Clippy

Author: EricLBuehler

mistralrs-core/src/vision_models/conformer/encoder.rs

@@ -1,3 +1,5 @@
+#![allow(clippy::cast_possible_truncation, clippy::cast_precision_loss)]
+
 use std::sync::Arc;
 
 use candle_core::{IndexOp, Result, Tensor, D};
@@ -340,11 +342,7 @@ impl ConvModule {
 
         let fix_len1;
         let ext_pw_conv_1d = if cfg.causal {
-            if cfg.ext_pw_kernel_size > 1 {
-                fix_len1 = true;
-            } else {
-                fix_len1 = false;
-            }
+            fix_len1 = cfg.ext_pw_kernel_size > 1;
             layers::conv1d(
                 cfg.attention_dim,
                 cfg.ext_pw_out_channel,
@@ -383,7 +381,7 @@ impl ConvModule {
             None
         };
 
-        assert_eq!(cfg.linear_glu_in_convm, false);
+        assert!(!cfg.linear_glu_in_convm);
         let glu = GLUPointWiseConv::new(cfg, vb.pp("glu"))?;
 
         Ok(Self {

mistralrs-core/src/vision_models/conformer/nemo.rs

@@ -1,3 +1,5 @@
+#![allow(clippy::cast_possible_truncation, clippy::cast_precision_loss)]
+
 use std::sync::Arc;
 
 use candle_core::{Result, Tensor};
@@ -29,7 +31,7 @@ impl NemoConvSubsampling {
         let kernel_size = 3;
         let ceil_mode = false;
 
-        assert_eq!(cfg.is_causal, false);
+        assert!(!cfg.is_causal);
         assert_eq!(cfg.subsampling, "dw_striding");
 
         let left_padding = (kernel_size - 1) / 2;
@@ -50,7 +52,7 @@ impl NemoConvSubsampling {
                 kernel_size,
                 Conv2dConfig {
                     padding: left_padding,
-                    stride: stride,
+                    stride,
                     dilation: 1,
                     groups: 1,
                 },
@@ -69,7 +71,7 @@ impl NemoConvSubsampling {
                     kernel_size,
                     Conv2dConfig {
                         padding: left_padding,
-                        stride: stride,
+                        stride,
                         dilation: 1,
                         groups: in_channels,
                     },

mistralrs-core/src/vision_models/conformer/pos_embed.rs

@@ -1,3 +1,5 @@
+#![allow(clippy::cast_possible_truncation, clippy::cast_precision_loss)]
+
 use candle_core::{DType, Device, IndexOp, Result, Tensor, D};
 use candle_nn::{Embedding, Module};
 use mistralrs_quant::ShardedVarBuilder;

mistralrs-core/src/vision_models/phi4/inputs_processor.rs

@@ -46,6 +46,8 @@ pub(crate) const DYHD_BASE_RESOLUTION: usize = 448;
 
 const AUDIO_FEATURE_SIZE: usize = 80; // mel bins
 
+type AudioProcessingResult = Result<(Option<Tensor>, Option<Vec<usize>>, Option<Tensor>)>;
+
 // Input processor
 pub struct Phi4MMInputsProcessor {
     audio_compression_rate: usize,
@@ -648,16 +650,26 @@ impl Phi4MMInputsProcessor {
             let right_bin = bin_centers[m + 2];
 
             // Left slope
-            for bin in left_bin..center_bin {
+            for (bin, filter) in filter
+                .iter_mut()
+                .enumerate()
+                .take(center_bin)
+                .skip(left_bin)
+            {
                 if bin < bank_width {
-                    filter[bin] = (bin - left_bin) as f32 / (center_bin - left_bin) as f32;
+                    *filter = (bin - left_bin) as f32 / (center_bin - left_bin) as f32;
                 }
             }
 
             // Right slope
-            for bin in center_bin..right_bin {
+            for (bin, filter) in filter
+                .iter_mut()
+                .enumerate()
+                .take(right_bin)
+                .skip(center_bin)
+            {
                 if bin < bank_width {
-                    filter[bin] = (right_bin - bin) as f32 / (right_bin - center_bin) as f32;
+                    *filter = (right_bin - bin) as f32 / (right_bin - center_bin) as f32;
                 }
             }
 
@@ -710,13 +722,11 @@ impl Phi4MMInputsProcessor {
         &self,
         input_seqs: &[&mut Sequence],
         device: &Device,
-    ) -> Result<(Option<Tensor>, Option<Vec<usize>>, Option<Tensor>)> {
+    ) -> AudioProcessingResult {
         // Check if any sequence has audio tokens
-        let has_audio_tokens = input_seqs.iter().any(|seq| {
-            seq.get_toks()
-                .iter()
-                .any(|&token| token == AUDIO_SPECIAL_TOKEN_ID as u32)
-        });
+        let has_audio_tokens = input_seqs
+            .iter()
+            .any(|seq| seq.get_toks().contains(&(AUDIO_SPECIAL_TOKEN_ID as u32)));
 
         if !has_audio_tokens {
             return Ok((None, None, None));
@@ -728,10 +738,7 @@ impl Phi4MMInputsProcessor {
 
         // Process audio for each sequence that needs it
         for seq in input_seqs.iter() {
-            let has_audio = seq
-                .get_toks()
-                .iter()
-                .any(|&token| token == AUDIO_SPECIAL_TOKEN_ID as u32);
+            let has_audio = seq.get_toks().contains(&(AUDIO_SPECIAL_TOKEN_ID as u32));
 
             if has_audio {
                 // Load dummy audio (TODO: make this per-sequence)

mistralrs-core/src/vision_models/phi4/mm_embedding.rs

@@ -56,6 +56,7 @@ impl Phi4MMImageAudioEmbedding {
         })
     }
 
+    #[allow(clippy::too_many_arguments)]
     pub fn forward(
         &self,
         input_ids: &Tensor,