Clippy fixes for 1.81.0. (#2461)

* Clippy fixes for 1.81.0. * Another fix.
huggingface · Sep 5, 2024 · e326121 · e326121
1 parent c02b7c3
commit e326121
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Showing 17 changed files with 28 additions and 29 deletions.
diff --git a/candle-examples/examples/musicgen/musicgen_model.rs b/candle-examples/examples/musicgen/musicgen_model.rs
@@ -284,11 +284,11 @@ impl MusicgenDecoder {
  };
  let embed_dim = cfg.vocab_size + 1;
  let embed_tokens = (0..cfg.num_codebooks)
- .map(|i| embedding(embed_dim, h, vb.pp(&format!("embed_tokens.{i}"))))
+ .map(|i| embedding(embed_dim, h, vb.pp(format!("embed_tokens.{i}"))))
  .collect::<Result<Vec<_>>>()?;
  let embed_positions = MusicgenSinusoidalPositionalEmbedding::load(vb.clone(), cfg)?;
  let layers = (0..cfg.num_hidden_layers)
- .map(|i| MusicgenDecoderLayer::load(vb.pp(&format!("layers.{i}")), cfg))
+ .map(|i| MusicgenDecoderLayer::load(vb.pp(format!("layers.{i}")), cfg))
  .collect::<Result<Vec<_>>>()?;
  let layer_norm = layer_norm(h, 1e-5, vb.pp("layer_norm"))?;
  Ok(Self {
@@ -341,7 +341,7 @@ impl MusicgenForCausalLM {
  let h = cfg.hidden_size;
  let decoder = MusicgenDecoder::load(vb.pp("model.decoder"), cfg)?;
  let lm_heads = (0..cfg.num_codebooks)
- .map(|i| linear_no_bias(h, cfg.vocab_size, vb.pp(&format!("lm_heads.{i}"))))
+ .map(|i| linear_no_bias(h, cfg.vocab_size, vb.pp(format!("lm_heads.{i}"))))
  .collect::<Result<Vec<_>>>()?;
  Ok(Self {
  decoder,

diff --git a/candle-examples/examples/silero-vad/main.rs b/candle-examples/examples/silero-vad/main.rs
@@ -8,7 +8,6 @@ use anyhow::Result;
 use clap::Parser;
 
 use candle::{DType, Tensor};
-use candle_onnx;
 
 #[derive(Clone, Debug, Copy, PartialEq, Eq, clap::ValueEnum)]
 enum Which {

diff --git a/candle-examples/examples/yolo-v3/darknet.rs b/candle-examples/examples/yolo-v3/darknet.rs
@@ -123,7 +123,7 @@ fn conv(vb: VarBuilder, index: usize, p: usize, b: &Block) -> Result<(usize, Bl)
  let padding = if pad != 0 { (size - 1) / 2 } else { 0 };
  let (bn, bias) = match b.parameters.get("batch_normalize") {
  Some(p) if p.parse::<usize>()? != 0 => {
- let bn = batch_norm(filters, 1e-5, vb.pp(&format!("batch_norm_{index}")))?;
+ let bn = batch_norm(filters, 1e-5, vb.pp(format!("batch_norm_{index}")))?;
  (Some(bn), false)
  }
  Some(_) | None => (None, true),
@@ -135,9 +135,9 @@ fn conv(vb: VarBuilder, index: usize, p: usize, b: &Block) -> Result<(usize, Bl)
  dilation: 1,
  };
  let conv = if bias {
- conv2d(p, filters, size, conv_cfg, vb.pp(&format!("conv_{index}")))?
+ conv2d(p, filters, size, conv_cfg, vb.pp(format!("conv_{index}")))?
  } else {
- conv2d_no_bias(p, filters, size, conv_cfg, vb.pp(&format!("conv_{index}")))?
+ conv2d_no_bias(p, filters, size, conv_cfg, vb.pp(format!("conv_{index}")))?
  };
  let leaky = match activation {
  "leaky" => true,

