phase 1

scripts/train.ts

@@ -0,0 +1,35 @@
+import * as tf from "@tensorflow/tfjs-node";
+import { readFile } from "node:fs/promises";
+import { existsSync } from "node:fs";
+import { join } from "node:path";
+
+async function train() {
+  const savePath = process.argv[2] || 'sample/model';
+  const data = JSON.parse(await readFile(join(process.argv[3] || 'sample/dataset', 'dataset.json'), "utf-8"));
+  const X = tf.tensor2d(data.map((d: any) => d.x.map((v: any, i: number) => v / (i == 0 ? 20 : i == 1 ? 200 : 1))));
+  const y = tf.tensor2d(data.map((d: any) => [d.y]));
+
+  let model: tf.LayersModel;
+  const modelJsonPath = join(savePath, "model.json");
+
+  if (existsSync(modelJsonPath)) {
+    console.log("기존 모델을 불러와 추가 학습을 진행합니다.");
+    model = await tf.loadLayersModel(`file://${modelJsonPath}`);
+  } else {
+    console.log("새 모델을 생성합니다.");
+    model = tf.sequential({
+      layers: [
+        tf.layers.dense({ units: 32, activation: 'relu', inputShape: [5] }),
+        tf.layers.dense({ units: 16, activation: 'relu' }),
+        tf.layers.dense({ units: 1 })
+      ]
+    });
+  }
+
+  model.compile({ optimizer: 'adam', loss: 'meanSquaredError' });
+  const epochs = parseInt(process.argv[4]) || 50;
+  await model.fit(X, y, { epochs: epochs, verbose: 0 });
+  await model.save(`file://${savePath}`);
+  console.log(`학습 완료: 모델이 ${savePath}에 저장되었습니다.`);
+}
+train().catch(console.error);