From 7888bc902b41e320a7209eadb6c461bcc754c51e Mon Sep 17 00:00:00 2001
From: Abhinav <abhinavk.grd@gmail.com>
Date: Fri, 10 Feb 2023 22:25:37 +0530
Subject: [PATCH] comment out tsne generation code

---
 .../machineLearning/machineLearningService.ts | 28 ++++----
 src/utils/machineLearning/visualization.ts    | 64 ++++++++++---------
 2 files changed, 47 insertions(+), 45 deletions(-)

diff --git a/src/services/machineLearning/machineLearningService.ts b/src/services/machineLearning/machineLearningService.ts
index 64a5340c9..497c498bd 100644
--- a/src/services/machineLearning/machineLearningService.ts
+++ b/src/services/machineLearning/machineLearningService.ts
@@ -15,12 +15,12 @@ import {
     MLSyncResult,
 } from 'types/machineLearning';
 
-import { toTSNE } from 'utils/machineLearning/visualization';
+// import { toTSNE } from 'utils/machineLearning/visualization';
 // import {
 //     incrementIndexVersion,
 //     mlFilesStore
 // } from 'utils/storage/mlStorage';
-import { getAllFacesFromMap } from 'utils/machineLearning';
+// import { getAllFacesFromMap } from 'utils/machineLearning';
 import { MLFactory } from './machineLearningFactory';
 import mlIDbStorage from 'utils/storage/mlIDbStorage';
 import { getMLSyncConfig } from 'utils/machineLearning/config';
@@ -88,9 +88,9 @@ class MachineLearningService {
 
         // tf.engine().endScope();
 
-        if (syncContext.config.tsne) {
-            await this.runTSNE(syncContext);
-        }
+        // if (syncContext.config.tsne) {
+        //     await this.runTSNE(syncContext);
+        // }
 
         const mlSyncResult: MLSyncResult = {
             nOutOfSyncFiles: syncContext.outOfSyncFiles.length,
@@ -560,16 +560,16 @@ class MachineLearningService {
         await this.persistMLLibraryData(syncContext);
     }
 
-    private async runTSNE(syncContext: MLSyncContext) {
-        const allFacesMap = await FaceService.getAllSyncedFacesMap(syncContext);
-        const allFaces = getAllFacesFromMap(allFacesMap);
+    // private async runTSNE(syncContext: MLSyncContext) {
+    //     const allFacesMap = await FaceService.getAllSyncedFacesMap(syncContext);
+    //     const allFaces = getAllFacesFromMap(allFacesMap);
 
-        const input = allFaces
-            .slice(0, syncContext.config.tsne.samples)
-            .map((f) => Array.from(f.embedding));
-        syncContext.tsne = toTSNE(input, syncContext.config.tsne);
-        addLogLine('tsne: ', syncContext.tsne);
-    }
+    //     const input = allFaces
+    //         .slice(0, syncContext.config.tsne.samples)
+    //         .map((f) => Array.from(f.embedding));
+    //     syncContext.tsne = toTSNE(input, syncContext.config.tsne);
+    //     addLogLine('tsne: ', syncContext.tsne);
+    // }
 
     private async syncFaceDetections(
         syncContext: MLSyncContext,
diff --git a/src/utils/machineLearning/visualization.ts b/src/utils/machineLearning/visualization.ts
index 7275a50ac..949dde6f2 100644
--- a/src/utils/machineLearning/visualization.ts
+++ b/src/utils/machineLearning/visualization.ts
@@ -1,38 +1,40 @@
-import TSNE from 'tsne-js';
-import { TSNEConfig, TSNEData } from 'types/machineLearning';
+// // import TSNE from 'tsne-js';
+// import { TSNEConfig, TSNEData } from 'types/machineLearning';
 
-export function toD3Tsne(tsne) {
-    const data: TSNEData = {
-        width: 800,
-        height: 800,
-        dataset: [],
-    };
-    data.dataset = tsne.map((t) => {
-        return {
-            x: (data.width * (t[0] + 1.0)) / 2,
-            y: (data.height * (t[1] + 1.0)) / 2,
-        };
-    });
+// export function toD3Tsne(tsne) {
+//     const data: TSNEData = {
+//         width: 800,
+//         height: 800,
+//         dataset: [],
+//     };
+//     data.dataset = tsne.map((t) => {
+//         return {
+//             x: (data.width * (t[0] + 1.0)) / 2,
+//             y: (data.height * (t[1] + 1.0)) / 2,
+//         };
+//     });
 
-    return data;
-}
+//     return data;
+// }
 
-export function toTSNE(denseInput: Array<Array<number>>, config: TSNEConfig) {
-    if (!denseInput || denseInput.length < 1) {
-        return null;
-    }
+// export function toTSNE(denseInput: Array<Array<number>>, config: TSNEConfig) {
+//     if (!denseInput || denseInput.length < 1) {
+//         return null;
+//     }
 
-    const model = new TSNE(config);
+//     const model = new TSNE(config);
 
-    model.init({
-        data: denseInput,
-        type: 'dense',
-    });
+//     model.init({
+//         data: denseInput,
+//         type: 'dense',
+//     });
 
-    // `error`,  `iter`: final error and iteration number
-    // note: computation-heavy action happens here
-    model.run();
+//     // `error`,  `iter`: final error and iteration number
+//     // note: computation-heavy action happens here
+//     model.run();
 
-    // `outputScaled` is `output` scaled to a range of [-1, 1]
-    return model.getOutputScaled();
-}
+//     // `outputScaled` is `output` scaled to a range of [-1, 1]
+//     return model.getOutputScaled();
+// }
+
+export {};