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basic demo added #67

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basic demo added #67

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2a9983a
basic demo added
May 30, 2016
fdec44c
gulp integration
May 30, 2016
a6e1f2b
copy build folder automatically
May 30, 2016
14807d8
serve task added
May 31, 2016
8f96e60
CodeMirror lib added
May 31, 2016
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3 changes: 3 additions & 0 deletions .bowerrc
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Original file line number Diff line number Diff line change
@@ -0,0 +1,3 @@
{
"directory" : "demo/bower_components"
}
45 changes: 45 additions & 0 deletions Gulpfile.js
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var gulp = require('gulp');
var jshint = require('gulp-jshint');
var browserSync = require('browser-sync');
const reload = browserSync.reload;
gulp.task('copy', () =>
gulp.src([
'build/**/*'
], {
base: './'
}).pipe(gulp.dest('demo'))
);
// jshint files
gulp.task('jshint', function () {
//gulp.src(['test/**/*.js'])
// .pipe(jshint())
// .pipe(jshint.reporter());
});
// start local http server for development
gulp.task('http-server', function () {
browserSync({
notify: false,
// Customize the Browsersync console logging prefix
logPrefix: 'WSK',
// Allow scroll syncing across breakpoints
scrollElementMapping: ['main', '.mdl-layout'],
// Run as an https by uncommenting 'https: true'
// Note: this uses an unsigned certificate which on first access
// will present a certificate warning in the browser.
// https: true,
server: ['.tmp', 'demo'],
port: 3000
});
gulp.watch(['demo/**/*'], reload);
});
// start local http server with watch and livereload set up
gulp.task('server', function () {
gulp.run('http-server');
});
gulp.task('default', function () {
gulp.run('jshint', 'copy', 'server');
});
gulp.task('serve', function () {
gulp.run('default');
});

5 changes: 4 additions & 1 deletion bower.json
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Expand Up @@ -27,5 +27,8 @@
"bower_components",
"test",
"tests"
]
],
"dependencies": {
"codemirror": "^5.15.2"
}
}
29 changes: 29 additions & 0 deletions demo/index.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title></title>
</head>
<body>
<div id="egdiv"></div>
<script src="build/convnet.js"></script>
<script>var layer_defs = [];
layer_defs.push({type: 'input', out_sx: 1, out_sy: 1, out_depth: 2});
layer_defs.push({type: 'fc', num_neurons: 5, activation: 'sigmoid'});
layer_defs.push({type: 'regression', num_neurons: 1});
var net = new convnetjs.Net();
net.makeLayers(layer_defs);
var x = new convnetjs.Vol([0.5, -1.3]);
// train on this datapoint, saying [0.5, -1.3] should map to value 0.7:
// note that in this case we are passing it a list, because in general
// we may want to  regress multiple outputs and in this special case we
// used num_neurons:1 for the regression to only regress one.
var trainer = new convnetjs.SGDTrainer(net,
{learning_rate: 0.01, momentum: 0.0, batch_size: 1, l2_decay: 0.001});
trainer.train(x, [0.7]);
// evaluate on a datapoint. We will get a 1x1x1 Vol back, so we get the
// actual output by looking into its 'w' field:
var predicted_values = net.forward(x);
console.log('predicted value: ' + predicted_values.w[0]);</script>
</body>
</html>
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