You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: mod.rs
    path of file: ./repos/wgpu/examples/src/hello_compute
    
    the code of the file until where you have to start completion: use std::{borrow::Cow, str::FromStr};
use wgpu::util::DeviceExt;

// Indicates a u32 overflow in an intermediate Collatz value
const OVERFLOW: u32 = 0xffffffff;

#[cfg_attr(test, allow(dead_code))]
async fn run() {
    let numbers = if std::env::args().len() <= 2 {
        let default = vec![1, 2, 3, 4];
     
    
async fn execute_gpu(numbers: &[u32]) -> Option<Vec<u32>> {
    // Instantiates instance of WebGPU
    let instance = wgpu::Instance::default();

    // `request_adapter` instantiates the general connection to the GPU
    let adapter = instance
        .request_adapter(&wgpu::RequestAdapterOptions::default())
        .await?;

    // `request_device` instantiates the feature specific connection to the GPU, defining some parameters,
    //  `features` being the available features.
    let (device, queue) = adapter
        .request_device(
            &wgpu::DeviceDescriptor {
                label: None,
                required_features: wgpu::Features::empty(),
                required_limits: wgpu::Limits::downlevel_defaults(),
            },
            None,
        )
        .await
        .unwrap();

    execute_gpu_inner(&device, &queue, numbers).await
}