style: simplify string formatting for readability

candle-book/src/simplified.rs

@@ -123,7 +123,7 @@ async fn simplified() -> anyhow::Result<()> {
                 break;
             },
             Err(e) => {
-                println!("Error: {}", e);
+                println!("Error: {e}");
                 continue;
             }
         }
@@ -142,8 +142,8 @@ async fn simplified() -> anyhow::Result<()> {
         .argmax(D::Minus1)?
         .to_dtype(DType::F32)?
         .get(0).map(|x| x.to_scalar::<f32>())??;
-    println!("real_life_votes: {:?}", real_world_votes);
-    println!("neural_network_prediction_result: {:?}", result);
+    println!("real_life_votes: {real_world_votes:?}");
+    println!("neural_network_prediction_result: {result:?}");
 
     Ok(())
 

candle-core/benches/benchmarks/mod.rs

@@ -22,13 +22,13 @@ impl BenchDevice for Device {
                 #[cfg(feature = "cuda")]
                 return Ok(device.synchronize()?);
                 #[cfg(not(feature = "cuda"))]
-                panic!("Cuda device without cuda feature enabled: {:?}", device)
+                panic!("Cuda device without cuda feature enabled: {device:?}")
             }
             Device::Metal(device) => {
                 #[cfg(feature = "metal")]
                 return Ok(device.wait_until_completed()?);
                 #[cfg(not(feature = "metal"))]
-                panic!("Metal device without metal feature enabled: {:?}", device)
+                panic!("Metal device without metal feature enabled: {device:?}")
             }
         }
     }

candle-core/benches/benchmarks/qmatmul.rs

@@ -31,7 +31,7 @@ fn run_bench(c: &mut Criterion, device: &Device, dtype: GgmlDType) {
 
     let flops = b * m * n * k;
 
-    let mut group = c.benchmark_group(device.bench_name(format!("qmatmul_{:?}", dtype)));
+    let mut group = c.benchmark_group(device.bench_name(format!("qmatmul_{dtype:?}")));
     group.sample_size(200);
     group.throughput(Throughput::Bytes(flops as u64));
     group.bench_function("iter", move |b| {

candle-core/benches/benchmarks/unary.rs

@@ -40,7 +40,7 @@ fn criterion_benchmark(c: &mut Criterion) {
     let handler = BenchDeviceHandler::new().unwrap();
     for device in handler.devices {
         for dtype in [DType::F32, DType::BF16, DType::F16] {
-            let name = format!("sqrt_{:?}", dtype);
+            let name = format!("sqrt_{dtype:?}");
             run_unary_benchmark(c, &device, dtype, &name);
         }
     }

candle-core/src/display.rs

@@ -12,10 +12,10 @@ impl Tensor {
         let device_str = match self.device().location() {
             crate::DeviceLocation::Cpu => "".to_owned(),
             crate::DeviceLocation::Cuda { gpu_id } => {
-                format!(", cuda:{}", gpu_id)
+                format!(", cuda:{gpu_id}")
             }
             crate::DeviceLocation::Metal { gpu_id } => {
-                format!(", metal:{}", gpu_id)
+                format!(", metal:{gpu_id}")
             }
         };
 
@@ -502,10 +502,10 @@ impl std::fmt::Display for Tensor {
         let device_str = match self.device().location() {
             crate::DeviceLocation::Cpu => "".to_owned(),
             crate::DeviceLocation::Cuda { gpu_id } => {
-                format!(", cuda:{}", gpu_id)
+                format!(", cuda:{gpu_id}")
             }
             crate::DeviceLocation::Metal { gpu_id } => {
-                format!(", metal:{}", gpu_id)
+                format!(", metal:{gpu_id}")
             }
         };
 

candle-core/tests/quantized_tests.rs

@@ -378,12 +378,7 @@ fn compare_with_error(values: &[f32], expected: &[f32], tolerance: f32) {
 
         assert!(
             difference < tolerance,
-            "Error at index {}: value = {}, expected = {}. Difference = {} exceeds tolerance = {}.",
-            i,
-            value,
-            expected_value,
-            difference,
-            tolerance
+            "Error at index {i}: value = {value}, expected = {expected_value}. Difference = {difference} exceeds tolerance = {tolerance}."
         );
     }
 }

