update fmt

src/models/glm_ocr/config.rs

@@ -42,7 +42,6 @@ pub struct GlmOcrRopeParameters {
     pub rope_theta: f32,
 }
 
-
 /// Text decoder configuration for GLM-OCR.
 #[derive(Debug, Clone, PartialEq, Deserialize, Default)]
 pub struct GlmOcrTextConfig {

src/models/glm_ocr/generate.rs

@@ -5,7 +5,6 @@ use aha_openai_dive::v1::resources::chat::{
 use anyhow::{Result, anyhow};
 use candle_core::{DType, Device, IndexOp, Tensor};
 use candle_nn::VarBuilder;
-use candle_transformers::utils::apply_repeat_penalty;
 use rocket::async_stream::stream;
 use rocket::futures::Stream;
 
@@ -20,7 +19,10 @@ use crate::{
         },
     },
     tokenizer::TokenizerModel,
-    utils::{build_completion_chunk_response, build_completion_response, extract_user_text, find_type_files, get_device, get_dtype, get_logit_processor, img_utils::extract_image_url},
+    utils::{
+        build_completion_chunk_response, build_completion_response, extract_user_text,
+        find_type_files, get_device, get_dtype, get_logit_processor, img_utils::extract_image_url,
+    },
 };
 
 pub struct GlmOcrGenerateModel {
@@ -30,7 +32,6 @@ pub struct GlmOcrGenerateModel {
     model: GlmOcrModel,
     device: Device,
     eos_token_ids: Vec<u32>,
-    generation_config: GlmOcrGenerationConfig,
     model_name: String,
     image_token_id: u32,
     image_start_token_id: u32,
@@ -64,7 +65,6 @@ impl GlmOcrGenerateModel {
             model,
             device,
             eos_token_ids: generation_config.eos_token_id.clone(),
-            generation_config,
             model_name: "glm-ocr".to_string(),
             image_token_id: cfg.image_token_id,
             image_start_token_id: cfg.image_start_token_id,
@@ -136,7 +136,7 @@ impl GenerateModel for GlmOcrGenerateModel {
                 },
                 seqlen_offset,
             )?;
-            let logits = logits.i((0, seq_len - 1, ..))?.to_dtype(DType::F32)?;            
+            let logits = logits.i((0, seq_len - 1, ..))?.to_dtype(DType::F32)?;
             let next_token = logit_processor.sample(&logits)?;
 
             generate.push(next_token);
@@ -215,7 +215,7 @@ impl GenerateModel for GlmOcrGenerateModel {
                     seqlen_offset,
                 ).map_err(|e| anyhow!(format!("forward error: {e}")))?;
                 let logits = logits.i((0, seq_len - 1, ..)).map_err(|e| anyhow!(format!("index error: {e}")))?.to_dtype(DType::F32).map_err(|e| anyhow!(format!("dtype error: {e}")))?;
-                
+
                 let next_token = logit_processor.sample(&logits).map_err(|e| anyhow!(format!("sample error: {e}")))?;
                 generated.push(next_token);
 
@@ -254,6 +254,3 @@ impl GenerateModel for GlmOcrGenerateModel {
         Ok(Box::new(Box::pin(stream)))
     }
 }
-
-
-

src/models/glm_ocr/model.rs

@@ -10,9 +10,7 @@ use candle_nn::{
 use crate::{
     models::{
         common::GateUpDownMLP,
-        glm_ocr::config::{
+        glm_ocr::config::{GlmOcrConfig, GlmOcrTextConfig, GlmOcrVisionConfig},
-            GlmOcrConfig, GlmOcrTextConfig, GlmOcrVisionConfig,
-        },
     },
     position_embed::rope::{apply_rotary_pos_emb_vision, glm_ocr_apply_rotary_pos_emb},
     utils::tensor_utils::{prepare_causal_attention_mask, repeat_kv},

src/models/glm_ocr/processor.rs

@@ -87,11 +87,7 @@ impl GlmOcrProcessor {
         )?;
 
         // Resize image
-        let img = img.resize_exact(
+        let img = img.resize_exact(target_w, target_h, image::imageops::FilterType::Lanczos3);
-            target_w,
-            target_h,
-            image::imageops::FilterType::Lanczos3,
-        );
 
         let target_h = target_h as usize;
         let target_w = target_w as usize;
@@ -118,7 +114,8 @@ impl GlmOcrProcessor {
         let grid_h = target_h / self.patch_size;
         let grid_w = target_w / self.patch_size;
         let channels = 3;
-        let tensor = tensor.reshape((grid_h, self.patch_size, grid_w, self.patch_size, channels))?;
+        let tensor =
+            tensor.reshape((grid_h, self.patch_size, grid_w, self.patch_size, channels))?;
         let tensor = tensor.permute((0, 2, 4, 1, 3))?;
         let num_patches = grid_h * grid_w;
         let tensor = tensor.reshape((num_patches, channels, self.patch_size, self.patch_size))?;

src/utils/mod.rs

@@ -731,7 +731,7 @@ pub fn extract_user_text(mes: &ChatCompletionParameters) -> Result<String> {
                             }
                         }
                     }
-                },
+                }
                 _ => {}
             }
         }

src/utils/video_utils.rs

@@ -58,7 +58,6 @@ pub fn video_smart_resize(
     Ok((h_bar, w_bar))
 }
 
-
 // #[allow(unused)]
 // fn save_file(
 //     frame: &ffmpeg::frame::Video,