update fmt

src/models/common/mod.rs

@@ -3,8 +3,8 @@ use candle_core::{D, Tensor};
 use candle_nn::{
     Activation, BatchNorm, BatchNormConfig, Conv1d, Conv1dConfig, Conv2d, Conv2dConfig, Embedding,
     LayerNorm, LayerNormConfig, Linear, Module, RmsNorm, VarBuilder, batch_norm, conv1d,
-    conv1d_no_bias, conv2d, conv2d_no_bias, embedding, layer_norm, linear_b,
-    linear_no_bias, rms_norm,
+    conv1d_no_bias, conv2d, conv2d_no_bias, embedding, layer_norm, linear_b, linear_no_bias,
+    rms_norm,
 };
 use rayon::iter::{IndexedParallelIterator, IntoParallelRefIterator, ParallelIterator};
 

src/models/deepseek_ocr/model.rs

@@ -1,7 +1,10 @@
 use anyhow::Result;
 use candle_core::{D, IndexOp, Tensor};
 use candle_nn::{
-    Activation, Conv2d, Embedding, Init, LayerNorm, Linear, Module, RmsNorm, VarBuilder, embedding, linear, linear_b, linear_no_bias, ops::{sigmoid, softmax}, rms_norm
+    Activation, Conv2d, Embedding, Init, LayerNorm, Linear, Module, RmsNorm, VarBuilder, embedding,
+    linear, linear_b, linear_no_bias,
+    ops::{sigmoid, softmax},
+    rms_norm,
 };
 use candle_transformers::models::segment_anything::LayerNorm2d;
 
@@ -77,7 +80,7 @@ impl Attention {
         let head_dim = dim / num_heads;
         let scaling = 1.0 / (head_dim as f64).sqrt();
         let qkv = linear_b(dim, dim * 3, qkv_bias, vb.pp("qkv"))?;
-        
+
         let proj = linear(dim, dim, vb.pp("proj"))?;
         let mut rel_pos_h = None;
         let mut rel_pos_w = None;

src/models/qwen3/model.rs

@@ -1,8 +1,7 @@
 use anyhow::Result;
 use candle_core::Tensor;
 use candle_nn::{
-    Embedding, Linear, Module, RmsNorm, VarBuilder, embedding, linear_b, linear_no_bias,
-    rms_norm,
+    Embedding, Linear, Module, RmsNorm, VarBuilder, embedding, linear_b, linear_no_bias, rms_norm,
 };
 
 use crate::{