candle-examples/examples/clip/main.rs

@@ -95,7 +95,7 @@ pub fn main() -> anyhow::Result<()> {
     let (_logits_per_text, logits_per_image) = model.forward(&images, &input_ids)?;
     let softmax_image = softmax(&logits_per_image, 1)?;
     let softmax_image_vec = softmax_image.flatten_all()?.to_vec1::<f32>()?;
-    println!("softmax_image_vec: {:?}", softmax_image_vec);
+    println!("softmax_image_vec: {softmax_image_vec:?}");
     let probability_vec = softmax_image_vec
         .iter()
         .map(|v| v * 100.0)
@@ -105,7 +105,7 @@ pub fn main() -> anyhow::Result<()> {
         let start = i * probability_per_image;
         let end = start + probability_per_image;
         let prob = &probability_vec[start..end];
-        println!("\n\nResults for image: {}\n", img);
+        println!("\n\nResults for image: {img}\n");
         for (i, p) in prob.iter().enumerate() {
             println!("Probability: {:.4}% Text: {} ", p, vec_seq[i]);
         }

candle-examples/examples/codegeex4-9b/main.rs

@@ -70,7 +70,7 @@ impl TextGeneration {
         let start_gen = std::time::Instant::now();
 
         println!("\n start_gen");
-        println!("samplelen {}", sample_len);
+        println!("samplelen {sample_len}");
         let mut count = 0;
         let mut result = vec![];
         for index in 0..sample_len {
@@ -103,8 +103,7 @@ impl TextGeneration {
                 .expect("Token error");
             if self.verbose_prompt {
                 println!(
-                    "[Count: {}] [Raw Token: {}] [Decode Token: {}]",
-                    count, next_token, token
+                    "[Count: {count}] [Raw Token: {next_token}] [Decode Token: {token}]"
                 );
             }
             result.push(token);

candle-examples/examples/efficientvit/main.rs

@@ -30,7 +30,7 @@ impl Which {
             Self::M4 => "m4",
             Self::M5 => "m5",
         };
-        format!("timm/efficientvit_{}.r224_in1k", name)
+        format!("timm/efficientvit_{name}.r224_in1k")
     }
 
     fn config(&self) -> efficientvit::Config {

candle-examples/examples/fastvit/main.rs

@@ -32,7 +32,7 @@ impl Which {
             Self::SA36 => "sa36",
             Self::MA36 => "ma36",
         };
-        format!("timm/fastvit_{}.apple_in1k", name)
+        format!("timm/fastvit_{name}.apple_in1k")
     }
 
     fn config(&self) -> fastvit::Config {

candle-examples/examples/glm4/main.rs

@@ -108,8 +108,7 @@ impl TextGeneration {
                     .expect("Token error");
                 if self.verbose_prompt {
                     println!(
-                        "[Count: {}] [Raw Token: {}] [Decode Token: {}]",
-                        count, next_token, token
+                        "[Count: {count}] [Raw Token: {next_token}] [Decode Token: {token}]"
                     );
                 }
                 result.push(token);

candle-examples/examples/hiera/main.rs

@@ -30,7 +30,7 @@ impl Which {
             Self::Large => "large",
             Self::Huge => "huge",
         };
-        format!("timm/hiera_{}_224.mae_in1k_ft_in1k", name)
+        format!("timm/hiera_{name}_224.mae_in1k_ft_in1k")
     }
 
     fn config(&self) -> hiera::Config {

candle-examples/examples/llava/main.rs

@@ -207,8 +207,7 @@ fn main() -> Result<()> {
 
     println!("generating conv template");
     let image_token_se = format!(
-        "{}{}{}",
-        DEFAULT_IM_START_TOKEN, DEFAULT_IMAGE_TOKEN, DEFAULT_IM_END_TOKEN
+        "{DEFAULT_IM_START_TOKEN}{DEFAULT_IMAGE_TOKEN}{DEFAULT_IM_END_TOKEN}"
     );
     let qs = if args.prompt.contains(IMAGE_PLACEHOLDER) {
         if llava_config.mm_use_im_start_end {

candle-examples/examples/mamba-minimal/main.rs

@@ -123,7 +123,7 @@ enum Which {
 
 impl std::fmt::Display for Which {
     fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        write!(f, "{:?}", self)
+        write!(f, "{self:?}")
     }
 }
 

candle-examples/examples/mamba/main.rs

@@ -135,7 +135,7 @@ enum Which {
 
 impl std::fmt::Display for Which {
     fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        write!(f, "{:?}", self)
+        write!(f, "{self:?}")
     }
 }
 

candle-examples/examples/mobileclip/main.rs

@@ -25,7 +25,7 @@ impl Which {
             Self::S1 => "S1",
             Self::S2 => "S2",
         };
-        format!("apple/MobileCLIP-{}-OpenCLIP", name)
+        format!("apple/MobileCLIP-{name}-OpenCLIP")
     }
 
