Refactor the AI into a web worker, but it's untested.

This commit is contained in:
Starbeamrainbowlabs 2019-07-25 16:44:26 +01:00
parent edb6362688
commit 4708fdbd6e
7 changed files with 251 additions and 51 deletions

View file

@ -10,8 +10,8 @@ export default {
// The border around gateways that we should consult the AI on.
border: {
lat: 0.05,
lng: 0.1
lat: 0.1,
lng: 0.2
},
// The resolution of the coverage map

View file

@ -1,19 +1,20 @@
"use strict";
import path from 'path';
import L from 'leaflet';
import {
loadLayersModel as tf_loadLayersModel,
tensor as tf_tensor
} from '@tensorflow/tfjs';
import chroma from 'chroma-js';
import GetFromUrl from './Helpers/GetFromUrl.mjs';
import Config from './ClientConfig.mjs';
import { normalise } from '../../common/Math.mjs';
import AIWorker from './Worker/AI.worker.mjs';
class LayerAI {
/**
* Computes a bounding box that exactly encompasses all the gateways in
* the index.
* @return {{north:number,south:number,east:number,west:number}} The computed bounding box
*/
get gateway_bounds() {
let result = {
east: Infinity,
@ -31,30 +32,107 @@ class LayerAI {
return result;
}
/**
* Initialises a new Leaflet AI layer instance.
* @param {[type]} map [description]
*/
constructor(map) {
this.map = map;
this.gateways = new Map();
this.worker = new AIWorker();
this.map_bounds = null;
}
/**
* Sets up the Web Worker that does the TensorFlow prediction.
* Using a web worker avoids hanging the main thread.
* @return {Promise} A Promise that resolves when setup is complete.
*/
worker_setup() {
// Arrow functions inherit the parent scope, including the "this"
// special variable.
return new Promise((resolve, reject) => {
// Attach the listener first
this.worker.addEventListener("message", (event) => {
if(event.data.event !== "setup-complete") {
reject(`Error: AIWorker responded with event ${event.data.event}, but 'setup-complete' was expected.`, event.data);
return;
}
resolve();
}, { once: true });
// Ask the web worker to set itself up
this.worker.postMessage({
event: "setup",
bounds: this.gateway_bounds,
index: this.index
});
})
}
/**
* Uses the Web Worker to predict a row of signal strength values.
* @param {number} latitude The latitude for which predictions should be made.
* @return {Promise<number[]>} A Promise returning the array of predictions calculated by the web worker.
*/
worker_predict_row(latitude) {
return new Promise((resolve, reject) => {
// Attach the event listener....
this.worker.addEventListener("message", (event) => {
if(event.data.event !== "result") {
reject(`Error: AIWorker responded with event ${event.data.event}, but 'result' was expected.`, event.data);
return;
}
resolve(event.data);
}, { once: true });
// ....and send the request
this.worker.postMessage({
event: "predict-row",
latitude
});
});
}
/**
* Sets up the Leaflet AI visualisation layer.
* @return {Promise} A promise that resolves when setup is complete.
*/
async setup() {
// Download the index file that tells us where the gateways and their
// trained models are located
this.index = JSON.parse(
await GetFromUrl(Config.ai_index_file)
);
console.log(this.index);
for(let gateway of this.index.index) {
this.gateways.set(
gateway.id,
await tf_loadLayersModel(`${window.location.href}/${path.dirname(Config.ai_index_file)}/${gateway.id}/model.json`)
);
}
// Figure out the bounds of the map we're going to generate
this.map_bounds = this.gateway_bounds;
map_bounds.north += Config.border.lat;
map_bounds.south -= Config.border.lat;
this.layer = this.generate_layer();
map_bounds.east += Config.border.lng;
map_bounds.west -= Config.border.lng;
// Setup the web worker
await this.worker_setup();
// Generate the Leaflet layer
this.layer = await this.generate_layer();
this.layer.addTo(this.map);
console.log("[Layer/AI] Complete");
}
generate_layer() {
/**
* Generates and returns the Leaflet layer containing the AI-predicted
* values.
* @return {Promise} A Promise that resolves to the generated Leaflet layer.
*/
async generate_layer() {
console.log("[Layer/AI] Rendering map");
let map = this.render_map();
console.log("[Layer/AI] Passing to Leaflet");
@ -70,15 +148,12 @@ class LayerAI {
});
}
render_map() {
// FUTURE: Do this in a web worker?
let map_bounds = this.gateway_bounds;
map_bounds.north += Config.border.lat;
map_bounds.south -= Config.border.lat;
map_bounds.east += Config.border.lng;
map_bounds.west -= Config.border.lng;
/**
* Uses a Web Worker and pre-trained AIs to generate a GeoJSON map of
* signal strength for a bounding box around the known gateways.
* @return {Promise} A Promise that resolves to a GeoJSON array representing the map.
*/
async render_map() {
let coverage = [],
colour_scale = chroma.scale([
Config.colour_scale.min,
@ -88,28 +163,24 @@ class LayerAI {
this.index.properties.rssi_max
);
for(let lat = map_bounds.south; lat < map_bounds.north; lat += Config.step.lat) {
for(let lng = map_bounds.west; lng < map_bounds.east; lng += Config.step.lng) {
let max_predicted_rssi = -Infinity;
for(let [, ai] of this.gateways) {
let next_prediction = ai.predict(
tf_tensor([ lat, lng ], [1, 2])
);
max_predicted_rssi = Math.max(
max_predicted_rssi,
next_prediction.arraySync()[0][0]
);
}
max_predicted_rssi = normalise(max_predicted_rssi,
{ min: 0, max: 1 },
{
min: this.index.properties.rssi_min,
max: this.index.properties.rssi_max
}
);
let stats = {
rssi_min: Infinity,
rssi_max: -Infinity
};
for(let lat = this.map_bounds.south; lat < this.map_bounds.north; lat += Config.step.lat) {
let next_row = await worker_predict_row(lat);
let lng = this.map_bounds.west;
for(let value of next_row) {
// Keep up with the statistics
if(value > stats.rssi_max)
stats.rssi_max = value;
if(value < stats.rssi_min)
stats.rssi_min = value;
// Generate the GeoJSON feature for this cell of the map
coverage.push({
type: "Feature",
geometry: {
@ -125,12 +196,16 @@ class LayerAI {
]
},
properties: {
colour: colour_scale(max_predicted_rssi).toString()
colour: colour_scale(value).toString()
}
})
});
lng += Config.step.lng;
}
}
console.log(stats);
return coverage;
}
}