diff --git a/candle-examples/examples/yolo-v8/model.rs b/candle-examples/examples/yolo-v8/model.rs
@@ -161,7 +161,7 @@ impl C2f {
  let cv2 = ConvBlock::load(vb.pp("cv2"), (2 + n) * c, c2, 1, 1, None)?;
  let mut bottleneck = Vec::with_capacity(n);
  for idx in 0..n {
- let b = Bottleneck::load(vb.pp(&format!("bottleneck.{idx}")), c, c, shortcut)?;
+ let b = Bottleneck::load(vb.pp(format!("bottleneck.{idx}")), c, c, shortcut)?;
  bottleneck.push(b)
  }
  Ok(Self {

diff --git a/candle-transformers/src/models/bert.rs b/candle-transformers/src/models/bert.rs
@@ -419,7 +419,7 @@ struct BertEncoder {
 impl BertEncoder {
  fn load(vb: VarBuilder, config: &Config) -> Result<Self> {
  let layers = (0..config.num_hidden_layers)
- .map(|index| BertLayer::load(vb.pp(&format!("layer.{index}")), config))
+ .map(|index| BertLayer::load(vb.pp(format!("layer.{index}")), config))
  .collect::<Result<Vec<_>>>()?;
  let span = tracing::span!(tracing::Level::TRACE, "encoder");
  Ok(BertEncoder { layers, span })
@@ -454,8 +454,8 @@ impl BertModel {
  (Err(err), _) | (_, Err(err)) => {
  if let Some(model_type) = &config.model_type {
  if let (Ok(embeddings), Ok(encoder)) = (
- BertEmbeddings::load(vb.pp(&format!("{model_type}.embeddings")), config),
- BertEncoder::load(vb.pp(&format!("{model_type}.encoder")), config),
+ BertEmbeddings::load(vb.pp(format!("{model_type}.embeddings")), config),
+ BertEncoder::load(vb.pp(format!("{model_type}.encoder")), config),
  ) {
  (embeddings, encoder)
  } else {

diff --git a/candle-transformers/src/models/bigcode.rs b/candle-transformers/src/models/bigcode.rs
@@ -298,7 +298,7 @@ impl GPTBigCode {
  let wte = embedding(cfg.vocab_size, hidden_size, vb_t.pp("wte"))?;
  let wpe = embedding(cfg.max_position_embeddings, hidden_size, vb_t.pp("wpe"))?;
  let blocks = (0..cfg.num_hidden_layers)
- .map(|i| Block::load(vb_t.pp(&format!("h.{i}")), &cfg))
+ .map(|i| Block::load(vb_t.pp(format!("h.{i}")), &cfg))
  .collect::<Result<Vec<_>>>()?;
  let ln_f = layer_norm(hidden_size, cfg.layer_norm_epsilon, vb_t.pp("ln_f"))?;
  let lm_head = linear(hidden_size, cfg.vocab_size, false, vb_t.pp("wte"))?;

diff --git a/candle-transformers/src/models/distilbert.rs b/candle-transformers/src/models/distilbert.rs
@@ -275,7 +275,7 @@ struct Transformer {
 impl Transformer {
  fn load(vb: VarBuilder, config: &Config) -> Result<Self> {
  let layers = (0..config.n_layers)
- .map(|index| TransformerBlock::load(vb.pp(&format!("layer.{index}")), config))
+ .map(|index| TransformerBlock::load(vb.pp(format!("layer.{index}")), config))
  .collect::<Result<Vec<_>>>()?;
  let span = tracing::span!(tracing::Level::TRACE, "encoder");
  Ok(Transformer { layers, span })
@@ -311,8 +311,8 @@ impl DistilBertModel {
  (Err(err), _) | (_, Err(err)) => {
  if let Some(model_type) = &config.model_type {
  if let (Ok(embeddings), Ok(encoder)) = (
- Embeddings::load(vb.pp(&format!("{model_type}.embeddings")), config),
- Transformer::load(vb.pp(&format!("{model_type}.transformer")), config),
+ Embeddings::load(vb.pp(format!("{model_type}.embeddings")), config),
+ Transformer::load(vb.pp(format!("{model_type}.transformer")), config),
  ) {
  (embeddings, encoder)
  } else {

