf ball',
575: 'golfcart, golf cart',
576: 'gondola',
577: 'gong, tam-tam',
578: 'gown',
579: 'grand piano, grand',
580: 'greenhouse, nursery, glasshouse',
581: 'grille, radiator grille',
582: 'grocery store, grocery, food market, market',
583: 'guillotine',
584: 'hair slide',
585: 'hair spray',
586: 'half track',
587: 'hammer',
588: 'hamper',
589: 'hand blower, blow dryer, blow drier, hair dryer, hair drier',
590: 'hand-held computer, hand-held microcomputer',
591: 'handkerchief, hankie, hanky, hankey',
592: 'hard disc, hard disk, fixed disk',
593: 'harmonica, mouth organ, harp, mouth harp',
594: 'harp',
595: 'harvester, reaper',
596: 'hatchet',
597: 'holster',
598: 'home theater, home theatre',
599: 'honeycomb',
600: 'hook, claw',
601: 'hoopskirt, crinoline',
602: 'horizontal bar, high bar',
603: 'horse cart, horse-cart',
604: 'hourglass',
605: 'iPod',
606: 'iron, smoothing iron',
607: "jack-o'-lantern",
608: 'jean, blue jean, denim',
609: 'jeep, landrover',
610: 'jersey, T-shirt, tee shirt',
611: 'jigsaw puzzle',
612: 'jinrikisha, ricksha, rickshaw',
613: 'joystick',
614: 'kimono',
615: 'knee pad',
616: 'knot',
617: 'lab coat, laboratory coat',
618: 'ladle',
619: 'lampshade, lamp shade',
620: 'laptop, laptop computer',
621: 'lawn mower, mower',
622: 'lens cap, lens cover',
623: 'letter opener, paper knife, paperknife',
624: 'library',
625: 'lifeboat',
626: 'lighter, light, igniter, ignitor',
627: 'limousine, limo',
628: 'liner, ocean liner',
629: 'lipstick, lip rouge',
630: 'Loafer',
631: 'lotion',
632: 'loudspeaker, speaker, speaker unit, loudspeaker system, speaker system',
633: "loupe, jeweler's loupe",
634: 'lumbermill, sawmill',
635: 'magnetic compass',
636: 'mailbag, postbag',
637: 'mailbox, letter box',
638: 'maillot',
639: 'maillot, tank suit',
640: 'manhole cover',
641: 'maraca',
642: 'marimba, xylophone',
643: 'mask',
644: 'matchstick',
645: 'maypole',
646: 'maze, labyrinth',
647: 'measuring cup',
648: 'medicine chest, medicine cabinet',
649: 'megalith, megalithic structure',
650: 'microphone, mike',
651: 'microwave, microwave oven',
652: 'military uniform',
653: 'milk can',
654: 'minibus',
655: 'miniskirt, mini',
656: 'minivan',
657: 'missile',
658: 'mitten',
659: 'mixing bowl',
660: 'mobile home, manufactured home',
661: 'Model T',
662: 'modem',
663: 'monastery',
664: 'monitor',
665: 'moped',
666: 'mortar',
667: 'mortarboard',
668: 'mosque',
669: 'mosquito net',
670: 'motor scooter, scooter',
671: 'mountain bike, all-terrain bike, off-roader',
672: 'mountain tent',
673: 'mouse, computer mouse',
674: 'mousetrap',
675: 'moving van',
676: 'muzzle',
677: 'nail',
678: 'neck brace',
679: 'necklace',
680: 'nipple',
681: 'notebook, notebook computer',
682: 'obelisk',
683: 'oboe, hautboy, hautbois',
684: 'ocarina, sweet potato',
685: 'odometer, hodometer, mileometer, milometer',
686: 'oil filter',
687: 'organ, pipe organ',
688: 'oscilloscope, scope, cathode-ray oscilloscope, CRO',
689: 'overskirt',
690: 'oxcart',
691: 'oxygen mask',
692: 'packet',
693: 'paddle, boat paddle',
694: 'paddlewheel, paddle wheel',
695: 'padlock',
696: 'paintbrush',
697: "pajama, pyjama, pj's, jammies",
698: 'palace',
699: 'panpipe, pandean pipe, syrinx',
700: 'paper towel',
701: 'parachute, chute',
702: 'parallel bars, bars',
703: 'park bench',
704: 'parking meter',
705: 'passenger car, coach, carriage',
706: 'patio, terrace',
707: 'pay-phone, pay-station',
708: 'pedestal, plinth, footstall',
709: 'pencil box, pencil case',
710: 'pencil sharpener',
711: 'perfume, essence',
712: 'Petri dish',
713: 'photocopier',
714: 'pick, plectrum, plectron',
715: 'pickelhaube',
716: 'picket fence, paling',
717: 'pickup, pickup truck',
718: 'pier',
719: 'piggy bank, penny bank',
720: 'pill bottle',
