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authorLaurent Mazare <laurent.mazare@gmail.com>2023-10-11 20:51:10 +0200
committerGitHub <noreply@github.com>2023-10-11 19:51:10 +0100
commite7560443e4680b7655d011948d3cf178268fcfff (patch)
treefe7f26799c6afee59c30c9c33b24a390e397aae2 /candle-examples/examples/convmixer/main.rs
parent89b525b5e758218179dd32293e7167e3aae1b28f (diff)
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Convmixer example (#1074)
* Add a convmixer based example. * Mention the model in the readme.
Diffstat (limited to 'candle-examples/examples/convmixer/main.rs')
-rw-r--r--candle-examples/examples/convmixer/main.rs59
1 files changed, 59 insertions, 0 deletions
diff --git a/candle-examples/examples/convmixer/main.rs b/candle-examples/examples/convmixer/main.rs
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+++ b/candle-examples/examples/convmixer/main.rs
@@ -0,0 +1,59 @@
+#[cfg(feature = "mkl")]
+extern crate intel_mkl_src;
+
+#[cfg(feature = "accelerate")]
+extern crate accelerate_src;
+
+use clap::Parser;
+
+use candle::{DType, IndexOp, D};
+use candle_nn::{Module, VarBuilder};
+use candle_transformers::models::convmixer;
+
+#[derive(Parser)]
+struct Args {
+ #[arg(long)]
+ model: Option<String>,
+
+ #[arg(long)]
+ image: String,
+
+ /// Run on CPU rather than on GPU.
+ #[arg(long)]
+ cpu: bool,
+}
+
+pub fn main() -> anyhow::Result<()> {
+ let args = Args::parse();
+
+ let device = candle_examples::device(args.cpu)?;
+
+ let image = candle_examples::imagenet::load_image224(args.image)?;
+ println!("loaded image {image:?}");
+
+ let model_file = match args.model {
+ None => {
+ let api = hf_hub::api::sync::Api::new()?;
+ let api = api.model("lmz/candle-convmixer".into());
+ api.get("convmixer_1024_20_ks9_p14.safetensors")?
+ }
+ Some(model) => model.into(),
+ };
+ let vb = unsafe { VarBuilder::from_mmaped_safetensors(&[model_file], DType::F32, &device)? };
+ let model = convmixer::c1024_20(1000, vb)?;
+ println!("model built");
+ let logits = model.forward(&image.unsqueeze(0)?)?;
+ let prs = candle_nn::ops::softmax(&logits, D::Minus1)?
+ .i(0)?
+ .to_vec1::<f32>()?;
+ let mut prs = prs.iter().enumerate().collect::<Vec<_>>();
+ prs.sort_by(|(_, p1), (_, p2)| p2.total_cmp(p1));
+ for &(category_idx, pr) in prs.iter().take(5) {
+ println!(
+ "{:24}: {:.2}%",
+ candle_examples::imagenet::CLASSES[category_idx],
+ 100. * pr
+ );
+ }
+ Ok(())
+}