     fn config(&self) -> mobileclip::MobileClipConfig {
@@ -107,7 +107,7 @@ pub fn main() -> anyhow::Result<()> {
     let (_logits_per_text, logits_per_image) = model.forward(&images, &input_ids)?;
     let softmax_image = softmax(&logits_per_image, 1)?;
     let softmax_image_vec = softmax_image.flatten_all()?.to_vec1::<f32>()?;
-    println!("softmax_image_vec: {:?}", softmax_image_vec);
+    println!("softmax_image_vec: {softmax_image_vec:?}");
     let probability_vec = softmax_image_vec
         .iter()
         .map(|v| v * 100.0)
@@ -118,7 +118,7 @@ pub fn main() -> anyhow::Result<()> {
         let start = i * probability_per_image;
         let end = start + probability_per_image;
         let prob = &probability_vec[start..end];
-        println!("\n\nResults for image: {}\n", img);
+        println!("\n\nResults for image: {img}\n");
 
         for (i, p) in prob.iter().enumerate() {
             println!("Probability: {:.4}% Text: {}", p, vec_seq[i]);

candle-examples/examples/mobilenetv4/main.rs

@@ -28,7 +28,7 @@ impl Which {
             Self::Large => "conv_large.e600_r384",
             Self::HybridLarge => "hybrid_large.ix_e600_r384",
         };
-        format!("timm/mobilenetv4_{}_in1k", name)
+        format!("timm/mobilenetv4_{name}_in1k")
     }
 
     fn resolution(&self) -> u32 {

candle-examples/examples/mobileone/main.rs

@@ -28,7 +28,7 @@ impl Which {
             Self::S3 => "s3",
             Self::S4 => "s4",
         };
-        format!("timm/mobileone_{}.apple_in1k", name)
+        format!("timm/mobileone_{name}.apple_in1k")
     }
 
     fn config(&self) -> mobileone::Config {

candle-examples/examples/moondream/main.rs

@@ -106,7 +106,7 @@ impl TextGeneration {
                     }
                 };
                 load_t = start_gen.elapsed();
-                println!("load_t: {:?}", load_t);
+                println!("load_t: {load_t:?}");
                 logits
             };
             let logits = logits.squeeze(0)?.to_dtype(DType::F32)?;

candle-examples/examples/paligemma/main.rs

@@ -253,7 +253,7 @@ fn main() -> Result<()> {
         .to_device(&device)?
         .to_dtype(dtype)?
         .unsqueeze(0)?;
-    println!("loaded image with shape {:?}", image);
+    println!("loaded image with shape {image:?}");
     let start = std::time::Instant::now();
     let vb = unsafe { VarBuilder::from_mmaped_safetensors(&filenames, dtype, &device)? };
     let model = Model::new(&config, vb)?;

candle-examples/examples/pixtral/main.rs

@@ -295,7 +295,7 @@ fn main() -> Result<()> {
         )?
     };
     let image = image.to_device(&device)?.unsqueeze(0)?;
-    println!("loaded image with shape {:?}", image);
+    println!("loaded image with shape {image:?}");
     let vb = unsafe { VarBuilder::from_mmaped_safetensors(&filenames, dtype, &device)? };
 
     if args.vision_only {

candle-examples/examples/quantized-phi/main.rs

@@ -144,7 +144,7 @@ impl Args {
 
 fn format_size(size_in_bytes: usize) -> String {
     if size_in_bytes < 1_000 {
-        format!("{}B", size_in_bytes)
+        format!("{size_in_bytes}B")
     } else if size_in_bytes < 1_000_000 {
         format!("{:.2}KB", size_in_bytes as f64 / 1e3)
     } else if size_in_bytes < 1_000_000_000 {

candle-examples/examples/quantized-qwen2-instruct/main.rs

@@ -151,7 +151,7 @@ impl Args {
 
 fn format_size(size_in_bytes: usize) -> String {
     if size_in_bytes < 1_000 {
-        format!("{}B", size_in_bytes)
+        format!("{size_in_bytes}B")
     } else if size_in_bytes < 1_000_000 {
         format!("{:.2}KB", size_in_bytes as f64 / 1e3)
     } else if size_in_bytes < 1_000_000_000 {
@@ -213,8 +213,7 @@ fn main() -> anyhow::Result<()> {
     let mut tos = TokenOutputStream::new(tokenizer);
     let prompt_str = args.prompt.unwrap_or_else(|| DEFAULT_PROMPT.to_string());
     let prompt_str = format!(
-        "<|im_start|>user\n{}<|im_end|>\n<|im_start|>assistant\n",
-        prompt_str
+        "<|im_start|>user\n{prompt_str}<|im_end|>\n<|im_start|>assistant\n"
     );
     print!("formatted instruct prompt: {}", &prompt_str);
     let tokens = tos