721: 'pillow',
722: 'ping-pong ball',
723: 'pinwheel',
724: 'pirate, pirate ship',
725: 'pitcher, ewer',
726: "plane, carpenter's plane, woodworking plane",
727: 'planetarium',
728: 'plastic bag',
729: 'plate rack',
730: 'plow, plough',
731: "plunger, plumber's helper",
732: 'Polaroid camera, Polaroid Land camera',
733: 'pole',
734: 'police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria',
735: 'poncho',
736: 'pool table, billiard table, snooker table',
737: 'pop bottle, soda bottle',
738: 'pot, flowerpot',
739: "potter's wheel",
740: 'power drill',
741: 'prayer rug, prayer mat',
742: 'printer',
743: 'prison, prison house',
744: 'projectile, missile',
745: 'projector',
746: 'puck, hockey puck',
747: 'punching bag, punch bag, punching ball, punchball',
748: 'purse',
749: 'quill, quill pen',
750: 'quilt, comforter, comfort, puff',
751: 'racer, race car, racing car',
752: 'racket, racquet',
753: 'radiator',
754: 'radio, wireless',
755: 'radio telescope, radio reflector',
756: 'rain barrel',
757: 'recreational vehicle, RV, R.V.',
758: 'reel',
759: 'reflex camera',
760: 'refrigerator, icebox',
761: 'remote control, remote',
762: 'restaurant, eating house, eating place, eatery',
763: 'revolver, six-gun, six-shooter',
764: 'rifle',
765: 'rocking chair, rocker',
766: 'rotisserie',
767: 'rubber eraser, rubber, pencil eraser',
768: 'rugby ball',
769: 'rule, ruler',
770: 'running shoe',
771: 'safe',
772: 'safety pin',
773: 'saltshaker, salt shaker',
774: 'sandal',
775: 'sarong',
776: 'sax, saxophone',
777: 'scabbard',
778: 'scale, weighing machine',
779: 'school bus',
780: 'schooner',
781: 'scoreboard',
782: 'screen, CRT screen',
783: 'screw',
784: 'screwdriver',
785: 'seat belt, seatbelt',
786: 'sewing machine',
787: 'shield, buckler',
788: 'shoe shop, shoe-shop, shoe store',
789: 'shoji',
790: 'shopping basket',
791: 'shopping cart',
792: 'shovel',
793: 'shower cap',
794: 'shower curtain',
795: 'ski',
796: 'ski mask',
797: 'sleeping bag',
798: 'slide rule, slipstick',
799: 'sliding door',
800: 'slot, one-armed bandit',
801: 'snorkel',
802: 'snowmobile',
803: 'snowplow, snowplough',
804: 'soap dispenser',
805: 'soccer ball',
806: 'sock',
807: 'solar dish, solar collector, solar furnace',
808: 'sombrero',
809: 'soup bowl',
810: 'space bar',
811: 'space heater',
812: 'space shuttle',
813: 'spatula',
814: 'speedboat',
815: "spider web, spider's web",
816: 'spindle',
817: 'sports car, sport car',
818: 'spotlight, spot',
819: 'stage',
820: 'steam locomotive',
821: 'steel arch bridge',
822: 'steel drum',
823: 'stethoscope',
824: 'stole',
825: 'stone wall',
826: 'stopwatch, stop watch',
827: 'stove',
828: 'strainer',
829: 'streetcar, tram, tramcar, trolley, trolley car',
830: 'stretcher',
831: 'studio couch, day bed',
832: 'stupa, tope',
833: 'submarine, pigboat, sub, U-boat',
834: 'suit, suit of clothes',
835: 'sundial',
836: 'sunglass',
837: 'sunglasses, dark glasses, shades',
838: 'sunscreen, sunblock, sun blocker',
839: 'suspension bridge',
840: 'swab, swob, mop',
841: 'sweatshirt',
842: 'swimming trunks, bathing trunks',
843: 'swing',
844: 'switch, electric switch, electrical switch',
845: 'syringe',
846: 'table lamp',
847: 'tank, army tank, armored combat vehicle, armoured combat vehicle',
848: 'tape player',
849: 'teapot',
850: 'teddy, teddy bear',
851: 'television, television system',
852: 'tennis ball',
853: 'thatch, thatched roof',
854: 'theater curtain, theatre curtain',
855: 'thimble',
856: 'thresher, thrasher, threshing machine',
857: 'throne',
858: 'tile roof',
859: 'toaster',
860: 'tobacco shop, tobacconist shop, tobacconist',
861: 'toilet seat',
862: 'torch',
863: 'totem pole',
864: 'tow truck, tow car, wrecker',
865: 'toyshop',
866: 'tractor',
