Experiment with resnet (#1128)

* Add some preliminary support for resnet.

* Add an actual resnet example.

candle-examples/examples/resnet/main.rs

@@ -0,0 +1,76 @@
+#[cfg(feature = "mkl")]
+extern crate intel_mkl_src;
+
+#[cfg(feature = "accelerate")]
+extern crate accelerate_src;
+
+use candle::{DType, IndexOp, D};
+use candle_nn::{Module, VarBuilder};
+use candle_transformers::models::resnet;
+use clap::{Parser, ValueEnum};
+
+#[derive(Clone, Copy, Debug, ValueEnum)]
+enum Which {
+    Resnet18,
+    Resnet34,
+}
+
+#[derive(Parser)]
+struct Args {
+    #[arg(long)]
+    model: Option<String>,
+
+    #[arg(long)]
+    image: String,
+
+    /// Run on CPU rather than on GPU.
+    #[arg(long)]
+    cpu: bool,
+
+    /// Variant of the model to use.
+    #[arg(value_enum, long, default_value_t = Which::Resnet18)]
+    which: Which,
+}
+
+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-resnet".into());
+            let filename = match args.which {
+                Which::Resnet18 => "resnet18.safetensors",
+                Which::Resnet34 => "resnet34.safetensors",
+            };
+            api.get(filename)?
+        }
+        Some(model) => model.into(),
+    };
+    let vb = unsafe { VarBuilder::from_mmaped_safetensors(&[model_file], DType::F32, &device)? };
+    let class_count = candle_examples::imagenet::CLASS_COUNT as usize;
+    let model = match args.which {
+        Which::Resnet18 => resnet::resnet18(class_count, vb)?,
+        Which::Resnet34 => resnet::resnet34(class_count, 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(())
+}