candle-examples/examples/quantized/main.rs

@@ -364,7 +364,7 @@ impl Args {
 
 fn format_size(size_in_bytes: usize) -> String {
     if size_in_bytes < 1_000 {
-        format!("{}B", size_in_bytes)
+        format!("{size_in_bytes}B")
     } else if size_in_bytes < 1_000_000 {
         format!("{:.2}KB", size_in_bytes as f64 / 1e3)
     } else if size_in_bytes < 1_000_000_000 {

candle-examples/examples/repvgg/main.rs

@@ -38,7 +38,7 @@ impl Which {
             Self::B2G4 => "b2g4",
             Self::B3G4 => "b3g4",
         };
-        format!("timm/repvgg_{}.rvgg_in1k", name)
+        format!("timm/repvgg_{name}.rvgg_in1k")
     }
 
     fn config(&self) -> repvgg::Config {

candle-examples/examples/rwkv/main.rs

@@ -134,7 +134,7 @@ enum Which {
 
 impl std::fmt::Display for Which {
     fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        write!(f, "{:?}", self)
+        write!(f, "{self:?}")
     }
 }
 

candle-examples/examples/segformer/main.rs

@@ -57,16 +57,16 @@ enum Commands {
 }
 
 fn get_vb_and_config(model_name: String, device: &Device) -> anyhow::Result<(VarBuilder, Config)> {
-    println!("loading model {} via huggingface hub", model_name);
+    println!("loading model {model_name} via huggingface hub");
     let api = hf_hub::api::sync::Api::new()?;
     let api = api.model(model_name.clone());
     let model_file = api.get("model.safetensors")?;
-    println!("model {} downloaded and loaded", model_name);
+    println!("model {model_name} downloaded and loaded");
     let vb =
         unsafe { VarBuilder::from_mmaped_safetensors(&[model_file], candle::DType::F32, device)? };
     let config = std::fs::read_to_string(api.get("config.json")?)?;
     let config: Config = serde_json::from_str(&config)?;
-    println!("{:?}", config);
+    println!("{config:?}");
     Ok((vb, config))
 }
 
@@ -138,7 +138,7 @@ fn classification_task(args: ClassificationArgs, device: &Device) -> anyhow::Res
         classification.to_vec1::<f32>()?
     );
     let label_id = classification.argmax(0)?.to_scalar::<u32>()?;
-    let label_id = format!("{}", label_id);
+    let label_id = format!("{label_id}");
     println!("label: {}", config.id2label[&label_id]);
     Ok(())
 }

candle-examples/examples/siglip/main.rs

@@ -89,7 +89,7 @@ pub fn main() -> anyhow::Result<()> {
     let (_logits_per_text, logits_per_image) = model.forward(&images, &input_ids)?;
     let softmax_image = softmax(&logits_per_image, 1)?;
     let softmax_image_vec = softmax_image.flatten_all()?.to_vec1::<f32>()?;
-    println!("softmax_image_vec: {:?}", softmax_image_vec);
+    println!("softmax_image_vec: {softmax_image_vec:?}");
     let probability_vec = softmax_image_vec
         .iter()
         .map(|v| v * 100.0)
@@ -99,7 +99,7 @@ pub fn main() -> anyhow::Result<()> {
         let start = i * probability_per_image;
         let end = start + probability_per_image;
         let prob = &probability_vec[start..end];
-        println!("\n\nResults for image: {}\n", img);
+        println!("\n\nResults for image: {img}\n");
         for (i, p) in prob.iter().enumerate() {
             println!("Probability: {:.4}% Text: {} ", p, vec_seq[i]);
         }

candle-examples/examples/splade/main.rs

@@ -73,7 +73,7 @@ fn main() -> Result<()> {
             Err(_) => match repo.get("pytorch_model.bin") {
                 Ok(pytorch_model) => pytorch_model,
                 Err(e) => {
-                    return Err(anyhow::Error::msg(format!("Model weights not found. The weights should either be a `model.safetensors` or `pytorch_model.bin` file.  Error: {}", e)));
+                    return Err(anyhow::Error::msg(format!("Model weights not found. The weights should either be a `model.safetensors` or `pytorch_model.bin` file.  Error: {e}")));
                 }
             },
         },

candle-examples/examples/trocr/main.rs

@@ -93,7 +93,7 @@ pub fn main() -> anyhow::Result<()> {
                 .get("model.safetensors")?
             }
         };
-        println!("model: {:?}", model);
+        println!("model: {model:?}");
         unsafe { VarBuilder::from_mmaped_safetensors(&[model], DType::F32, &device)? }
     };