867: 'trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi',
868: 'tray',
869: 'trench coat',
870: 'tricycle, trike, velocipede',
871: 'trimaran',
872: 'tripod',
873: 'triumphal arch',
874: 'trolleybus, trolley coach, trackless trolley',
875: 'trombone',
876: 'tub, vat',
877: 'turnstile',
878: 'typewriter keyboard',
879: 'umbrella',
880: 'unicycle, monocycle',
881: 'upright, upright piano',
882: 'vacuum, vacuum cleaner',
883: 'vase',
884: 'vault',
885: 'velvet',
886: 'vending machine',
887: 'vestment',
888: 'viaduct',
889: 'violin, fiddle',
890: 'volleyball',
891: 'waffle iron',
892: 'wall clock',
893: 'wallet, billfold, notecase, pocketbook',
894: 'wardrobe, closet, press',
895: 'warplane, military plane',
896: 'washbasin, handbasin, washbowl, lavabo, wash-hand basin',
897: 'washer, automatic washer, washing machine',
898: 'water bottle',
899: 'water jug',
900: 'water tower',
901: 'whiskey jug',
902: 'whistle',
903: 'wig',
904: 'window screen',
905: 'window shade',
906: 'Windsor tie',
907: 'wine bottle',
908: 'wing',
909: 'wok',
910: 'wooden spoon',
911: 'wool, woolen, woollen',
912: 'worm fence, snake fence, snake-rail fence, Virginia fence',
913: 'wreck',
914: 'yawl',
915: 'yurt',
916: 'web site, website, internet site, site',
917: 'comic book',
918: 'crossword puzzle, crossword',
919: 'street sign',
920: 'traffic light, traffic signal, stoplight',
921: 'book jacket, dust cover, dust jacket, dust wrapper',
922: 'menu',
923: 'plate',
924: 'guacamole',
925: 'consomme',
926: 'hot pot, hotpot',
927: 'trifle',
928: 'ice cream, icecream',
929: 'ice lolly, lolly, lollipop, popsicle',
930: 'French loaf',
931: 'bagel, beigel',
932: 'pretzel',
933: 'cheeseburger',
934: 'hotdog, hot dog, red hot',
935: 'mashed potato',
936: 'head cabbage',
937: 'broccoli',
938: 'cauliflower',
939: 'zucchini, courgette',
940: 'spaghetti squash',
941: 'acorn squash',
942: 'butternut squash',
943: 'cucumber, cuke',
944: 'artichoke, globe artichoke',
945: 'bell pepper',
946: 'cardoon',
947: 'mushroom',
948: 'Granny Smith',
949: 'strawberry',
950: 'orange',
951: 'lemon',
952: 'fig',
953: 'pineapple, ananas',
954: 'banana',
955: 'jackfruit, jak, jack',
956: 'custard apple',
957: 'pomegranate',
958: 'hay',
959: 'carbonara',
960: 'chocolate sauce, chocolate syrup',
961: 'dough',
962: 'meat loaf, meatloaf',
963: 'pizza, pizza pie',
964: 'potpie',
965: 'burrito',
966: 'red wine',
967: 'espresso',
968: 'cup',
969: 'eggnog',
970: 'alp',
971: 'bubble',
972: 'cliff, drop, drop-off',
973: 'coral reef',
974: 'geyser',
975: 'lakeside, lakeshore',
976: 'promontory, headland, head, foreland',
977: 'sandbar, sand bar',
978: 'seashore, coast, seacoast, sea-coast',
979: 'valley, vale',
980: 'volcano',
981: 'ballplayer, baseball player',
982: 'groom, bridegroom',
983: 'scuba diver',
984: 'rapeseed',
985: 'daisy',
986: "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum",
987: 'corn',
988: 'acorn',
989: 'hip, rose hip, rosehip',
990: 'buckeye, horse chestnut, conker',
991: 'coral fungus',
992: 'agaric',
993: 'gyromitra',
994: 'stinkhorn, carrion fungus',
995: 'earthstar',
996: 'hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa',
997: 'bolete',
998: 'ear, spike, capitulum',
999: 'toilet tissue, toilet paper, bathroom tissue'}
test/data/model.test.batchnorm.json 0 → 100644
浏览文件 @ 6c40834f
因为 它太大了无法显示 source diff 。你可以改为 查看blob。
test/data/model.test.concat.json 0 → 100644
浏览文件 @ 6c40834f
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test/data/model.test.conv2d.json 0 → 100644
浏览文件 @ 6c40834f
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test/data/model.test.depthwise_conv2d.json 0 → 100644
浏览文件 @ 6c40834f
因为 它太大了无法显示 source diff 。你可以改为 查看blob。
test/data/model.test.elementwise_add.json 0 → 100644
浏览文件 @ 6c40834f
