Write the the data input, but it's untested.

There's also some confusion over the batch size. If it doesn't work, we 
probably need to  revise our understanding of the batch size in 
different contexts.

server/settings.default.toml

@@ -59,6 +59,14 @@ devices = [
 rssi_min = -150
 rssi_max = 0
 
+# Data is streamed from the SQLite databse. The batch size specifies how many 
+# rows to gather for training at once.
+# Note that the entire available dataset will eventually end up being used - 
+# this setting just controls how much of ti is in memory at once.
+batch_size = 32
+# The number of epochs to train for.
+epochs = 5
+
 [logging]
 # The format the date displayed when logging things should take.
 # Allowed values: relative (e.g like when a Linux machine boots), absolute (e.g. like Nginx server logs), none (omits it entirely))

server/train-ai/AITrainer.mjs

@@ -31,15 +31,31 @@ class AITrainer {
 		return model;
 	}
 	
-	async train() {
+	async train_all() {
 		for(let gateway of this.repo_gateway.iterate()) {
-			let dataset = this.dataset_fetcher.fetch(gateway.id);
+			await this.train_dataset(gateway.id);
-			await this.train_dataset(dataset);
 		}
 	}
 	
-	async train_dataset(dataset) {
+	async train_gateway(gateway_id) {
-		// TODO: Fill this in
+		let dataset_input = tf.data.generator(
+			this.dataset_fetcher.fetch_input.bind(null, gateway_id)
+		);
+		let dataset_output = tf.data.generator(
+			this.dataset_fetcher.fetch_output.bind(null, gateway_id)
+		);
+		
+		let dataset = tf.data.zip({
+				xs: dataset_input,
+				ys: dataset_output
+			}).shuffle(this.settings.ai.batch_size)
+			.batch(this.settings.ai.batch_size);
+		
+		let result = await this.model.fitDataset(dataset, {
+			epochs: this.settings.ai.epochs,
+			batchSize:  this.settings.ai.batch_size
+		});
+		console.log(result);
 	}
 }
 

server/train-ai/DatasetFetcher.mjs

@@ -8,11 +8,9 @@ class DatasetFetcher {
 		this.repo_rssi = RSSIRepo;
 	}
 	
-	fetch(gateway_id) {
+	*fetch_input(gateway_id) {
-		let result = [];
+		for(let rssi of this.repo_rssi.iterate_gateway(gateway_id)) {
-		for(let rssi of this.repo_rssi.iterate_gateway(gateway_id) {
+			yield [
-			result.push({
-				input: [
 				normalise(rssi.latitude,
 					{ min: -90, max: +90 },
 					{ min: 0, max: 1 }
@@ -21,16 +19,19 @@ class DatasetFetcher {
 					{ min: -180, max: +180 },
 					{ min: 0, max: 1 }
 				)
-				],
+			];
-				output: [
+		}
-					clamp(normalise(rssis.rssi,
+	}
+	
+	*fetch_output(gateway_id) {
+		for(let rssi of this.repo_rssi.iterate_gateway(gateway_id)) {
+			yield [
+				clamp(normalise(rssi.rssi,
 					{ min: this.settings.ai.rssi_min, max: this.settings.ai.rssi_max },
 					{ min: 0, max: 1 }
 				), 0, 1)
-				]
+			];
-			});
 		}
-		return result;
 	}
 }