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install.js
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// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
'use strict';
// This script is written in JavaScript. This is because it is used in "install" script in package.json, which is called
// when the package is installed either as a dependency or from "npm ci"/"npm install" without parameters. TypeScript is
// not always available.
// The purpose of this script is to download the required binaries for the platform and architecture.
// Currently, most of the binaries are already bundled in the package, except for the following:
// - Linux/x64/CUDA 11
// - Linux/x64/CUDA 12
//
// The CUDA binaries are not bundled because they are too large to be allowed in the npm registry. Instead, they are
// downloaded from the GitHub release page of ONNX Runtime. The script will download the binaries if they are not
// already present in the package.
// Step.1: Check if we should exit early
const os = require('os');
const fs = require('fs');
const path = require('path');
const tar = require('tar');
const { execFileSync } = require('child_process');
const { Readable } = require('stream');
// commandline flag:
// --onnxruntime-node-install-cuda Force install the CUDA EP binaries. Try to detect the CUDA version.
// --onnxruntime-node-install-cuda=v11 Force install the CUDA EP binaries for CUDA 11.
// --onnxruntime-node-install-cuda=v12 Force install the CUDA EP binaries for CUDA 12.
// --onnxruntime-node-install-cuda=skip Skip the installation of the CUDA EP binaries.
//
// Alternatively, use environment variable "ONNXRUNTIME_NODE_INSTALL_CUDA"
//
// If the flag is not provided, the script will only install the CUDA EP binaries when:
// - The platform is Linux/x64.
// - The binaries are not already present in the package.
// - The installation is not a local install (when used inside ONNX Runtime repo).
//
const INSTALL_CUDA_FLAG = parseInstallCudaFlag();
const NO_INSTALL = INSTALL_CUDA_FLAG === 'skip';
const FORCE_INSTALL = !NO_INSTALL && INSTALL_CUDA_FLAG;
const IS_LINUX_X64 = os.platform() === 'linux' && os.arch() === 'x64';
const BIN_FOLDER = path.join(__dirname, '..', 'bin/napi-v3/linux/x64');
const BIN_FOLDER_EXISTS = fs.existsSync(BIN_FOLDER);
const CUDA_DLL_EXISTS = fs.existsSync(path.join(BIN_FOLDER, 'libonnxruntime_providers_cuda.so'));
const ORT_VERSION = require('../package.json').version;
const npm_config_local_prefix = process.env.npm_config_local_prefix;
const npm_package_json = process.env.npm_package_json;
const SKIP_LOCAL_INSTALL =
npm_config_local_prefix && npm_package_json && path.dirname(npm_package_json) === npm_config_local_prefix;
const shouldInstall = FORCE_INSTALL || (!SKIP_LOCAL_INSTALL && IS_LINUX_X64 && BIN_FOLDER_EXISTS && !CUDA_DLL_EXISTS);
if (NO_INSTALL || !shouldInstall) {
process.exit(0);
}
// Step.2: Download the required binaries
const artifactUrl = {
get 11() {
// TODO: support ORT Cuda v11 binaries
throw new Error(`CUDA 11 binaries are not supported by this script yet.
To use ONNX Runtime Node.js binding with CUDA v11 support, please follow the manual steps:
1. Use "--onnxruntime-node-install-cuda=skip" to skip the auto installation.
2. Navigate to https://aiinfra.visualstudio.com/PublicPackages/_artifacts/feed/onnxruntime-cuda-11
3. Download the binaries for your platform and architecture
4. Extract the following binaries to "node_modules/onnxruntime-node/bin/napi-v3/linux/x64:
- libonnxruntime_providers_tensorrt.so
- libonnxruntime_providers_shared.so
- libonnxruntime.so.${ORT_VERSION}
- libonnxruntime_providers_cuda.so
`);
},
12: `https://github.com/microsoft/onnxruntime/releases/download/v${ORT_VERSION}/onnxruntime-linux-x64-gpu-${
ORT_VERSION
}.tgz`,
}[INSTALL_CUDA_FLAG || tryGetCudaVersion()];
console.log(`Downloading "${artifactUrl}"...`);
fetch(artifactUrl).then((res) => {
if (!res.ok) {
throw new Error(`Failed to download the binaries: ${res.status} ${res.statusText}.
Use "--onnxruntime-node-install-cuda=skip" to skip the installation. You will still be able to use ONNX Runtime, but the CUDA EP will not be available.`);
}
// Extract the binaries
const FILES = new Set([
'libonnxruntime_providers_tensorrt.so',
'libonnxruntime_providers_shared.so',
`libonnxruntime.so.${ORT_VERSION}`,
'libonnxruntime_providers_cuda.so',
]);
Readable.fromWeb(res.body)
.pipe(
tar.t({
strict: true,
onentry: (entry) => {
const filename = path.basename(entry.path);
if (entry.type === 'File' && FILES.has(filename)) {
console.log(`Extracting "${filename}" to "${BIN_FOLDER}"...`);
entry.pipe(fs.createWriteStream(path.join(BIN_FOLDER, filename)));
entry.on('finish', () => {
console.log(`Finished extracting "${filename}".`);
});
}
},
}),
)
.on('error', (err) => {
throw new Error(`Failed to extract the binaries: ${err.message}.
Use "--onnxruntime-node-install-cuda=skip" to skip the installation. You will still be able to use ONNX Runtime, but the CUDA EP will not be available.`);
});
});
function tryGetCudaVersion() {
// Should only return 11 or 12.
// try to get the CUDA version from the system ( `nvcc --version` )
let ver = 12;
try {
const nvccVersion = execFileSync('nvcc', ['--version'], { encoding: 'utf8' });
const match = nvccVersion.match(/release (\d+)/);
if (match) {
ver = parseInt(match[1]);
if (ver !== 11 && ver !== 12) {
throw new Error(`Unsupported CUDA version: ${ver}`);
}
}
} catch (e) {
if (e?.code === 'ENOENT') {
console.warn('`nvcc` not found. Assuming CUDA 12.');
} else {
console.warn('Failed to detect CUDA version from `nvcc --version`:', e.message);
}
}
// assume CUDA 12 if failed to detect
return ver;
}
function parseInstallCudaFlag() {
let flag = process.env.ONNXRUNTIME_NODE_INSTALL_CUDA || process.env.npm_config_onnxruntime_node_install_cuda;
if (!flag) {
for (let i = 0; i < process.argv.length; i++) {
if (process.argv[i].startsWith('--onnxruntime-node-install-cuda=')) {
flag = process.argv[i].split('=')[1];
break;
} else if (process.argv[i] === '--onnxruntime-node-install-cuda') {
flag = 'true';
}
}
}
switch (flag) {
case 'true':
case '1':
case 'ON':
return tryGetCudaVersion();
case 'v11':
return 11;
case 'v12':
return 12;
case 'skip':
case undefined:
return flag;
default:
throw new Error(`Invalid value for --onnxruntime-node-install-cuda: ${flag}`);
}
}