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3.290370225906372,
-0.8352606296539307,
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4.816962242126465,
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-4.548575401306152,
-2.211716890335083,
2.8640294075012207,
0.07712188363075256
],
"name": "fc_0.tmp_1",
"shape": [
1000
]
},
]
}
test/data/model.test.json 0 → 100644
浏览文件 @ 6c40834f
因为 它太大了无法显示 source diff 。你可以改为 查看blob。
test/data/model.test.mul.json 0 → 100644
浏览文件 @ 6c40834f
因为 它太大了无法显示 source diff 。你可以改为 查看blob。
test/data/model.test.pool2d.json 0 → 100644
浏览文件 @ 6c40834f
因为 它太大了无法显示 source diff 。你可以改为 查看blob。
test/data/model.test.relu.json 0 → 100644
浏览文件 @ 6c40834f
因为 它太大了无法显示 source diff 。你可以改为 查看blob。
test/data/model.test.scale.json 0 → 100644
浏览文件 @ 6c40834f
{
"ops": [
{
"attrs": {
"bias": 0.0,
"bias_after_scale": true,
"scale": 1.0
},
"inputs": {
"X": [
"fc_0.tmp_2"
]
},
"outputs": {
"Out": [
"scale_0.tmp_0"
]
},
"type": "scale"
}
],
"vars": [
{
"data": [
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.0,
1.6504194778766687e-16
],
"name": "fc_0.tmp_2",
"persistable": 0,
"shape": [
10
]
},
{
"data": [
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.0,
1.6504194778766687e-16
],
"name": "scale_0.tmp_0",
"persistable": 0,
"shape": [
10
]
}
]
}
test/data/model.test.softmax.json 0 → 100644
浏览文件 @ 6c40834f
{
"ops": [
{
"attrs": {
"bias": 0.0,
"bias_after_scale": true,
"scale": 1.0
},
"inputs": {
"X": [
"fc_0.tmp_2"
]
},
"outputs": {
"Out": [
"scale_0.tmp_0"
]
},
"type": "scale"
}
],
"vars": [
{
"data": [
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.0,
1.6504194778766687e-16
],
"name": "fc_0.tmp_2",
"persistable": 0,
"shape": [
10
]
},
{
"data": [
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.6038109389511792e-28,
1.0,
1.6504194778766687e-16
],
"name": "scale_0.tmp_0",
"persistable": 0,
"shape": [
10
]
}
]
}
test/data/model.test.split.json 0 → 100644
浏览文件 @ 6c40834f
{
"ops": [
{
"attrs": {
"axis": 2,
"num": 2,
"sections": []
},
"inputs": {
"X": ["reshape2_3.tmp_0"]
},
"outputs": {
"Out": ["split_1.tmp_0", "split_1.tmp_1"]
},
"type": "split"
}
],
"vars": [
{
"data": [
1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18,
19, 20, 21, 22, 23, 24
],
"name": "reshape2_3.tmp_0",
"shape": [2, 2, 2, 3]
},
{
"data": [1, 2, 3, 7, 8, 9, 13, 14, 15, 16, 17, 18],
"name": "split_1.tmp_0",
"shape": [2, 2, 1, 3]
},
{
"data": [4, 5, 6, 10, 11, 12, 16, 17, 18, 22, 23, 24],
"name": "split_1.tmp_1",
"shape": [2, 2, 1, 3]
}
]
}
test/testUtils/testUtils.es6
浏览文件 @ 6c40834f
import 'babel-polyfill'; import 'babel-polyfill';
import Paddle from '../../src/paddle/paddle'; import Paddle from '../../src/paddle/paddle';
import Utils from '../../src/utils/utils';
const unitPath = { const unitPath = {
'conv2d': 'model.test.conv2d.json', 'conv2d': 'model.test.conv2d.json',
...@@ -9,16 +10,24 @@ const unitPath = { ...@@ -9,16 +10,24 @@ const unitPath = {
'relu': 'model.test.relu.json', 'relu': 'model.test.relu.json',
'scale': 'model.test.scale.json', 'scale': 'model.test.scale.json',
'softmax': 'model.test.softmax.json', 'softmax': 'model.test.softmax.json',
'relu6' : 'model.test.relu6.json' 'relu6' : 'model.test.relu6.json',
'elementwise' : 'model.test.elementwise_add.json',
'depthwise' : 'model.test.depthwise_conv2d.json',
'reshape' : 'model.test.reshape.json',
'bilinear_interp' : 'model.test.bilinear_interp.json',
'transpose' : 'model.test.transpose.json',
'conv2d_transpose': 'model.test.conv2d_transpose.json',
'elementwise_add': 'model.test.elementwise_add.json',
'concat': 'model.test.concat.json',
'split': 'model.test.split.json'
}; };
// 制定运行的 op // 制定运行的 op
const modelType = 'softmax'; const modelType = 'split';
// 制定运行的 op
