Remove some dead-code annotations. (#629)

* Remove some dead-code annotations.

* More dead code removal.

* One more.

* CI fix.

candle-examples/examples/custom-ops/main.rs

@@ -2,19 +2,16 @@
 // own forward pass (CPU and GPU versions) as well as their backward pass.
 //
 // In this example we add the RMS normalization operation and implement it for f32.
-#![allow(dead_code)]
-#![allow(unused)]
 
 #[cfg(feature = "mkl")]
 extern crate intel_mkl_src;
 
+#[allow(unused)]
 mod cuda_kernels;
 
 use clap::Parser;
 
-use candle::backend::BackendStorage;
-use candle::cpu_backend;
-use candle::{CpuStorage, CustomOp1, DType, Device, Layout, Result, Shape, Tensor};
+use candle::{CpuStorage, CustomOp1, Layout, Result, Shape, Tensor};
 
 #[derive(Parser, Debug)]
 #[command(author, version, about, long_about = None)]
@@ -57,8 +54,9 @@ impl CustomOp1 for LayerNorm {
         storage: &candle::CudaStorage,
         layout: &Layout,
     ) -> Result<(candle::CudaStorage, Shape)> {
-        use candle::cuda_backend::{cudarc, WrapErr};
-        use cudarc::driver::{LaunchAsync, LaunchConfig};
+        use candle::backend::BackendStorage;
+        use candle::cuda_backend::cudarc::driver::{LaunchAsync, LaunchConfig};
+        use candle::cuda_backend::WrapErr;
         let (d1, d2) = layout.shape().dims2()?;
         let d1 = d1 as u32;
         let d2 = d2 as u32;

candle-examples/examples/quantized/main.rs

@@ -1,4 +1,3 @@
-#![allow(dead_code)]
 #[cfg(feature = "mkl")]
 extern crate intel_mkl_src;
 
@@ -185,16 +184,6 @@ struct ModelWeights {
     span_output: tracing::Span,
 }
 
-struct WeightMap(HashMap<String, QTensor>);
-impl WeightMap {
-    fn get(&mut self, name: &str) -> Result<QTensor> {
-        match self.0.remove(name) {
-            None => candle::bail!("cannot find tensor with name '{name}'"),
-            Some(tensor) => Ok(tensor),
-        }
-    }
-}
-
 fn precomput_freqs_cis(head_dim: usize, freq_base: f32) -> Result<(Tensor, Tensor)> {
     let theta: Vec<_> = (0..head_dim)
         .step_by(2)

candle-examples/examples/stable-diffusion/clip.rs

@@ -1,4 +1,3 @@
-#![allow(dead_code)]
 //! Contrastive Language-Image Pre-Training
 //!
 //! Contrastive Language-Image Pre-Training (CLIP) is an architecture trained on

candle-examples/examples/stable-diffusion/ddim.rs

@@ -1,4 +1,3 @@
-#![allow(dead_code)]
 //! # Denoising Diffusion Implicit Models
 //!
 //! The Denoising Diffusion Implicit Models (DDIM) is a simple scheduler
@@ -164,17 +163,6 @@ impl DDIMScheduler {
         }
     }
 
-    pub fn add_noise(&self, original: &Tensor, noise: Tensor, timestep: usize) -> Result<Tensor> {
-        let timestep = if timestep >= self.alphas_cumprod.len() {
-            timestep - 1
-        } else {
-            timestep
-        };
-        let sqrt_alpha_prod = self.alphas_cumprod[timestep].sqrt();
-        let sqrt_one_minus_alpha_prod = (1.0 - self.alphas_cumprod[timestep]).sqrt();
-        (original * sqrt_alpha_prod)? + (noise * sqrt_one_minus_alpha_prod)?
-    }
-
     pub fn init_noise_sigma(&self) -> f64 {
         self.init_noise_sigma
     }

candle-examples/examples/stable-diffusion/embeddings.rs

@@ -1,4 +1,3 @@
-#![allow(dead_code)]
 use candle::{Result, Tensor, D};
 use candle_nn as nn;
 use candle_nn::Module;

candle-examples/examples/stable-diffusion/resnet.rs

@@ -1,4 +1,3 @@
-#![allow(dead_code)]
 //! ResNet Building Blocks
 //!
 //! Some Residual Network blocks used in UNet models.

candle-examples/examples/whisper/model.rs

@@ -19,34 +19,6 @@ pub struct Config {
     pub suppress_tokens: Vec<u32>,
 }
 
-impl Config {
-    #[allow(dead_code)]
-    pub fn tiny_en() -> Self {
-        let suppress_tokens = vec![
-            1, 2, 7, 8, 9, 10, 14, 25, 26, 27, 28, 29, 31, 58, 59, 60, 61, 62, 63, 90, 91, 92, 93,
-            357, 366, 438, 532, 685, 705, 796, 930, 1058, 1220, 1267, 1279, 1303, 1343, 1377, 1391,
-            1635, 1782, 1875, 2162, 2361, 2488, 3467, 4008, 4211, 4600, 4808, 5299, 5855, 6329,
-            7203, 9609, 9959, 10563, 10786, 11420, 11709, 11907, 13163, 13697, 13700, 14808, 15306,
-            16410, 16791, 17992, 19203, 19510, 20724, 22305, 22935, 27007, 30109, 30420, 33409,
-            34949, 40283, 40493, 40549, 47282, 49146, 50257, 50357, 50358, 50359, 50360, 50361,
-            50362,
-        ];
-        Self {
-            num_mel_bins: 80,
-            vocab_size: 51864,
-            max_source_positions: 1500,
-            d_model: 384,
-            encoder_attention_heads: 6,
-            encoder_layers: 4,
-            max_target_positions: 448,
-            // n_text_state: 384,
-            decoder_attention_heads: 6,
-            decoder_layers: 4,
-            suppress_tokens,
-        }
-    }
-}
-
 fn embedding(vocab_size: usize, hidden_size: usize, vb: VarBuilder) -> Result<Embedding> {
     let embeddings = vb.get((vocab_size, hidden_size), "weight")?;
     Ok(Embedding::new(embeddings, hidden_size))

candle-examples/examples/yolo-v8/model.rs

@@ -675,7 +675,6 @@ pub struct YoloV8Pose {
     head: PoseHead,
 }
 
-#[allow(unused)]
 impl YoloV8Pose {
     pub fn load(
         vb: VarBuilder,