Wasm llama2 tweaks (#309)

* Clean-up the llama2.c wasm example.

* Use a proper tokenizer.
This commit is contained in:
Laurent Mazare
2023-08-02 15:49:43 +01:00
committed by GitHub
parent 4f17290ce0
commit 186c308d51
6 changed files with 14 additions and 52 deletions

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@ -12,6 +12,7 @@ license.workspace = true
candle = { path = "../../candle-core", version = "0.1.0", package = "candle-core" }
candle-nn = { path = "../../candle-nn", version = "0.1.0" }
num-traits = { workspace = true }
tokenizers = { workspace = true, features = ["unstable_wasm"] }
# App crates.
anyhow = { workspace = true }

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@ -4,7 +4,7 @@
<meta charset="utf-8" />
<title>Welcome to Candle!</title>
<link data-trunk rel="copy-file" href="tokenizer.bin" />
<link data-trunk rel="copy-file" href="tokenizer.json" />
<link data-trunk rel="copy-file" href="model.bin" />
<link data-trunk rel="rust" href="Cargo.toml" data-bin="app" data-type="main" />
<link data-trunk rel="rust" href="Cargo.toml" data-bin="worker" data-type="worker" />

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@ -53,7 +53,7 @@ pub struct App {
}
async fn model_data_load() -> Result<ModelData, JsValue> {
let tokenizer = fetch_url("tokenizer.bin").await?;
let tokenizer = fetch_url("tokenizer.json").await?;
let model = fetch_url("model.bin").await?;
console_log!("{}", model.len());
Ok(ModelData { tokenizer, model })

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@ -1,28 +1,3 @@
#![allow(dead_code)]
pub const WITH_TIMER: bool = true;
struct Timer {
label: &'static str,
}
impl Timer {
fn new(label: &'static str) -> Self {
if WITH_TIMER {
web_sys::console::time_with_label(label);
}
Self { label }
}
}
impl Drop for Timer {
fn drop(&mut self) {
if WITH_TIMER {
web_sys::console::time_end_with_label(self.label)
}
}
}
mod app;
mod model;
mod worker;

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@ -106,14 +106,15 @@ struct CausalSelfAttention {
n_key_value_head: usize,
head_dim: usize,
cache: Cache,
max_seq_len: usize,
}
impl CausalSelfAttention {
fn apply_rotary_emb(&self, x: &Tensor, index_pos: usize) -> Result<Tensor> {
let (b_sz, seq_len, h, n_embd) = x.dims4()?;
let cos = self.cache.cos.narrow(0, index_pos, seq_len)?;
let sin = self.cache.sin.narrow(0, index_pos, seq_len)?;
let cos = self.cache.cos.i(index_pos..index_pos + seq_len)?;
let sin = self.cache.sin.i(index_pos..index_pos + seq_len)?;
let cos = cos.unsqueeze(1)?;
let sin = sin.unsqueeze(1)?;
let cos = cos.broadcast_as((b_sz, seq_len, 1, n_embd / 2, 1))?;
let sin = sin.broadcast_as((b_sz, seq_len, 1, n_embd / 2, 1))?;
let x = x.reshape((b_sz, seq_len, h, n_embd / 2, 2))?;
@ -196,7 +197,6 @@ impl CausalSelfAttention {
n_key_value_head: cfg.n_kv_heads,
head_dim: cfg.dim / cfg.n_heads,
cache: cache.clone(),
max_seq_len: cfg.seq_len,
})
}
}

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@ -4,6 +4,7 @@ use candle::{DType, Device, IndexOp, Result, Shape, Tensor, D};
use candle_nn::{ops::softmax, VarBuilder};
use rand::{distributions::Distribution, SeedableRng};
use serde::{Deserialize, Serialize};
use tokenizers::Tokenizer;
use wasm_bindgen::prelude::*;
use yew_agent::{HandlerId, Public, WorkerLink};
@ -48,23 +49,6 @@ fn read_tensor<R: std::io::Read, S: Into<Shape>>(
Ok(tensor)
}
struct Tokenizer {
tokens: Vec<String>,
}
impl Tokenizer {
fn from_reader<R: std::io::Read>(r: &mut R, c: &Config) -> Result<Self> {
let mut tokens = Vec::with_capacity(c.vocab_size);
for _token_index in 0..c.vocab_size {
let token_len = read_i32(r)?;
let mut token = vec![0u8; token_len as usize];
r.read_exact(&mut token)?;
tokens.push(String::from_utf8_lossy(&token).into_owned())
}
Ok(Self { tokens })
}
}
struct Model {
cache: Cache,
config: Config,
@ -129,8 +113,10 @@ impl Model {
let next_token = logits_processor.sample(&logits)?;
tokens.push(next_token);
let token = self.tokenizer.tokens[next_token as usize].clone();
link.respond(id, Ok(WorkerOutput::Generated(token)));
if let Some(text) = self.tokenizer.id_to_token(next_token) {
let text = text.replace('▁', " ").replace("<0x0A>", "\n");
link.respond(id, Ok(WorkerOutput::Generated(text)));
}
}
Ok(())
}
@ -282,8 +268,8 @@ impl Model {
let vb = weights.var_builder(&config, &dev)?;
let cache = Cache::new(true, &config, vb.pp("rot"))?;
let llama = Llama::load(vb, &cache, &config)?;
let mut tokenizer = std::io::Cursor::new(md.tokenizer);
let tokenizer = Tokenizer::from_reader(&mut tokenizer, &config)?;
let tokenizer =
Tokenizer::from_bytes(&md.tokenizer).map_err(|m| candle::Error::Msg(m.to_string()))?;
Ok(Self {
cache,
config,