const unitData = unitPath[modelType]; const unitData = unitPath[modelType];
let Diff = require('./diff');
let datas; let datas;
let otherResult; let output;
let output
async function run() { async function run() {
const path = 'test/unitData'; const path = 'test/unitData';
const MODEL_CONFIG = { const MODEL_CONFIG = {
...@@ -35,8 +44,9 @@ async function run() { ...@@ -35,8 +44,9 @@ async function run() {
let model = await paddle.load(); let model = await paddle.load();
datas = model.graph.data; datas = model.graph.data;
output = deepCopy(datas); output = deepCopy(datas);
// 测试单元
model.graph.weightMap.forEach(op => { model.graph.weightMap.forEach(op => {
const type = op.type; const type = op.type;
if (type !== 'feed' && type !== 'fetch') { if (type !== 'feed' && type !== 'fetch') {
...@@ -45,18 +55,22 @@ async function run() { ...@@ -45,18 +55,22 @@ async function run() {
} }
}); });
const executor = model.graph.weightMap; const executor = model.graph.weightMap;
let inst = model.graph.execute_(executor[0]); model.graph.execute_(executor[0]);
let result = model.graph.inst.read(); // NHWC输出
console.dir(['result', result]); let result = await model.graph.inst.read();
var one = model.graph.inst.read();
// var other = getResult('conv2d');
console.log('one'); // 获取 NHWC -> NCHW 的 输出
console.log(one); const outputNCHWShape = getOutputShape();
console.log('other'); const outputNHWCShape = nchwShape2nhwcShape(outputNCHWShape);
} let nchwResult = Utils.nhwc2nchw(result, outputNHWCShape);
console.log('result');
console.log(result);
console.log('NCHW RESULT');
console.log(nchwResult);
}
run(); run();
...@@ -64,90 +78,44 @@ function deepCopy (data) { ...@@ -64,90 +78,44 @@ function deepCopy (data) {
return JSON.parse(JSON.stringify(data)); return JSON.parse(JSON.stringify(data));
} }
// let output = deepCopy(datas);
let getTensor = function(id, times = 1) {
let find = 0;
let data = datas.ops.filter((item, idx) => {
if (id === item.type) {
++find;
if (find === times) {
return true;
}
}
});
return getInputs(data[0]);
};
let getInputs = function(data) {
Object.keys(data.inputs).forEach(function(key){
data.inputs[key] = getValue(data.inputs[key][0], datas);
});
Object.keys(data.outputs).forEach(function(key){
let out = getValue(data.outputs[key][0], datas)
data.outputs[key] = out;
otherResult = out[0].data;
});
return data;
};
let getResult = function(id) {
let data = output.ops.filter((item, idx) => {
if (id === item.type) {
return true; const getResult = function (id) {
} const data = output.ops.filter(item => id === item.type);
});
return getoutputs(data[0]); return getoutputs(data[0]);
}; };
let getoutputs = function(data) {
let otherResult;
Object.keys(data.outputs).forEach(function(key){
let out = getValue(data.outputs[key][0], output);
otherResult = out[0].data;
});
return otherResult;
};
let getValue = function(name, datas) { const getValue = function(name, datas) {
return datas.vars.filter((item, idx) => { return datas.vars.find(item => name === item.name);
if (name === item.name) {
return item;
}
});
}; };
// // 测试单元
// let item = getTensor('conv2d');
let func = function (model) {
// console.log(other);
// var one = inst.read();
// var other = getResult('softmax');
// var color ='';
// var span = null;
// var diff = Diff.diffChars(one.toString(), other.toString()),
// display = document.getElementById('display'),
// fragment = document.createDocumentFragment();
//
// diff.forEach(function(part){
// // green for additions, red for deletions
// // grey for common parts
// color = part.added ? 'green' :
// part.removed ? 'red' : 'grey';
// span = document.createElement('span');
// span.style.color = color;
// span.appendChild(document
// .createTextNode(part.value));
// fragment.appendChild(span);
// });
//
