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: where_cond.rs
    path of file: ./repos/candle/candle-core/benches/benchmarks
    
    the code of the file until where you have to start completion: use crate::benchmarks::{BenchDevice, BenchDeviceHandler};
use candle_core::{DType, Device, Tensor};
use criterion::{black_box, criterion_group, Criterion, Throughput};
use std::time::Instant;

fn run(a: &Tensor, b: &Tensor, c: &Tensor) {
    a.where_cond(b, c).unwrap();
}

const fn create_cond_arr<const N: usize>
    
fn run_where_cond_benchmark(c: &mut Criterion, device: &Device, dtype: DType, name: &str) {
    let tensor = Tensor::from_slice(DATA.as_slice(), (B, M, K), &device).unwrap();
    let on_true = Tensor::ones((B, M, K), dtype, &device).unwrap();
    let on_false = Tensor::zeros((B, M, K), dtype, &device).unwrap();

    let elements = B * M * K;
    // E.g. 2 f32 tensors + 1 u8 tensor
    let flops = (2 * elements * dtype.size_in_bytes()) + elements;

    let mut group = c.benchmark_group(device.bench_name(name));
    group.throughput(Throughput::Bytes(flops as u64));
    group.bench_function("iter", move |b| {
        b.iter_custom(|iters| {
            let start = Instant::now();
            for _i in 0..iters {
                run(
                    black_box(&tensor),
                    black_box(&on_true),
                    black_box(&on_false),
                );
            }
            device.sync().unwrap();
            start.elapsed()
        })
    });
    group.finish();
}