Fixes for clippy 1.87. (#2956)

candle-datasets/src/vision/mnist.rs

@@ -16,10 +16,9 @@ fn read_u32<T: Read>(reader: &mut T) -> std::io::Result<u32> {
 fn check_magic_number<T: Read>(reader: &mut T, expected: u32) -> Result<()> {
     let magic_number = read_u32(reader)?;
     if magic_number != expected {
-        Err(io::Error::new(
-            io::ErrorKind::Other,
-            format!("incorrect magic number {magic_number} != {expected}"),
-        ))?;
+        Err(io::Error::other(format!(
+            "incorrect magic number {magic_number} != {expected}"
+        )))?;
     }
     Ok(())
 }

candle-examples/examples/debertav2/main.rs

@@ -20,8 +20,8 @@ use hf_hub::{api::sync::Api, Repo, RepoType};
 use tokenizers::{Encoding, PaddingParams, Tokenizer};
 
 enum TaskType {
-    Ner(DebertaV2NERModel),
-    TextClassification(DebertaV2SeqClassificationModel),
+    Ner(Box<DebertaV2NERModel>),
+    TextClassification(Box<DebertaV2SeqClassificationModel>),
 }
 
 #[derive(Parser, Debug, Clone, ValueEnum)]
@@ -169,21 +169,16 @@ impl Args {
 
         match self.task {
             ArgsTask::Ner => Ok((
-                TaskType::Ner(DebertaV2NERModel::load(
-                    vb,
-                    &config,
-                    Some(id2label.clone()),
-                )?),
+                TaskType::Ner(DebertaV2NERModel::load(vb, &config, Some(id2label.clone()))?.into()),
                 config,
                 tokenizer,
                 id2label,
             )),
             ArgsTask::TextClassification => Ok((
-                TaskType::TextClassification(DebertaV2SeqClassificationModel::load(
-                    vb,
-                    &config,
-                    Some(id2label.clone()),
-                )?),
+                TaskType::TextClassification(
+                    DebertaV2SeqClassificationModel::load(vb, &config, Some(id2label.clone()))?
+                        .into(),
+                ),
                 config,
                 tokenizer,
                 id2label,

candle-examples/examples/distilbert/main.rs

@@ -16,8 +16,8 @@ use std::path::PathBuf;
 use tokenizers::Tokenizer;
 
 enum ModelType {
-    Masked(DistilBertForMaskedLM),
-    UnMasked(DistilBertModel),
+    Masked(Box<DistilBertForMaskedLM>),
+    UnMasked(Box<DistilBertModel>),
 }
 
 impl ModelType {
@@ -144,10 +144,12 @@ impl Args {
 
     fn create_model(&self, config: &Config, vb: VarBuilder) -> Result<ModelType> {
         match self.model {
-            Which::DistilbertForMaskedLM => {
-                Ok(ModelType::Masked(DistilBertForMaskedLM::load(vb, config)?))
-            }
-            Which::DistilBert => Ok(ModelType::UnMasked(DistilBertModel::load(vb, config)?)),
+            Which::DistilbertForMaskedLM => Ok(ModelType::Masked(
+                DistilBertForMaskedLM::load(vb, config)?.into(),
+            )),
+            Which::DistilBert => Ok(ModelType::UnMasked(
+                DistilBertModel::load(vb, config)?.into(),
+            )),
         }
     }
 }

candle-transformers/src/models/deepseek2.rs

@@ -869,8 +869,8 @@ impl Moe {
 }
 
 enum MoeOrMlp {
-    Moe(Moe),
-    Mlp(Mlp),
+    Moe(Box<Moe>),
+    Mlp(Box<Mlp>),
 }
 
 impl MoeOrMlp {
@@ -908,14 +908,17 @@ impl DecoderLayer {
             && layer_idx >= cfg.first_k_dense_replace
             && layer_idx % cfg.moe_layer_freq == 0
         {
-            MoeOrMlp::Moe(Moe::new(
-                cfg,
-                vb.pp("mlp"),
-                cfg.n_shared_experts,
-                cfg.n_routed_experts.unwrap(),
-            )?)
+            MoeOrMlp::Moe(
+                Moe::new(
+                    cfg,
+                    vb.pp("mlp"),
+                    cfg.n_shared_experts,
+                    cfg.n_routed_experts.unwrap(),
+                )?
+                .into(),
+            )
         } else {
-            MoeOrMlp::Mlp(Mlp::new(cfg, vb.pp("mlp"), None, None)?)
+            MoeOrMlp::Mlp(Mlp::new(cfg, vb.pp("mlp"), None, None)?.into())
         };
 
         Ok(Self {

candle-transformers/src/models/segment_anything/sam.rs

@@ -17,8 +17,8 @@ const CROP_NMS_THRESH: f32 = 0.7;
 
 #[derive(Debug)]
 enum ImageEncoder {
-    Original(ImageEncoderViT),
-    TinyViT(TinyViT),
+    Original(Box<ImageEncoderViT>),
+    TinyViT(Box<TinyViT>),
 }
 
 impl Module for ImageEncoder {
@@ -83,7 +83,7 @@ impl Sam {
         let pixel_std =
             Tensor::new(&[58.395f32, 57.12, 57.375], vb.device())?.reshape((3, 1, 1))?;
         Ok(Self {
-            image_encoder: ImageEncoder::Original(image_encoder),
+            image_encoder: ImageEncoder::Original(image_encoder.into()),
             prompt_encoder,
             mask_decoder,
             pixel_std,
@@ -114,7 +114,7 @@ impl Sam {
         let pixel_std =
             Tensor::new(&[58.395f32, 57.12, 57.375], vb.device())?.reshape((3, 1, 1))?;
         Ok(Self {
-            image_encoder: ImageEncoder::TinyViT(image_encoder),
+            image_encoder: ImageEncoder::TinyViT(image_encoder.into()),
             prompt_encoder,
             mask_decoder,
             pixel_std,

candle-transformers/src/models/stable_diffusion/ddim.rs

@@ -134,12 +134,7 @@ impl Scheduler for DDIMScheduler {
             timestep
         };
         // https://github.com/huggingface/diffusers/blob/6e099e2c8ce4c4f5c7318e970a8c093dc5c7046e/src/diffusers/schedulers/scheduling_ddim.py#L195
-        let prev_timestep = if timestep > self.step_ratio {
-            timestep - self.step_ratio
-        } else {
-            0
-        };
-
+        let prev_timestep = timestep.saturating_sub(self.step_ratio);
         let alpha_prod_t = self.alphas_cumprod[timestep];
         let alpha_prod_t_prev = self.alphas_cumprod[prev_timestep];
         let beta_prod_t = 1. - alpha_prod_t;