// display.appendChild(fragment);
const OUTPUT_KEYS = ['out', 'y', 'output'];
const getoutputs = function (data) {
const outputkey = Object.keys(data.outputs).find(key => OUTPUT_KEYS.includes(key.toLowerCase()));
const outputTensorId = data.outputs[outputkey].slice(-1)[0];
const outputTensor = getValue(outputTensorId, output);
return outputTensor;
}; };
function getOutputShape () {
var outputTensor = getResult(modelType);
return outputTensor.shape;
}
// NCHW shape 2 NHWC shape
function nchwShape2nhwcShape(nchw) {
let batchNCHW = nchw;
if (nchw.length < 4) {
let batch = [];
for (let i = 0; i < (4 - nchw.length); i++) {
batch.push(1);
}
batchNCHW = batch.concat(nchw);
}
const N = batchNCHW[0];
const C = batchNCHW[1];
const H = batchNCHW[2];
const W = batchNCHW[3];
return [N, H, W, C];
}
tools/logger.es6 0 → 100644
浏览文件 @ 6c40834f
/**
* file tools/logger logger工具
* author saniac(snailsword@gmail.com)
*/
export default class Logger {
constructor() {
this.timeTable = {};
this.countTable = {};
this.duringTable = {};
this.lastStopTable = {};
}
start(key) {
let arr = this.timeTable[key];
if (!arr) {
arr = [{}];
}
else {
if (!arr[arr.length - 1].endTime) {
console.error('[logger] key:' + key + ' duplicate start logger');
return;
}
arr.push({});
}
arr[arr.length - 1].startTime = this.time;
this.timeTable[key] = arr;
return this;
}
end(key) {
// console.log(this.timeTable[key]);
if (!this.timeTable[key]) {
console.log(this.timeTable[key]);
console.error('[logger] key:' + key + ' no matching start logger');
return;
}
let currentObj = this.timeTable[key][this.timeTable[key].length - 1];
if (currentObj.endTime) {
console.error('[logger] key:' + key + ' duplicate end logger');
return;
}
currentObj.endTime = this.time;
currentObj.during = currentObj.endTime - currentObj.startTime;
return this;
}
// 数次数
count(key) {
if (this.countTable[key]) {
this.countTable[key]++;
}
else {
this.countTable[key] = 1;
}
return this;
}
// 看每次执行的时间间隔
during(key) {
if (this.lastStopTable[key]) {
this.duringTable[key].push(this.time - this.lastStopTable[key]);
this.lastStopTable[key] = this.time;
}
else {
this.lastStopTable[key] = this.time;
this.duringTable[key] = [];
}
return this;
}
get time() {
return +new Date().getTime();
}
get statistics() {
// time
let timeResult = [];
let item;
for (let key in this.timeTable) {
item = this.timeTable[key];
let len = item.length;
let max = 0;
let min = Number.MAX_VALUE;
let sum = 0;
for (let i = 0; i < len; i++) {
max = Math.max(max, item[i].during);
min = Math.min(min, item[i].during);
sum += item[i].during;
}
timeResult.push({
name: key,
length: len,
avg: sum / len,
max,
min
});
}
console.table(timeResult);
return {timeResult};
}
}
tools/toWebModel.py 0 → 100644
浏览文件 @ 6c40834f
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
import json
import paddle.fluid as fluid
import paddle
import numpy as np
import collections
import math
import sys as sys
import os
import struct
#常量控制
#抽样打印数据数量
logDataCount = 50
# 输入模型所在目录
modelDir = "humanseg/"
# 输入模型名
modelName = "model"
# 输入参数名，当且仅当所有模型参数被保存在一个单独的二进制文件中，它才需要被指定，若为分片模型，请设置为None
paramsName = None
# 模型feed shape
inputShape = (1, 3, 192, 192)
# 输入数据
inputData = np.full(inputShape, 1, "float32")
# 输出模型目录
outputDir = "../dist/model/humanseg/"
# 权重分片扩展名
extensionName = ".dat"
# 输出各var数据
outputVarData = False
# 确认fluid的版本号
print(paddle.__version__)
# 采样输出list数据，采样的个数logDataCount为常量
def stridePrint1(data):
dataCount = len(data)
stride = math.floor(dataCount / logDataCount)
if stride == 0:
stride = 1
nums = []
# outputCount = logDataCount
# if dataCount < logDataCount:
# outputCount = dataCount
# for i in range(outputCount):
# # nums.append(str(i) + ": " + str(data[i]))
# nums.append(data[i])
for i in range(0, logDataCount):