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@ -0,0 +1,26 @@
export default function(self) {
let ai_wrapper = new AIWrapper();
self.addEventListener("message", async (event) => {
console.log(event.data);
switch(event.data.event) {
case "setup":
await ai_wrapper.setup(event.data.setup_info);
self.postMessage({
"event": "setup-complete"
});
break;
case "predict-row":
let message = await ai_wrapper.predict_row(event.data.latitude);
message.event = "result";
self.postMessage(message);
break;
case "end":
self.close();
break;
}
});
}

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@ -0,0 +1,84 @@
"use strict";
import path from 'path';
import {
loadLayersModel as tf_loadLayersModel,
tensor as tf_tensor
} from '@tensorflow/tfjs';
import { normalise } from '../../common/Math.mjs';
import Config from '../ClientConfig.mjs';
class AIWrapper {
constructor() {
this.setup_complete = false;
this.map_bounds = null;
this.index = null;
this.gateways = new Map();
}
async setup({ bounds, index }) {
this.map_bounds = bounds;
this.index = index;
for(let gateway of this.index.index) {
this.gateways.set(
gateway.id,
await tf_loadLayersModel(`${window.location.href}/${path.dirname(Config.ai_index_file)}/${gateway.id}/model.json`)
);
}
this.setup_complete = true;
}
predict_row(lat) {
if(!setup_complete)
throw new Error("Error: Can't do predictions until the setup is complete.");
let results = [],
stats = {
rssi_min: Infinity,
rssi_max: -Infinity
};
for(let lng = this.map_bounds.west; lng < this.map_bounds.east; lng += Config.step.lng) {
let max_predicted_rssi = -Infinity;
for(let [, ai] of this.gateways) {
let next_prediction = this.predict_value(lat, lng)
max_predicted_rssi = Math.max(
max_predicted_rssi,
next_prediction
);
}
max_predicted_rssi = normalise(max_predicted_rssi,
{ min: 0, max: 1 },
{
min: this.index.properties.rssi_min,
max: this.index.properties.rssi_max
}
);
if(max_predicted_rssi > stats.rssi_max)
stats.rssi_max = max_predicted_rssi;
if(max_predicted_rssi < stats.rssi_min)
stats.rssi_min = max_predicted_rssi;
result.push(max_predicted_rssi);
}
return { result, stats };
}
predict_value(latitude, longitude) {
return ai.predict(
tf_tensor([ latitude, longitude ], [1, 2])
).arraySync()[0][0];
}
}
export default AIWrapper;

9
package-lock.json generated
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@ -3892,6 +3892,15 @@
"terser": "^4.1.0"
}
},
"rollup-plugin-webworkify": {
"version": "0.0.4",
"resolved": "https://registry.npmjs.org/rollup-plugin-webworkify/-/rollup-plugin-webworkify-0.0.4.tgz",
"integrity": "sha512-GvDPdz7qeakeB26cinVpxPgOBWHx/p3xua/itRXZ/30gGOK5QZeb/iu/9V4M7Zuhwmo2UPR1rViVX8OCqmhi1g==",
"dev": true,
"requires": {
"rollup-pluginutils": "^2"
}
},
"rollup-pluginutils": {
"version": "2.8.1",
"resolved": "https://registry.npmjs.org/rollup-pluginutils/-/rollup-pluginutils-2.8.1.tgz",

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@ -43,6 +43,7 @@
"rollup-plugin-commonjs": "^10.0.1",
"rollup-plugin-node-resolve": "^5.2.0",
"rollup-plugin-postcss": "^2.0.3",
"rollup-plugin-replace": "^2.2.0"
"rollup-plugin-replace": "^2.2.0",
"rollup-plugin-webworkify": "0.0.4"
}
}

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@ -8,6 +8,7 @@ import postcss from 'rollup-plugin-postcss';
import { terser } from "rollup-plugin-terser";
import replace from 'rollup-plugin-replace';
import builtins from '@joseph184/rollup-plugin-node-builtins';
import webworkify from 'rollup-plugin-webworkify';
// import json from 'rollup-plugin-json';
import postcss_import from 'postcss-import';
@ -55,6 +56,10 @@ let plugins = [
}),
webworkify({
pattern: '**/*.worker.mjs'
}),
postcss({
plugins: [
postcss_import({}),