huggingface/candle
1
0
Fork 0
mirror of https://github.com/huggingface/candle.git synced 2025-06-16 18:48:51 +00:00
Code Issues Packages Projects Releases Wiki Activity

Clippy fixes for 1.81.0. (#2461)

Browse Source 
* Clippy fixes for 1.81.0.

* Another fix.
This commit is contained in:
Laurent Mazare
2024-09-05 22:46:55 +01:00
committed by GitHub
parent c02b7c3272
commit e3261216b1
17 changed files with 28 additions and 29 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
candle-examples/examples/musicgen/musicgen_model.rs
View File

@ -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,

1
candle-examples/examples/silero-vad/main.rs
View File

@ -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 {

6
candle-examples/examples/yolo-v3/darknet.rs
View File

@ -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,

2
candle-examples/examples/yolo-v8/model.rs
View File

@ -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 {

6
candle-transformers/src/models/bert.rs
View File

@ -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 {

2
candle-transformers/src/models/bigcode.rs
View File

@ -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"))?;

6
candle-transformers/src/models/distilbert.rs
View File

@ -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 {

2
candle-transformers/src/models/falcon.rs
View File

@ -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,

2
candle-transformers/src/models/jina_bert.rs
View File

@ -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())?;

2
candle-transformers/src/models/llama.rs
View File

@ -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 {

2
candle-transformers/src/models/llama2_c.rs
View File

@ -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,

2
candle-transformers/src/models/moondream.rs
View File

@ -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,

8
candle-transformers/src/models/segformer.rs
View File

@ -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(

2
candle-transformers/src/models/t5.rs
View File

@ -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,

4
candle-transformers/src/models/whisper/model.rs
View File

@ -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"))?;

2
candle-wasm-examples/llama2-c/src/model.rs
View File

@ -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))
}

2
candle-wasm-examples/yolo/src/model.rs
View File

@ -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 {