item = data[i * stride]
nums.append(str(i * stride) + ": " + str(item))
print(nums)
def stridePrint(tensor):
length = len(tensor)
# if length < 3000:
# print(tensor)
# return
size = 20
stride = math.floor(length / size)
if stride == 0:
stride = 1
size = math.floor(length / stride)
nums = []
for i in range(0, size):
item = tensor[i * stride]
nums.append(str(i * stride) + ": " + str(item))
print(nums)
# 对字典进行排序，返回有序字典，默认升序
def sortDict(oldDict, reverse = False):
# 获得排序后的key list
keys = sorted(oldDict.keys(), reverse = reverse)
orderDict = collections.OrderedDict()
# 遍历 key 列表
for key in keys:
orderDict[key] = oldDict[key]
return orderDict
# 将权重数据分片输出到文件，默认分片策略为按4M分片
def sliceDataToBinaryFile(weightValueList, sliceMethod = 0):
# TODO: 分片这里不太对，待修改
totalWeightCount = len(weightValueList)
countPerSlice = 0
# sliceCount = 0
if sliceMethod == 0:
# 分片策略 0:按4M分片
countPerSlice = int(4 * 1024 * 1024 / 4)
# sliceCount = math.ceil(totalWeightCount / countPerSlice)
else:
# 分片策略 1:按<=4M等分
# TODO: 待实现
countPerSlice = 0
# sliceCount = 0
if not os.path.exists(outputDir):
os.makedirs(outputDir)
currentChunkIndex = 0
currentWeightIndex = 0
while currentWeightIndex < totalWeightCount - 1:
remainCount = totalWeightCount - currentWeightIndex
if remainCount < countPerSlice:
countPerSlice = remainCount
chunkPath = outputDir + 'chunk_%s' % (currentChunkIndex + 1) + extensionName
file = open(chunkPath, 'wb')
for i in weightValueList[currentWeightIndex : currentWeightIndex + countPerSlice]:
byte = struct.pack('f', float(i))
file.write(byte)
file.close()
currentWeightIndex = currentWeightIndex + countPerSlice
currentChunkIndex = currentChunkIndex + 1
# for debug
print("第" + str(currentChunkIndex + 1) + "片权重输出完毕，输出个数：" + str(countPerSlice) + " 剩余个数:" + str(totalWeightCount - currentWeightIndex))
# for debug
print("========权重输出完毕，共" + str(currentWeightIndex) + "个数据，" + str(currentChunkIndex) + "个分片文件" + "========")
# 处理fluid的OP type与PaddleJS的OP type不对应情况
def mapToPaddleJSTypeName(fluidOPName):
if fluidOPName == "batch_norm":
return "batchnorm"
return fluidOPName
# 将shape扩充为4维
def padToFourDimShape(shape):
fourDimShape = []
if len(shape) == 4:
fourDimShape = shape
elif len(shape) < 4:
for i in range(0, 4 - len(shape)):
fourDimShape.append(1)
fourDimShape = fourDimShape + shape
else:
return []
return fourDimShape
# for debug，将NCHW排布的数据转为NHWC排布的数据
def convertNCHW2NHWC(data, shape):
fourDimShape = padToFourDimShape(shape)
N = fourDimShape[0]
C = fourDimShape[1]
H = fourDimShape[2]
W = fourDimShape[3]
print(fourDimShape)
HXW = H * W
CXHXW = C * H * W
index = 0
nhwcData = []
for n in range(0, N):
for h in range(0, H):
for w in range(0, W):
for c in range(0, C):
nhwcData.append(data[n * CXHXW + c * HXW + h * W + w])
index = index + 1
return nhwcData
# for debug 输出特定varName对应的数据
def writeTempOutputData(name):
# FIXME:待完善
return
dataList = np.array(fluid.global_scope().find_var(name).get_tensor()).flatten().tolist()
path = '/Users/bluebird/baidu/fluid_tools/check-temp/filter.txt'
if os.path.exists(path):
os.remove()
file = open(path,'a')
for a in range(0, len(dataList)):
file.write(str(dataList[a]))
file.write(",")
file.close()
def convertToPaddleJSModel():
# 1. 初始化fluid运行环境和配置
exe = fluid.Executor(fluid.CPUPlace())
[prog, feed_target_names, fetch_targets] = fluid.io.load_inference_model(dirname=modelDir, executor=exe, model_filename=modelName, params_filename=paramsName)
out = exe.run(prog, feed={feed_target_names[0]: inputData}, fetch_list=fetch_targets, return_numpy=False)
print(out)
index = 0
# 存放模型结构
modelInfo = {"vars": [], "ops": []}
# 存放var信息（未排序）
varInfoDict = {}
# 存放权重数值（未排序）
weightValueDict = {}
# 2. 获取program中所有的var，遍历并获取所有未排序的var信息和权重数值
vars = list(prog.list_vars())
for v in vars:
