Small example for benchmarking some cpu ops (#394)

* Refactor the benchmark example.

* Rename the example.

* Add some comments.
This commit is contained in:
Laurent Mazare
2023-08-10 18:00:17 +02:00
committed by GitHub
parent 7f710a573d
commit ff53f38467
3 changed files with 96 additions and 24 deletions

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@ -30,6 +30,7 @@ zip = { workspace = true }
[dev-dependencies] [dev-dependencies]
anyhow = { workspace = true } anyhow = { workspace = true }
clap = { workspace = true }
[features] [features]
default = [] default = []

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@ -1,24 +0,0 @@
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::Result;
use candle_core::{Device, Tensor};
pub const N_ITERS: usize = 5;
fn main() -> Result<()> {
let inp = Tensor::randn(0f32, 1., (1, 384, 3000), &Device::Cpu)?;
let w = Tensor::randn(0f32, 1., (384, 384, 3), &Device::Cpu)?;
let res = inp.conv1d(&w, 0, 1);
println!("{res:?}");
let start = std::time::Instant::now();
for i in 0..N_ITERS {
let res = inp.conv1d(&w, 0, 1);
println!("{i} {res:?}");
}
println!("{:?}", start.elapsed() / N_ITERS as u32);
Ok(())
}

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@ -0,0 +1,95 @@
/// This example contains some simple benchmarks so that it's easy to run them in perf etc.
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use candle_core::{Device, Result, Tensor};
use clap::{Parser, Subcommand};
trait Benchmark {
type PreProcessData;
type RunResult;
fn preprocess() -> Result<Self::PreProcessData>;
fn run_one(_: &Self::PreProcessData) -> Result<Self::RunResult>;
const ITERS: usize;
}
// Conv1d example as used in whisper.
struct Conv1d;
impl Benchmark for Conv1d {
type PreProcessData = (Tensor, Tensor);
type RunResult = Tensor;
fn preprocess() -> Result<Self::PreProcessData> {
let inp = Tensor::randn(0f32, 1., (1, 384, 3000), &Device::Cpu)?;
let w = Tensor::randn(0f32, 1., (384, 384, 3), &Device::Cpu)?;
Ok((inp, w))
}
fn run_one(d: &Self::PreProcessData) -> Result<Self::RunResult> {
d.0.conv1d(&d.1, 0, 1)
}
const ITERS: usize = 5;
}
// Conv2d example as used in stable-diffusion.
struct Conv2d;
impl Benchmark for Conv2d {
type PreProcessData = (Tensor, Tensor);
type RunResult = Tensor;
fn preprocess() -> Result<Self::PreProcessData> {
let inp = Tensor::randn(0f32, 1., (2, 320, 96, 96), &Device::Cpu)?;
let w = Tensor::randn(0f32, 1., (320, 320, 3, 3), &Device::Cpu)?;
Ok((inp, w))
}
fn run_one(d: &Self::PreProcessData) -> Result<Self::RunResult> {
d.0.conv2d(&d.1, 0, 1)
}
const ITERS: usize = 1;
}
fn run<B: Benchmark>(iters: Option<usize>) -> Result<()> {
use std::hint::black_box;
let iters = iters.unwrap_or(B::ITERS);
let d = B::preprocess()?;
let start = std::time::Instant::now();
for _iter in 0..iters {
let _res = black_box(B::run_one(black_box(&d))?);
}
println!("{:?}", start.elapsed() / iters as u32);
Ok(())
}
#[derive(Subcommand, Debug, Clone)]
enum Task {
Conv1d,
Conv2d,
}
#[derive(Parser, Debug)]
#[command(author, version, about, long_about = None)]
pub struct Args {
/// The benchmark to be run.
#[command(subcommand)]
task: Task,
#[arg(long)]
iters: Option<usize>,
}
fn main() -> Result<()> {
let args = Args::parse();
match args.task {
Task::Conv1d => run::<Conv1d>(args.iters)?,
Task::Conv2d => run::<Conv2d>(args.iters)?,
}
Ok(())
}