Fix crash at startup if TensorFlow is not supported (#8984)

* Lazy loading tensorflow

* CHANGELOG

* CHANGELOG

* Check CPU flags

* .
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MeiMei 2022-07-12 10:38:57 +09:00 committed by GitHub
parent 1557d0afb8
commit 660781afd9
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2 changed files with 29 additions and 2 deletions

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@ -9,6 +9,13 @@
You should also include the user name that made the change. You should also include the user name that made the change.
--> -->
## 12.x.x (unreleased)
### Improvements
### Bugfixes
- Server: Fix crash at startup if TensorFlow is not supported @mei23
## 12.112.3 (2022/07/09) ## 12.112.3 (2022/07/09)
### Improvements ### Improvements

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@ -2,19 +2,34 @@ import * as fs from 'node:fs';
import { fileURLToPath } from 'node:url'; import { fileURLToPath } from 'node:url';
import { dirname } from 'node:path'; import { dirname } from 'node:path';
import * as nsfw from 'nsfwjs'; import * as nsfw from 'nsfwjs';
import * as tf from '@tensorflow/tfjs-node'; import si from 'systeminformation';
const _filename = fileURLToPath(import.meta.url); const _filename = fileURLToPath(import.meta.url);
const _dirname = dirname(_filename); const _dirname = dirname(_filename);
const REQUIRED_CPU_FLAGS = ['avx2', 'fma'];
let isSupportedCpu: undefined | boolean = undefined;
let model: nsfw.NSFWJS; let model: nsfw.NSFWJS;
export async function detectSensitive(path: string): Promise<nsfw.predictionType[] | null> { export async function detectSensitive(path: string): Promise<nsfw.predictionType[] | null> {
try { try {
if (isSupportedCpu === undefined) {
const cpuFlags = await getCpuFlags();
isSupportedCpu = REQUIRED_CPU_FLAGS.every(required => cpuFlags.includes(required));
}
if (!isSupportedCpu) {
console.error('This CPU cannot use TensorFlow.');
return null;
}
const tf = await import('@tensorflow/tfjs-node');
if (model == null) model = await nsfw.load(`file://${_dirname}/../../nsfw-model/`, { size: 299 }); if (model == null) model = await nsfw.load(`file://${_dirname}/../../nsfw-model/`, { size: 299 });
const buffer = await fs.promises.readFile(path); const buffer = await fs.promises.readFile(path);
const image = await tf.node.decodeImage(buffer, 3) as tf.Tensor3D; const image = await tf.node.decodeImage(buffer, 3) as any;
try { try {
const predictions = await model.classify(image); const predictions = await model.classify(image);
return predictions; return predictions;
@ -26,3 +41,8 @@ export async function detectSensitive(path: string): Promise<nsfw.predictionType
return null; return null;
} }
} }
async function getCpuFlags(): Promise<string[]> {
const str = await si.cpuFlags();
return str.split(/\s+/);
}