diff --git a/candle-transformers/src/models/falcon.rs b/candle-transformers/src/models/falcon.rs
@@ -448,7 +448,7 @@ impl Falcon {
  vb.pp("transformer.word_embeddings"),
  )?;
  let blocks = (0..cfg.num_hidden_layers)
- .map(|i| FalconDecoderLayer::load(vb.pp(&format!("transformer.h.{i}")), &cfg))
+ .map(|i| FalconDecoderLayer::load(vb.pp(format!("transformer.h.{i}")), &cfg))
  .collect::<Result<Vec<_>>>()?;
  let ln_f = layer_norm(
  cfg.hidden_size,

diff --git a/candle-transformers/src/models/jina_bert.rs b/candle-transformers/src/models/jina_bert.rs
@@ -344,7 +344,7 @@ impl BertEncoder {
  candle::bail!("only alibi is supported as a position-embedding-type")
  }
  let layers = (0..cfg.num_hidden_layers)
- .map(|index| BertLayer::new(vb.pp(&format!("layer.{index}")), cfg))
+ .map(|index| BertLayer::new(vb.pp(format!("layer.{index}")), cfg))
  .collect::<Result<Vec<_>>>()?;
  let span = tracing::span!(tracing::Level::TRACE, "encoder");
  let alibi = build_alibi_bias(cfg)?.to_device(vb.device())?;

diff --git a/candle-transformers/src/models/llama.rs b/candle-transformers/src/models/llama.rs
@@ -507,7 +507,7 @@ impl Llama {
  let lm_head = linear(cfg.hidden_size, cfg.vocab_size, vb.pp("lm_head"))?;
  let ln_f = RmsNorm::new(cfg.hidden_size, cfg.rms_norm_eps, vb.pp("model.norm"))?;
  let blocks: Vec<_> = (0..cfg.num_hidden_layers)
- .map(|i| Block::load(vb.pp(&format!("model.layers.{i}")), cfg).unwrap())
+ .map(|i| Block::load(vb.pp(format!("model.layers.{i}")), cfg).unwrap())
  .collect();
 
  Ok(Self {

diff --git a/candle-transformers/src/models/llama2_c.rs b/candle-transformers/src/models/llama2_c.rs
@@ -354,7 +354,7 @@ impl Llama {
  let lm_head = linear(cfg.dim, cfg.vocab_size, vb.pp("lm_head"))?;
  let ln_f = rms_norm(cfg.dim, cfg.norm_eps, vb.pp("model.norm"))?;
  let blocks: Vec<_> = (0..cfg.n_layers)
- .map(|i| Block::load(vb.pp(&format!("model.layers.{i}")), &cfg).unwrap())
+ .map(|i| Block::load(vb.pp(format!("model.layers.{i}")), &cfg).unwrap())
  .collect();
  Ok(Self {
  wte,

diff --git a/candle-transformers/src/models/moondream.rs b/candle-transformers/src/models/moondream.rs
@@ -167,7 +167,7 @@ impl VisionTransformer {
  let blocks = (0..cfg.num_blocks)
  .map(|i| {
  VitBlock::new(
- vb.pp(&format!("blocks.{}", i)),
+ vb.pp(format!("blocks.{}", i)),
  cfg.embed_dim,
  cfg.num_heads,
  cfg,

diff --git a/candle-transformers/src/models/segformer.rs b/candle-transformers/src/models/segformer.rs
@@ -404,7 +404,7 @@ impl SegformerEncoder {
  stride,
  num_channels,
  hidden_size,
- vb.pp(&format!("patch_embeddings.{}", i)),
+ vb.pp(format!("patch_embeddings.{}", i)),
  )?);
  let mut layers = Vec::with_capacity(config.depths[i]);
  for j in 0..config.depths[i] {
@@ -417,14 +417,14 @@ impl SegformerEncoder {
  num_attention_heads,
  sequence_reduction_ratio,
  mlp_ratio,
- vb.pp(&format!("block.{}.{}", i, j)),
+ vb.pp(format!("block.{}.{}", i, j)),
  )?);
  }
  blocks.push(layers);
  layer_norms.push(layer_norm(
  hidden_size,
  config.layer_norm_eps,
- vb.pp(&format!("layer_norm.{}", i)),
+ vb.pp(format!("layer_norm.{}", i)),
  )?);
  }
  Ok(Self {
@@ -507,7 +507,7 @@ impl SegformerDecodeHead {
  linear_c.push(SegformerMLP::new(
  config,
  hidden_size,
- vb.pp(&format!("linear_c.{}", i)),
+ vb.pp(format!("linear_c.{}", i)),
  )?);
  }
  let linear_fuse = conv2d_no_bias(