# 跳过feed和fetch
if "feed" == v.name:
continue
if "fetch" == v.name:
continue
print("Var index:" + str(index) + " name:" + v.name)
print(v)
index += 1
varShape = list(v.shape)
# FIXME:start paddlejs 不支持shape中为-1，这里需要手动过滤一下，支持了以后可以删除
varShapeExcludeNegativeOne = []
for s in varShape:
if s == -1:
continue
varShapeExcludeNegativeOne.append(s)
varShape = varShapeExcludeNegativeOne
# FIXME:end
# 存放variable信息，在dump成json时排序
varInfo = {}
varInfo["shape"] = varShape
# 数据是否是持久化数据，如weight为持久化数据，op的output不是持久化数据
# 只输出持久化数据，paddlejs中也仅读取持久化数据
varInfo["persistable"] = v.persistable
varInfoDict[v.name] = varInfo
# for debug，输出var变量
if outputVarData:
writeTempOutputData(v.name)
# persistable数据存入weightDict，等待排序
if v.persistable:
data = np.array(fluid.global_scope().find_var(v.name).get_tensor()).flatten().tolist()
weightValueDict[v.name] = data
# 3. 对var信息dict，按照key（var名）进行字母顺序排序
varInfoOrderDict = sortDict(varInfoDict)
# 4. 将var信息按照顺序，添加到model info的vars中
for key, value in varInfoOrderDict.items():
value["name"] = key
modelInfo["vars"].append(value)
# 5. 对权重数值dict，按照key（权重名）进行字母顺序排序，并组合到一起
weightValueOrderDict = sortDict(weightValueDict)
weightValues = []
for key, value in weightValueOrderDict.items():
weightValues += value
# 6. 分片输出权重
sliceDataToBinaryFile(weightValues)
# 7. 获取program中所有的op，按op顺序加入到model info
ops = prog.current_block().ops
feedOutputName = None
for op in ops:
opInfo = {}
# 获取OP type，需要映射到PaddleJS的名字
opInfo["type"] = mapToPaddleJSTypeName(op.type)
# 获取OP input
inputs = {}
for name in op.input_names:
value = op.input(name)
if len(value) <= 0:
continue
if value[0] == feedOutputName:
# FIXME:workaround,PaddleJSfeed 输入必须是image，且为单输入
# 这里修改feed后面的OP的input为image，建立前后关联
# 这里可能会有问题
inputs[name] = ["image"]
else:
inputs[name] = value
opInfo["inputs"] = inputs
# 获取OP output
outputs = {}
for name in op.output_names:
value = op.output(name)
if len(value) <= 0:
continue
if op.type == "feed":
# FIXME:workaround,PaddleJSfeed 输入必须是image，且为单输入
# 这里可能会有问题
feedOutputName = value[0]
outputs[name] = ["image"]
else:
outputs[name] = value
opInfo["outputs"] = outputs
# 获取OP attribute
attrs = {}
for name in op.attr_names:
# 过滤不需要的参数
if name in ["op_callstack", 'col', 'op_role', 'op_namescope', 'op_role_var']:
continue
value = op.attr(name)
attrs[name] = value
opInfo["attrs"] = attrs
# 存入modelInfo
modelInfo["ops"].append(opInfo)
# 8. 模型信息按照key字母顺序导出到json
outputModelPath = outputDir + "model.json"
with open(outputModelPath, 'w') as outputFile:
json.dump(modelInfo, outputFile, indent = 4, separators=(", ", ": "), sort_keys = True)
print("========模型结构输出完毕========")
convertToPaddleJSModel()
webpack.config.js 0 → 100644
浏览文件 @ 6c40834f
/**
* @file 打包到rd机器的配置
*/
const path = require('path');
const ExtractTextPlugin = require('extract-text-webpack-plugin');
const extractLess = new ExtractTextPlugin({
filename: '[name].css'
});
module.exports = {
// mode: 'development',
mode: 'production',
devtool: 'none',
optimization: {
minimize: true
},
entry: {
index: ['./src/executor/runner']
},
output: {
filename: '../graphfe/dep/paddleweb/index.min.js',
path: path.resolve(__dirname, './'),
library: 'panorama',
libraryTarget: 'umd',
libraryExport: 'default'
},
module: {
rules: [{
test: /\.(es6|js)$/,
exclude: /node_modules/,
use: {
loader: 'babel-loader',
options: {
presets: ['@babel/preset-env'],
plugins: ['@babel/transform-runtime']
}
}
}, {
test: /\.(eot|woff|woff2|ttf|svg|png|jpg)$/,
loader: 'url-loader?limit=30000&name=[name].[ext]'
}, {
test: /\.less$/,
exclude: /node_modules/,
loader: ExtractTextPlugin.extract([
{loader: 'css-loader', options: {minimize: true}},
{loader: 'less-loader'}
])
}]
},
plugins: [extractLess],
resolve: {
extensions: ['.es6', '.js', '.json']
}
};
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