From b6d56a00a8efe6d8b2fe552fb53a5ae784f567d0 Mon Sep 17 00:00:00 2001
From: Wanming Lin <wanming.lin@intel.com>
Date: Tue, 7 May 2024 15:46:46 +0800
Subject: [PATCH] Fix lint error

---
 object_detection/main.js             | 11 +----------
 object_detection/tiny_yolov2_nchw.js | 17 +++++++++++------
 2 files changed, 12 insertions(+), 16 deletions(-)

diff --git a/object_detection/main.js b/object_detection/main.js
index eeea0c1d..8ed9b8fe 100644
--- a/object_detection/main.js
+++ b/object_detection/main.js
@@ -158,16 +158,7 @@ async function drawOutput(inputElement, outputs, labels) {
         boxesList, scoresList, classesList, labels);
   } else {
     // Draw output for Tiny Yolo V2 model
-    // Transpose 'nchw' output to 'nhwc' for postprocessing
-    let outputBuffer = outputs.output;
-    if (layout === 'nchw') {
-      outputBuffer = tf.tidy(() => {
-        const a =
-            tf.tensor(outputBuffer, netInstance.outputDimensions, 'float32');
-        const b = tf.transpose(a, [0, 2, 3, 1]);
-        return b.dataSync();
-      });
-    }
+    const outputBuffer = outputs.output;
     const decodeOut = Yolo2Decoder.decodeYOLOv2({numClasses: 20},
         outputBuffer, inputOptions.anchors);
     const boxes = Yolo2Decoder.getBoxes(decodeOut, inputOptions.margin);
diff --git a/object_detection/tiny_yolov2_nchw.js b/object_detection/tiny_yolov2_nchw.js
index 8238aff7..6ddcbcdb 100644
--- a/object_detection/tiny_yolov2_nchw.js
+++ b/object_detection/tiny_yolov2_nchw.js
@@ -1,6 +1,6 @@
 'use strict';
 
-import {buildConstantByNpy, computePadding2DForAutoPad, weightsOrigin, toHalf} from '../common/utils.js';
+import {buildConstantByNpy, computePadding2DForAutoPad, weightsOrigin} from '../common/utils.js';
 
 // Tiny Yolo V2 model with 'nchw' layout, trained on the Pascal VOC dataset.
 export class TinyYoloV2Nchw {
@@ -23,20 +23,24 @@ export class TinyYoloV2Nchw {
   }
 
   async buildConv_(input, name) {
-    let biasName = `${this.weightsUrl_}ConvBnFusion_BN_B_BatchNormalization_B${name}.npy`;
-    let weightName = `${this.weightsUrl_}ConvBnFusion_W_convolution${name}_W.npy`;
+    let biasName =
+        `${this.weightsUrl_}ConvBnFusion_BN_B_BatchNormalization_B${name}.npy`;
+    let weightName =
+        `${this.weightsUrl_}ConvBnFusion_W_convolution${name}_W.npy`;
     if (name === '8') {
       biasName = `${this.weightsUrl_}convolution8_B.npy`;
       weightName = `${this.weightsUrl_}convolution8_W.npy`;
     }
 
-    const weight = await buildConstantByNpy(this.builder_, weightName, this.targetDataType_);
+    const weight = await buildConstantByNpy(
+        this.builder_, weightName, this.targetDataType_);
     const options = {autoPad: 'same-upper'};
     options.padding = computePadding2DForAutoPad(
         /* nchw */[input.shape()[2], input.shape()[3]],
         /* oihw */[weight.shape()[2], weight.shape()[3]],
         options.strides, options.dilations, 'same-upper');
-    options.bias = await buildConstantByNpy(this.builder_, biasName, this.targetDataType_);
+    options.bias = await buildConstantByNpy(
+        this.builder_, biasName, this.targetDataType_);
     const conv = this.builder_.conv2d(input, weight, options);
     if (name === '8') {
       return conv;
@@ -92,7 +96,8 @@ export class TinyYoloV2Nchw {
     const conv6 = await this.buildConv_(pool5, '6');
     const conv7 = await this.buildConv_(conv6, '7');
     const conv = await this.buildConv_(conv7, '8');
-    const transpose = this.builder_.transpose(conv, {permutation: [0, 2, 3, 1]});
+    const transpose = this.builder_.transpose(
+        conv, {permutation: [0, 2, 3, 1]});
     if (this.targetDataType_ === 'float16') {
       return this.builder_.cast(transpose, 'float32');
     } else {