diff --git a/candle-transformers/src/models/t5.rs b/candle-transformers/src/models/t5.rs
@@ -659,7 +659,7 @@ struct T5Stack {
 impl T5Stack {
  fn load(decoder: bool, vb: VarBuilder, shared: &Arc<Embedding>, cfg: &Config) -> Result<Self> {
  let block = (0..cfg.num_layers)
- .map(|i| T5Block::load(i == 0, decoder, vb.pp(&format!("block.{i}")), cfg))
+ .map(|i| T5Block::load(i == 0, decoder, vb.pp(format!("block.{i}")), cfg))
  .collect::<Result<Vec<_>>>()?;
  let final_layer_norm = T5LayerNorm::load(
  cfg.d_model,

diff --git a/candle-transformers/src/models/whisper/model.rs b/candle-transformers/src/models/whisper/model.rs
@@ -260,7 +260,7 @@ impl AudioEncoder {
  let positional_embedding = sinusoids(n_ctx, n_state, vb.device())?;
  let blocks = (0..cfg.encoder_layers)
  .map(|i| {
- ResidualAttentionBlock::load(n_state, n_head, false, vb.pp(&format!("layers.{i}")))
+ ResidualAttentionBlock::load(n_state, n_head, false, vb.pp(format!("layers.{i}")))
  })
  .collect::<Result<Vec<_>>>()?;
  let ln_post = layer_norm(n_state, vb.pp("layer_norm"))?;
@@ -321,7 +321,7 @@ impl TextDecoder {
  let positional_embedding = vb.get((n_ctx, n_state), "embed_positions.weight")?;
  let blocks = (0..cfg.decoder_layers)
  .map(|i| {
- ResidualAttentionBlock::load(n_state, n_head, true, vb.pp(&format!("layers.{i}")))
+ ResidualAttentionBlock::load(n_state, n_head, true, vb.pp(format!("layers.{i}")))
  })
  .collect::<Result<Vec<_>>>()?;
  let ln = layer_norm(n_state, vb.pp("layer_norm"))?;

diff --git a/candle-wasm-examples/llama2-c/src/model.rs b/candle-wasm-examples/llama2-c/src/model.rs
@@ -275,7 +275,7 @@ impl Llama {
  let lm_head = linear(cfg.dim, cfg.vocab_size, vb.pp("lm_head"))?;
  let norm = rms_norm(cfg.dim, cfg.norm_eps, vb.pp("model.norm"))?;
  let blocks: Vec<_> = (0..cfg.n_layers)
- .map(|i| Block::load(vb.pp(&format!("model.layers.{i}")), cache, cfg).unwrap())
+ .map(|i| Block::load(vb.pp(format!("model.layers.{i}")), cache, cfg).unwrap())
  .collect();
  Ok(Self::new(wte, blocks, norm, lm_head))
  }

diff --git a/candle-wasm-examples/yolo/src/model.rs b/candle-wasm-examples/yolo/src/model.rs
@@ -155,7 +155,7 @@ impl C2f {
  let cv2 = ConvBlock::load(vb.pp("cv2"), (2 + n) * c, c2, 1, 1, None)?;
  let mut bottleneck = Vec::with_capacity(n);
  for idx in 0..n {
- let b = Bottleneck::load(vb.pp(&format!("bottleneck.{idx}")), c, c, shortcut)?;
+ let b = Bottleneck::load(vb.pp(format!("bottleneck.{idx}")), c, c, shortcut)?;
  bottleneck.push(b)
  }
  Ok(Self {