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Add FastViT model. (#2444)
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102
candle-examples/examples/fastvit/main.rs
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102
candle-examples/examples/fastvit/main.rs
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#[cfg(feature = "mkl")]
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extern crate intel_mkl_src;
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#[cfg(feature = "accelerate")]
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extern crate accelerate_src;
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use clap::{Parser, ValueEnum};
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use candle::{DType, IndexOp, D};
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use candle_nn::{Module, VarBuilder};
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use candle_transformers::models::fastvit;
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#[derive(Clone, Copy, Debug, ValueEnum)]
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enum Which {
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T8,
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T12,
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S12,
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SA12,
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SA24,
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SA36,
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MA36,
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}
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impl Which {
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fn model_filename(&self) -> String {
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let name = match self {
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Self::T8 => "t8",
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Self::T12 => "t12",
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Self::S12 => "s12",
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Self::SA12 => "sa12",
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Self::SA24 => "sa24",
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Self::SA36 => "sa36",
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Self::MA36 => "ma36",
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};
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format!("timm/fastvit_{}.apple_in1k", name)
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}
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fn config(&self) -> fastvit::Config {
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match self {
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Self::T8 => fastvit::Config::t8(),
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Self::T12 => fastvit::Config::t12(),
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Self::S12 => fastvit::Config::s12(),
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Self::SA12 => fastvit::Config::sa12(),
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Self::SA24 => fastvit::Config::sa24(),
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Self::SA36 => fastvit::Config::sa36(),
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Self::MA36 => fastvit::Config::ma36(),
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}
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}
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}
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#[derive(Parser)]
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struct Args {
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#[arg(long)]
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model: Option<String>,
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#[arg(long)]
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image: String,
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/// Run on CPU rather than on GPU.
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#[arg(long)]
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cpu: bool,
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#[arg(value_enum, long, default_value_t=Which::S12)]
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which: Which,
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}
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pub fn main() -> anyhow::Result<()> {
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let args = Args::parse();
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let device = candle_examples::device(args.cpu)?;
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let image = candle_examples::imagenet::load_image(args.image, 256)?.to_device(&device)?;
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println!("loaded image {image:?}");
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let model_file = match args.model {
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None => {
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let model_name = args.which.model_filename();
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let api = hf_hub::api::sync::Api::new()?;
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let api = api.model(model_name);
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api.get("model.safetensors")?
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}
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Some(model) => model.into(),
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};
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let vb = unsafe { VarBuilder::from_mmaped_safetensors(&[model_file], DType::F32, &device)? };
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let model = fastvit::fastvit(&args.which.config(), 1000, vb)?;
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println!("model built");
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let logits = model.forward(&image.unsqueeze(0)?)?;
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let prs = candle_nn::ops::softmax(&logits, D::Minus1)?
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.i(0)?
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.to_vec1::<f32>()?;
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let mut prs = prs.iter().enumerate().collect::<Vec<_>>();
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prs.sort_by(|(_, p1), (_, p2)| p2.total_cmp(p1));
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for &(category_idx, pr) in prs.iter().take(5) {
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println!(
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"{:24}: {:.2}%",
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candle_examples::imagenet::CLASSES[category_idx],
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100. * pr
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);
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}
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Ok(())
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}
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